Datasets:

xpertsystems
/

hlt013-sample

+---
+license: cc-by-nc-4.0
+task_categories:
+- tabular-classification
+- tabular-regression
+language:
+- en
+tags:
+- synthetic
+- healthcare
+- genomics
+- variant-calling
+- vcf
+- vep
+- cadd
+- clinvar
+- gnomad
+- rna-seq
+- bulk-rna-seq
+- single-cell
+- scrna-seq
+- pbmc
+- gene-expression
+- polygenic-risk-score
+- prs
+- pharmacogenomics
+- pgx
+- cpic
+- pharmgkb
+- cyp2d6
+- cyp2c19
+- ancestry
+- grch38
+- hg38
+- titv
+- hardy-weinberg
+- tabula-sapiens
+- gtex
+- 10x-genomics
+pretty_name: HLT-013 Synthetic Multi-Modal Genomics Dataset (Sample Preview)
+size_categories:
+- 1K<n<10K
+---
+# HLT-013 — Synthetic Multi-Modal Genomics Dataset (Sample Preview)
+**A free, schema-identical preview of the full HLT-013 commercial product from [XpertSystems.ai](https://xpertsystems.ai).**
+A **fully synthetic** multi-modal genomics dataset combining **variant calls** (VCF-style with VEP/CADD/ClinVar/gnomAD annotations), **bulk RNA-seq gene expression** (5 tissues × 2,000 genes), **single-cell RNA-seq PBMC profiles** (10 cell types), **polygenic risk scores** (50 traits across 5 disease domains), and **pharmacogenomics star allele calls** (25 CPIC-actionable genes) — all linked through 1,000 individuals across 5 ancestry superpopulations (EUR/AFR/EAS/AMR/SAS, gnomAD-calibrated).
+> ⚠️ **PRIVACY & SYNTHETIC NATURE**
+> Every record in this dataset is **100% synthetic**. **No real patient data, no PHI, no real genome sequences, no real variant calls.** Population-level distributions match published gnomAD / ClinVar / VEP / CPIC / Tabula Sapiens benchmarks but the genomic profiles are computationally generated.
+---
+## What's in this sample
+**1,000 individuals × 6 multi-modal genomic data tables linked by `sample_id`.**
+| File | Rows × Cols | Description |
+|---|---|---|
+| `cohort_manifest.csv` | 1,000 × 10 | Individual master — ancestry, sex, age, sequencing type, mean coverage, pct bases ≥20x, consent tier |
+| `variants_annotated.csv` | 600 × 14 | VCF-style: CHROM/POS/RSID/REF/ALT/GT/GQ/DP + VEP consequence + CADD Phred + ClinVar sig + gnomAD AF + HWE p-value |
+| `gene_expression.csv` | 2,000 × 7 | Bulk RNA-seq gene panel — mean log2TPM, SD, CV, % expressed, housekeeping flag |
+| `scrna_pbmc.csv` | ~1,900 × 11 | Single-cell PBMC: cell type, cluster ID, UMAP coords, n_genes, n_counts, pct_mito, doublet score |
+| `polygenic_risk_scores.csv` | 1,000 × 152 | 50 PRS traits × (raw score + ancestry-adjusted percentile + risk tier) per individual |
+| `pharmacogenomics.csv` | 1,000 × 102 | 25 PGx genes × (star allele class + CPIC recommendation + ACMG actionable + drug-specific guidance) |
+| `metadata.json` | — | Run manifest: seed, genome build, ancestry distribution, Ti/Tv, tissue/cell-type/PRS/PGx counts |
+**Total:** ~2.4 MB across 8 files.
+---
+## Schema highlights
+### `cohort_manifest.csv` (10 columns)
+`sample_id`, `ancestry_superpop` (EUR/AFR/EAS/AMR/SAS), `sex`, `age`, `cohort_id`, `genome_build` (GRCh38), `sequencing_type` (WGS/WES), `mean_coverage` (numeric, 30x WGS / 100x WES mix), `pct_bases_20x` (QC metric), `consent_tier` (research/clinical/broad)
+### `variants_annotated.csv` (14 columns)
+**Position:** `CHROM` (1-22, X), `POS` (genomic coordinate), `RSID` (rs identifier), `REF`, `ALT`, `variant_type` (SNP/InDel)
+**Genotype:** `GT` (0/0, 0/1, 1/1), `GQ` (genotype quality 0-99), `DP` (read depth)
+**Annotation:** `consequence` (VEP terms: intergenic / intron / synonymous / missense / 3'UTR / 5'UTR / splice_region / stop_gained / splice_donor / splice_acceptor / frameshift / inframe_indel), `CADD_phred` (deleteriousness 0-50+), `ClinVar_sig` (Benign / Likely_benign / VUS / Likely_pathogenic / Pathogenic), `AF_gnomAD` (allele frequency 0-1)
+**Population genetics:** `HWE_pval` (Hardy-Weinberg Equilibrium p-value)
+### `gene_expression.csv` (7 columns)
+`gene_id` (ENSG-style), `gene_name`, `mean_log2TPM`, `sd_log2TPM`, `cv` (coefficient of variation), `pct_expressed` (% of individuals with detectable expression), `is_housekeeping` (flag for stably-expressed reference genes)
+### `scrna_pbmc.csv` (11 columns)
+`sample_id`, `cell_barcode`, `cell_type` (10 types: CD4_T_naive, CD4_T_memory, CD8_T_cytotoxic, B_cell_naive, B_cell_memory, NK_cell, Monocyte_classical, Monocyte_nonclassical, pDC, Platelet), `cluster_id`, `UMAP_1`, `UMAP_2`, `n_genes`, `n_counts`, `pct_mito`, `doublet_score`, `cell_type_confidence`
+### `polygenic_risk_scores.csv` (152 columns)
+`sample_id`, `ancestry`, plus **50 traits × 3 fields each**:
+- `PRS_<trait>` — raw polygenic score
+- `PRS_<trait>_pct` — ancestry-adjusted percentile (0-100)
+- `PRS_<trait>_tier` — risk tier (Low/Intermediate/High)
+**50 traits across 5 domains:**
+- **CVD (10):** coronary_artery_disease, atrial_fibrillation, heart_failure, hypertension, stroke, peripheral_artery_disease, abdominal_aortic_aneurysm, hypertrophic_cardiomyopathy, dilated_cardiomyopathy, long_qt_syndrome
+- **Metabolic (10):** type2_diabetes, BMI, LDL_cholesterol, HDL_cholesterol, triglycerides, fasting_glucose, HbA1c, type1_diabetes, obesity, NAFLD
+- **Oncology (10):** breast_cancer, prostate_cancer, colorectal_cancer, lung_cancer, melanoma, ovarian_cancer, pancreatic_cancer, glioma, leukemia, lymphoma
+- **Autoimmune (10):** rheumatoid_arthritis, type1_diabetes_autoimmune, MS, lupus, psoriasis, IBD_crohns, IBD_ulcerative_colitis, celiac, asthma, atopic_dermatitis
+- **Psychiatric (10):** depression, bipolar, schizophrenia, anxiety, ADHD, autism, alzheimers, parkinsons, alcohol_dependence, smoking_behavior
+### `pharmacogenomics.csv` (102 columns)
+`sample_id`, `ancestry`, plus **25 genes × 4 fields each**:
+- `PGx_<gene>_class` — predicted phenotype (NM=Normal Metabolizer / IM=Intermediate / PM=Poor / RM=Rapid / UM=Ultrarapid)
+- `PGx_<gene>_CPIC` — CPIC dosing recommendation (Standard/Reduce/Increase/Avoid)
+- `PGx_<gene>_ACMG_actionable` — ACMG SF v3.2 actionable flag
+- `PGx_<gene>_recommendation` — drug-specific guidance text
+**25 genes (CPIC Level A or B):** CYP2D6, CYP2C19, CYP2C9, CYP3A5, CYP2B6, CYP1A2, TPMT, NUDT15, DPYD, SLCO1B1, VKORC1, UGT1A1, HLA-B, HLA-A, CYP4F2, IFNL3, G6PD, RYR1, CACNA1S, ABCG2, F5, MTHFR, NAT2, ATM, BRCA1
+---
+## Calibration source story
+The full HLT-013 generator anchors all distributions to authoritative genomics references:
+- **gnomAD v4 (Karczewski et al. 2020)** — Population allele frequencies, ancestry superpopulation proportions
+- **VEP (McLaren et al. 2016)** — Variant Effect Predictor consequence annotation
+- **ClinVar (Landrum et al. 2018)** — Clinical variant significance database
+- **CADD (Rentzsch et al. 2019)** — Combined Annotation Dependent Depletion scores
+- **CPIC** — Clinical Pharmacogenetics Implementation Consortium dosing guidelines
+- **PharmGKB** — Gene-drug interaction knowledge base
+- **10x Genomics PBMC 10k reference** — Single-cell PBMC cell type proportions
+- **Tabula Sapiens (Quake Lab)** — Cross-tissue cell type catalog
+- **GTEx Consortium** — Tissue-specific gene expression
+- **PGS Catalog (Lambert et al. 2021)** — Polygenic score trait coverage
+- **ACMG SF v3.2** — Secondary findings actionable variant list
+### Sample-scale validation scorecard
+| Metric | Observed | Target | Status | Source |
+|---|---|---|---|---|
+| EUR ancestry share | 40.2% | 40% ± 5% | ✅ PASS | gnomAD v4 |
+| Ancestry superpop count | 5 | 5 | ✅ PASS | gnomAD |
+| Ti/Tv ratio | 2.31 | 2.06 ± 0.80 | ✅ PASS | Wang et al. (2015) |
+| ClinVar P/LP rate | 2.3% | 2.5% ± 2.5% | ✅ PASS | ClinVar |
+| Mean coverage | 42.1x | 42 ± 10 | ✅ PASS | Clinical genomics QC |
+| Cell type diversity | 10 | 10 | ✅ PASS | 10x Genomics PBMC 10k |
+| PRS trait count | 50 | 50 | ✅ PASS | PGS Catalog |
+| PGx gene count | 25 | 25 | ✅ PASS | CPIC Level A/B |
+| CYP2D6 NM rate | 66.7% | 65% ± 15% | ✅ PASS | CPIC + PharmGKB |
+| Expression tissue count | 5 | 5 | ✅ PASS | Tabula Sapiens / GTEx |
+**Grade: A+ (100/100) — verified across 6 random seeds (42, 7, 123, 2024, 99, 1).**
+---
+## Loading examples
+### Pandas — explore the cohort
+```python
+import pandas as pd
+cohort = pd.read_csv("cohort_manifest.csv")
+variants = pd.read_csv("variants_annotated.csv")
+prs = pd.read_csv("polygenic_risk_scores.csv")
+pgx = pd.read_csv("pharmacogenomics.csv")
+# Ancestry distribution
+print(cohort["ancestry_superpop"].value_counts(normalize=True).round(3))
+# Variant consequence breakdown
+print(variants["consequence"].value_counts(normalize=True).round(3))
+# ClinVar significance
+print(variants["ClinVar_sig"].value_counts())
+```
+### Variant filtering
+```python
+import pandas as pd
+variants = pd.read_csv("variants_annotated.csv")
+# High-impact variants (Pathogenic + CADD > 25)
+high_impact = variants[
+    (variants["ClinVar_sig"].isin(["Pathogenic", "Likely_pathogenic"])) |
+    (variants["CADD_phred"] > 25)
+]
+print(f"High-impact variants: {len(high_impact)}")
+# Rare variants (gnomAD AF < 1%)
+rare = variants[variants["AF_gnomAD"] < 0.01]
+print(f"Rare variants: {len(rare)}")
+# HWE-departure variants
+hwe_violations = variants[variants["HWE_pval"] < 0.001]
+print(f"HWE violations: {len(hwe_violations)}")
+```
+### PRS risk stratification
+```python
+import pandas as pd
+prs = pd.read_csv("polygenic_risk_scores.csv")
+# Top 10% CAD risk individuals
+high_cad = prs[prs["PRS_coronary_artery_disease_pct"] >= 90]
+print(f"High CAD risk: {len(high_cad)} individuals")
+# Multi-trait risk profile
+risk_traits = ["coronary_artery_disease", "type2_diabetes", "breast_cancer"]
+for trait in risk_traits:
+    tier_col = f"PRS_{trait}_tier"
+    if tier_col in prs.columns:
+        print(f"\n{trait} risk tier distribution:")
+        print(prs[tier_col].value_counts(normalize=True).round(3))
+```
+### PGx phenotype distribution
+```python
+import pandas as pd
+pgx = pd.read_csv("pharmacogenomics.csv")
+# CYP2D6 phenotype by ancestry
+print(pd.crosstab(pgx["ancestry"], pgx["PGx_CYP2D6_class"], normalize="index").round(3))
+# Actionable findings (ACMG SF v3.2)
+actionable_cols = [c for c in pgx.columns if c.endswith("_ACMG_actionable")]
+n_actionable = pgx[actionable_cols].sum(axis=1)
+print(f"\nIndividuals with ≥1 actionable PGx finding:")
+print(f"  None:    {(n_actionable == 0).sum()}")
+print(f"  1 gene:  {(n_actionable == 1).sum()}")
+print(f"  2+ genes: {(n_actionable >= 2).sum()}")
+```
+### scRNA-seq cell type analysis
+```python
+import pandas as pd
+scrna = pd.read_csv("scrna_pbmc.csv")
+# Cell type proportions per sample
+cell_pcts = scrna.groupby("sample_id")["cell_type"].value_counts(normalize=True).unstack(fill_value=0)
+print("Mean cell type proportions:")
+print(cell_pcts.mean().sort_values(ascending=False).round(3))
+# QC metrics by cell type
+print("\nQC metrics by cell type:")
+print(scrna.groupby("cell_type")[["n_genes", "pct_mito", "doublet_score"]].mean().round(2))
+```
+### Hugging Face Datasets
+```python
+from datasets import load_dataset
+ds = load_dataset("xpertsystems/hlt013-sample", data_files={
+    "cohort":     "cohort_manifest.csv",
+    "variants":   "variants_annotated.csv",
+    "expression": "gene_expression.csv",
+    "scrna":      "scrna_pbmc.csv",
+    "prs":        "polygenic_risk_scores.csv",
+    "pgx":        "pharmacogenomics.csv",
+})
+print(ds)
+```
+---
+## Suggested use cases
+- **Variant prioritization ML** — train classifiers on CADD + ClinVar + AF features to predict pathogenicity
+- **PRS-disease prediction modeling** — multi-trait ML for absolute risk stratification
+- **Ancestry imputation** — train ancestry callers from variant features
+- **Variant Effect Predictor pipeline testing** — schema-compliant data for VEP/SnpEff annotation pipeline development
+- **Pharmacogenomic CDS rules engine testing** — populate PGx clinical decision support systems
+- **scRNA-seq cell type classification** — train cell type callers from gene expression + UMAP coordinates
+- **HWE violation detection** — flag spurious genotype calls or population structure
+- **Multi-modal genomics integration** — joint modeling across variants + expression + PRS + PGx
+- **Clinical genomics LIMS testing** — populate clinical genomics pipelines with realistic synthetic patients
+- **Healthcare AI pretraining** — pretrain models on synthetic genomic profiles before fine-tuning on real biobank data
+- **Educational use** — graduate genomics, biostatistics, and precision medicine coursework
+---
+## Sample vs. full product
+| Aspect | This sample | Full HLT-013 product |
+|---|---|---|
+| Individuals | 1,000 | 100,000+ (default) up to 1M |
+| Variants per individual | 600 representative | Full WGS ~6.5M variants |
+| Genes (bulk expression) | 2,000 | Full transcriptome ~20,000 genes |
+| scRNA cells per sample | ~2 (sampled) | ~200 cells per sample |
+| PRS traits | 50 | 50 (full coverage) |
+| PGx genes | 25 | 25 (full CPIC Level A/B coverage) |
+| Schema | identical | identical |
+| Calibration | identical | identical |
+| License | CC-BY-NC-4.0 | Commercial license |
+The full product unlocks:
+- **Up to 1M individuals** for biobank-scale genomic ML training
+- **Full WGS variant calls** (~6.5M variants per individual)
+- **Full transcriptome** (20,000+ genes)
+- **Dense scRNA-seq profiles** (200+ cells per sample)
+- **GWAS summary statistics** for the 50 PRS traits
+- **Family pedigrees** for trio/quartet analysis
+- Commercial use rights
+**Contact us for the full product.**
+---
+## Limitations & honest disclosures
+- **Sample is preview-only.** 1,000 individuals × 600 representative variants is enough to demonstrate schema and calibration, but is **not statistically sufficient** for serious GWAS, PRS development, or rare variant analysis. Use the full product (100K+) for serious work.
+- **Variant set is sub-sampled.** Each individual carries 600 representative variants (mix of SNPs + InDels), not the ~6.5M variants from full WGS. Variant positions are real-coordinate-valid but sparse.
+- **scRNA-seq cells per sample are sparse (~2 cells/sample at preview scale).** Real PBMC scRNA-seq experiments yield 200-1000 cells per sample. The sample compresses this for size — full product has dense per-sample profiles.
+- **Gene expression is panel-summary, not per-individual.** The `gene_expression.csv` file gives population-level summary statistics (mean log2TPM, SD, CV) across the 1,000 individuals, NOT individual-specific TPM values. For per-individual expression matrices, use the full product.
+- **Housekeeping gene flag rate runs slightly high (~7.5% vs typical 1-3%).** The generator marks more genes as housekeeping than strict biological definitions. Cross-reference with HK genes lists (Eisenberg & Levanon 2013) if exact housekeeping calls matter.
+- **Ti/Tv ratio variance is high at 600-variant sample scale (1.78-2.68 across seeds vs target 2.06).** This is small-sample noise — full WGS at 6.5M variants converges tightly to the gnomAD target.
+- **RSIDs are synthetic.** Generated RSIDs follow the rsXXXXXXX format but do NOT correspond to real dbSNP entries.
+- **gnomAD AF values are sampled from realistic distributions but are NOT real allele frequencies.** Do not use this data for variant frequency reporting.
+- **ClinVar IDs not included.** Variants have `ClinVar_sig` classifications but no real ClinVar variation IDs.
+- **PRS scores are simulated, not based on real GWAS effect sizes.** Distributions match published PRS percentile shapes but specific scores do NOT reflect real allele effects.
+- **PGx phenotype calls follow CPIC frequency distributions but are NOT mechanistic.** Star allele class assignments are population-frequency-driven, not derived from underlying CYP/TPMT/etc. variant calls in `variants_annotated.csv`.
+- **Synthetic, not derived from real biobank data.** Distributions match published gnomAD/ClinVar/CPIC/Tabula Sapiens references but do NOT reflect any specific real cohort (UK Biobank, All of Us, etc.).
+---
+## Ethical use guidance
+This dataset is designed for:
+- Genomic ML methodology development
+- Clinical genomics pipeline testing
+- PRS modeling research
+- Pharmacogenomics CDS rule engine development
+- scRNA-seq cell type annotation methodology
+- Healthcare AI pretraining for genomic prediction tasks
+- Educational use in clinical genomics, precision medicine, and biostatistics
+This dataset is **not appropriate for**:
+- Making clinical genetic diagnoses about real individuals
+- Real PRS reporting for real patients without validated ancestry-matched reference panels
+- Pharmacogenomic prescribing decisions for real patients without CPIC consultation
+- Variant pathogenicity calls without ACMG framework validation on real ClinVar data
+- Ancestry-based discriminatory modeling
+- Population-genetic claims about real ethnic groups
+---
+## Companion datasets in the Healthcare vertical
+- [HLT-001](https://huggingface.co/datasets/xpertsystems/hlt001-sample) — Synthetic Patient Population (CDC/NHANES)
+- [HLT-002](https://huggingface.co/datasets/xpertsystems/hlt002-sample) — Synthetic EHR (FHIR R4)
+- [HLT-003](https://huggingface.co/datasets/xpertsystems/hlt003-sample) — Synthetic Clinical Trial
+- [HLT-004](https://huggingface.co/datasets/xpertsystems/hlt004-sample) — Synthetic Disease Progression
+- [HLT-005](https://huggingface.co/datasets/xpertsystems/hlt005-sample) — Synthetic Hospital Admission
+- [HLT-006](https://huggingface.co/datasets/xpertsystems/hlt006-sample) — Synthetic Medical Imaging
+- [HLT-007](https://huggingface.co/datasets/xpertsystems/hlt007-sample) — Synthetic Drug Response
+- [HLT-008](https://huggingface.co/datasets/xpertsystems/hlt008-sample) — Synthetic Healthcare Claims
+- [HLT-009](https://huggingface.co/datasets/xpertsystems/hlt009-sample) — Synthetic ICU Vital Sign Monitoring
+- [HLT-010](https://huggingface.co/datasets/xpertsystems/hlt010-sample) — Synthetic Hospital Resource Usage
+- [HLT-011](https://huggingface.co/datasets/xpertsystems/hlt011-sample) — Synthetic Rare Disease + Trial Eligibility
+- [HLT-012](https://huggingface.co/datasets/xpertsystems/hlt012-sample) — Synthetic Pandemic Spread
+- **HLT-013** — Synthetic Multi-Modal Genomics (you are here)
+Use **HLT-001 through HLT-013 together** for the full healthcare data stack — and HLT-013 specifically extends the catalog into **precision medicine & clinical genomics**, complementing HLT-007 (drug response with PGx hooks) and HLT-011 (rare disease with gene-variant calls).
+---
+## Citation
+If you use this dataset, please cite:
+```bibtex
+@dataset{xpertsystems_hlt013_sample_2026,
+  author       = {XpertSystems.ai},
+  title        = {HLT-013 Synthetic Multi-Modal Genomics Dataset (Sample Preview)},
+  year         = 2026,
+  publisher    = {Hugging Face},
+  url          = {https://huggingface.co/datasets/xpertsystems/hlt013-sample}
+}
+```
+---
+## Contact
+- **Web:** [https://xpertsystems.ai](https://xpertsystems.ai)
+- **Email:** [pradeep@xpertsystems.ai](mailto:pradeep@xpertsystems.ai)
+- **Full product catalog:** Cybersecurity, Insurance & Risk, Materials & Energy, Oil & Gas, Healthcare, and more
+**Sample License:** CC-BY-NC-4.0 (Creative Commons Attribution-NonCommercial 4.0)
+**Full product License:** Commercial — please contact for pricing.

cohort_manifest.csv ADDED Viewed

	@@ -0,0 +1,1001 @@

+sample_id,ancestry_superpop,sex,age,cohort_id,genome_build,sequencing_type,mean_coverage,pct_bases_20x,consent_tier
+HLT013_000001,EAS,Female,31,COHORT_A,GRCh38,WES,55.1,96.79,TIER1
+HLT013_000002,AFR,Female,61,COHORT_A,GRCh38,WGS,29.9,95.94,TIER2
+HLT013_000003,AMR,Female,20,COHORT_B,GRCh38,WGS,45.9,91.15,TIER2
+HLT013_000004,EAS,Male,20,COHORT_A,GRCh38,WGS,48.1,96.16,TIER2
+HLT013_000005,EUR,Female,49,COHORT_B,GRCh38,WES,25.3,92.95,TIER1
+HLT013_000006,SAS,Female,61,COHORT_A,GRCh38,WGS,33.5,92.89,TIER1
+HLT013_000007,EAS,Male,27,COHORT_C,GRCh38,WGS,30.7,98.39,TIER1
+HLT013_000008,EAS,Male,19,COHORT_B,GRCh38,WES,26.9,94.45,TIER2
+HLT013_000009,EUR,Male,32,COHORT_A,GRCh38,WES,57.4,89.95,TIER1
+HLT013_000010,AFR,Female,58,COHORT_A,GRCh38,WGS,31.9,97.58,TIER1
+HLT013_000011,EUR,Male,79,COHORT_B,GRCh38,WES,55.5,92.56,TIER3
+HLT013_000012,SAS,Male,29,COHORT_C,GRCh38,WES,51.3,90.27,TIER3
+HLT013_000013,EAS,Female,50,COHORT_B,GRCh38,WGS,28.3,95.07,TIER3
+HLT013_000014,AMR,Female,39,COHORT_B,GRCh38,WGS,48.0,91.61,TIER2
+HLT013_000015,AFR,Female,30,COHORT_A,GRCh38,WGS,31.0,94.67,TIER3
+HLT013_000016,EUR,Male,77,COHORT_C,GRCh38,WGS,26.9,96.09,TIER1
+HLT013_000017,AFR,Male,37,COHORT_C,GRCh38,WES,48.9,89.79,TIER3
+HLT013_000018,EUR,Male,58,COHORT_A,GRCh38,WES,50.9,95.83,TIER2
+HLT013_000019,AMR,Female,25,COHORT_C,GRCh38,WGS,45.4,94.92,TIER2
+HLT013_000020,EAS,Male,21,COHORT_C,GRCh38,WGS,27.3,96.9,TIER2
+HLT013_000021,EAS,Female,36,COHORT_A,GRCh38,WGS,59.4,98.85,TIER2
+HLT013_000022,EUR,Female,42,COHORT_B,GRCh38,WES,42.9,95.35,TIER2
+HLT013_000023,SAS,Female,50,COHORT_B,GRCh38,WES,39.9,93.34,TIER3
+HLT013_000024,AMR,Male,53,COHORT_C,GRCh38,WES,58.0,98.13,TIER1
+HLT013_000025,EAS,Female,31,COHORT_B,GRCh38,WGS,53.1,88.26,TIER2
+HLT013_000026,EUR,Male,86,COHORT_B,GRCh38,WES,58.4,96.44,TIER1
+HLT013_000027,AFR,Male,43,COHORT_A,GRCh38,WGS,30.0,94.02,TIER1
+HLT013_000028,EUR,Male,85,COHORT_B,GRCh38,WGS,44.7,96.0,TIER3
+HLT013_000029,EUR,Male,59,COHORT_C,GRCh38,WGS,41.7,95.07,TIER3
+HLT013_000030,EAS,Female,27,COHORT_C,GRCh38,WGS,42.7,96.56,TIER1
+HLT013_000031,EAS,Male,43,COHORT_A,GRCh38,WGS,41.5,89.28,TIER1
+HLT013_000032,SAS,Female,25,COHORT_A,GRCh38,WGS,59.6,93.45,TIER3
+HLT013_000033,EUR,Male,42,COHORT_C,GRCh38,WES,53.1,98.37,TIER3
+HLT013_000034,EUR,Male,33,COHORT_A,GRCh38,WGS,54.8,94.31,TIER1
+HLT013_000035,AFR,Female,86,COHORT_B,GRCh38,WGS,43.6,89.65,TIER3
+HLT013_000036,EUR,Female,62,COHORT_B,GRCh38,WES,37.9,95.43,TIER2
+HLT013_000037,EUR,Male,67,COHORT_B,GRCh38,WGS,34.5,97.56,TIER3
+HLT013_000038,AFR,Male,87,COHORT_B,GRCh38,WGS,51.6,95.82,TIER2
+HLT013_000039,EUR,Female,36,COHORT_C,GRCh38,WGS,54.2,92.52,TIER3
+HLT013_000040,EAS,Female,36,COHORT_B,GRCh38,WES,49.4,96.82,TIER1
+HLT013_000041,AFR,Female,61,COHORT_A,GRCh38,WES,27.0,93.82,TIER1
+HLT013_000042,AMR,Female,68,COHORT_C,GRCh38,WGS,32.0,90.1,TIER1
+HLT013_000043,EAS,Female,53,COHORT_B,GRCh38,WGS,44.9,96.56,TIER3
+HLT013_000044,EUR,Male,21,COHORT_C,GRCh38,WES,40.4,93.38,TIER2
+HLT013_000045,AMR,Male,72,COHORT_B,GRCh38,WGS,32.3,94.45,TIER1
+HLT013_000046,AMR,Male,59,COHORT_C,GRCh38,WES,56.4,97.04,TIER2
+HLT013_000047,EUR,Male,71,COHORT_C,GRCh38,WES,31.4,89.18,TIER3
+HLT013_000048,EUR,Female,43,COHORT_A,GRCh38,WGS,55.7,92.72,TIER3
+HLT013_000049,EAS,Male,65,COHORT_B,GRCh38,WGS,40.1,98.93,TIER1
+HLT013_000050,EUR,Female,29,COHORT_C,GRCh38,WES,34.2,92.84,TIER2
+HLT013_000051,EUR,Male,34,COHORT_B,GRCh38,WES,51.2,96.99,TIER3
+HLT013_000052,EUR,Male,27,COHORT_B,GRCh38,WGS,45.2,91.25,TIER2
+HLT013_000053,EAS,Female,83,COHORT_A,GRCh38,WGS,59.5,88.34,TIER3
+HLT013_000054,EAS,Male,56,COHORT_C,GRCh38,WGS,50.2,90.23,TIER1
+HLT013_000055,EAS,Female,31,COHORT_C,GRCh38,WES,40.2,92.51,TIER1
+HLT013_000056,EAS,Female,23,COHORT_C,GRCh38,WES,25.9,94.93,TIER2
+HLT013_000057,AFR,Female,39,COHORT_C,GRCh38,WES,33.7,90.28,TIER2
+HLT013_000058,AFR,Male,32,COHORT_B,GRCh38,WGS,40.9,89.02,TIER1
+HLT013_000059,EUR,Male,61,COHORT_A,GRCh38,WGS,49.8,98.26,TIER3
+HLT013_000060,EUR,Female,22,COHORT_C,GRCh38,WGS,59.9,94.86,TIER1
+HLT013_000061,EAS,Male,38,COHORT_C,GRCh38,WGS,57.0,93.23,TIER2
+HLT013_000062,AFR,Female,52,COHORT_B,GRCh38,WES,46.5,96.25,TIER1
+HLT013_000063,AFR,Female,26,COHORT_A,GRCh38,WES,54.6,97.52,TIER3
+HLT013_000064,EAS,Male,25,COHORT_A,GRCh38,WES,37.5,94.58,TIER2
+HLT013_000065,EAS,Male,53,COHORT_C,GRCh38,WGS,33.8,89.79,TIER1
+HLT013_000066,AFR,Male,88,COHORT_B,GRCh38,WES,57.2,99.0,TIER2
+HLT013_000067,AFR,Male,36,COHORT_A,GRCh38,WGS,26.9,95.54,TIER1
+HLT013_000068,EUR,Female,20,COHORT_C,GRCh38,WGS,31.4,94.71,TIER1
+HLT013_000069,EUR,Male,37,COHORT_B,GRCh38,WGS,42.4,96.71,TIER1
+HLT013_000070,AFR,Male,31,COHORT_A,GRCh38,WGS,48.2,93.3,TIER1
+HLT013_000071,EUR,Male,46,COHORT_C,GRCh38,WGS,38.6,89.23,TIER3
+HLT013_000072,AFR,Female,77,COHORT_B,GRCh38,WGS,48.8,93.67,TIER2
+HLT013_000073,AMR,Male,53,COHORT_B,GRCh38,WES,36.8,88.25,TIER2
+HLT013_000074,EUR,Female,89,COHORT_C,GRCh38,WGS,28.6,93.98,TIER2
+HLT013_000075,EUR,Male,25,COHORT_B,GRCh38,WGS,59.2,88.66,TIER2
+HLT013_000076,EUR,Male,33,COHORT_C,GRCh38,WES,54.4,89.25,TIER2
+HLT013_000077,EUR,Male,36,COHORT_B,GRCh38,WES,55.6,95.95,TIER2
+HLT013_000078,EAS,Female,62,COHORT_A,GRCh38,WES,47.6,95.78,TIER3
+HLT013_000079,AFR,Female,27,COHORT_A,GRCh38,WGS,44.0,93.63,TIER1
+HLT013_000080,EAS,Female,19,COHORT_C,GRCh38,WES,44.4,92.68,TIER1
+HLT013_000081,EAS,Male,36,COHORT_C,GRCh38,WES,25.3,88.63,TIER3
+HLT013_000082,AFR,Female,58,COHORT_C,GRCh38,WGS,29.3,90.62,TIER3
+HLT013_000083,AMR,Male,67,COHORT_A,GRCh38,WGS,51.5,92.35,TIER3
+HLT013_000084,EUR,Female,82,COHORT_B,GRCh38,WGS,58.5,92.94,TIER3
+HLT013_000085,EUR,Male,85,COHORT_B,GRCh38,WES,34.6,93.39,TIER2
+HLT013_000086,EUR,Female,41,COHORT_B,GRCh38,WGS,46.9,89.37,TIER3
+HLT013_000087,EAS,Male,48,COHORT_B,GRCh38,WES,40.0,90.38,TIER2
+HLT013_000088,AFR,Male,72,COHORT_C,GRCh38,WES,53.1,92.09,TIER1
+HLT013_000089,EUR,Male,19,COHORT_C,GRCh38,WGS,45.3,88.27,TIER3
+HLT013_000090,AFR,Male,86,COHORT_A,GRCh38,WES,45.1,95.3,TIER1
+HLT013_000091,EUR,Male,30,COHORT_A,GRCh38,WES,36.1,96.24,TIER3
+HLT013_000092,EAS,Female,54,COHORT_B,GRCh38,WGS,53.5,91.82,TIER3
+HLT013_000093,AFR,Female,58,COHORT_C,GRCh38,WES,58.2,93.38,TIER1
+HLT013_000094,EUR,Male,77,COHORT_B,GRCh38,WES,32.8,92.95,TIER3
+HLT013_000095,EUR,Female,37,COHORT_B,GRCh38,WGS,56.2,88.31,TIER2
+HLT013_000096,EAS,Female,50,COHORT_C,GRCh38,WGS,34.4,91.9,TIER2
+HLT013_000097,EUR,Female,42,COHORT_C,GRCh38,WES,36.5,98.34,TIER2
+HLT013_000098,EUR,Female,76,COHORT_A,GRCh38,WES,28.7,94.88,TIER3
+HLT013_000099,EUR,Female,88,COHORT_C,GRCh38,WGS,54.1,96.43,TIER1
+HLT013_000100,SAS,Male,83,COHORT_B,GRCh38,WGS,39.2,91.6,TIER2
+HLT013_000101,AMR,Female,35,COHORT_C,GRCh38,WES,56.3,88.81,TIER2
+HLT013_000102,EAS,Male,58,COHORT_B,GRCh38,WES,31.1,94.44,TIER1
+HLT013_000103,EUR,Male,50,COHORT_B,GRCh38,WGS,35.7,98.58,TIER1
+HLT013_000104,SAS,Male,70,COHORT_C,GRCh38,WGS,29.5,97.35,TIER2
+HLT013_000105,EAS,Male,48,COHORT_A,GRCh38,WGS,37.6,91.18,TIER2
+HLT013_000106,EAS,Male,39,COHORT_C,GRCh38,WGS,25.7,94.69,TIER2
+HLT013_000107,AFR,Female,35,COHORT_B,GRCh38,WES,37.0,95.66,TIER2
+HLT013_000108,EUR,Male,80,COHORT_B,GRCh38,WES,32.1,95.26,TIER2
+HLT013_000109,EUR,Female,34,COHORT_C,GRCh38,WGS,60.0,93.75,TIER3
+HLT013_000110,AMR,Male,86,COHORT_A,GRCh38,WGS,51.2,88.67,TIER2
+HLT013_000111,AFR,Female,48,COHORT_C,GRCh38,WGS,34.1,91.83,TIER3
+HLT013_000112,EUR,Male,65,COHORT_C,GRCh38,WES,39.4,90.78,TIER2
+HLT013_000113,EUR,Female,32,COHORT_C,GRCh38,WES,28.4,98.64,TIER3
+HLT013_000114,AFR,Female,45,COHORT_B,GRCh38,WGS,33.0,92.85,TIER2
+HLT013_000115,EUR,Female,26,COHORT_A,GRCh38,WGS,34.2,95.89,TIER3
+HLT013_000116,AMR,Female,32,COHORT_C,GRCh38,WES,45.0,89.97,TIER1
+HLT013_000117,EAS,Male,55,COHORT_B,GRCh38,WGS,40.9,91.35,TIER1
+HLT013_000118,EAS,Female,86,COHORT_A,GRCh38,WGS,30.6,88.72,TIER3
+HLT013_000119,AFR,Female,21,COHORT_A,GRCh38,WGS,39.3,92.57,TIER1
+HLT013_000120,EAS,Female,42,COHORT_A,GRCh38,WGS,48.6,92.91,TIER1
+HLT013_000121,AFR,Male,19,COHORT_C,GRCh38,WES,41.1,91.49,TIER3
+HLT013_000122,EAS,Female,76,COHORT_A,GRCh38,WGS,57.0,92.24,TIER2
+HLT013_000123,EUR,Male,44,COHORT_A,GRCh38,WES,36.1,96.23,TIER1
+HLT013_000124,AFR,Male,41,COHORT_A,GRCh38,WES,58.1,95.28,TIER1
+HLT013_000125,EUR,Male,86,COHORT_C,GRCh38,WGS,34.2,98.9,TIER1
+HLT013_000126,AFR,Female,20,COHORT_B,GRCh38,WGS,56.9,92.93,TIER1
+HLT013_000127,EUR,Male,23,COHORT_B,GRCh38,WGS,35.1,95.3,TIER3
+HLT013_000128,EUR,Female,30,COHORT_A,GRCh38,WES,35.7,91.13,TIER2
+HLT013_000129,EUR,Female,48,COHORT_A,GRCh38,WES,29.8,90.31,TIER2
+HLT013_000130,AFR,Female,86,COHORT_B,GRCh38,WGS,42.8,91.79,TIER3
+HLT013_000131,EUR,Male,83,COHORT_C,GRCh38,WGS,51.6,94.37,TIER2
+HLT013_000132,SAS,Female,22,COHORT_B,GRCh38,WGS,47.2,88.38,TIER2
+HLT013_000133,AFR,Female,41,COHORT_B,GRCh38,WGS,25.8,92.19,TIER3
+HLT013_000134,EUR,Male,31,COHORT_B,GRCh38,WGS,33.4,97.81,TIER2
+HLT013_000135,AFR,Male,57,COHORT_B,GRCh38,WES,25.6,91.62,TIER2
+HLT013_000136,EUR,Female,71,COHORT_A,GRCh38,WGS,43.3,97.45,TIER3
+HLT013_000137,SAS,Male,27,COHORT_B,GRCh38,WGS,32.8,96.47,TIER3
+HLT013_000138,AFR,Female,57,COHORT_A,GRCh38,WGS,50.8,97.16,TIER3
+HLT013_000139,EAS,Male,75,COHORT_C,GRCh38,WGS,30.8,88.81,TIER3
+HLT013_000140,EUR,Male,37,COHORT_C,GRCh38,WGS,50.6,90.85,TIER1
+HLT013_000141,AFR,Female,31,COHORT_B,GRCh38,WGS,44.8,93.29,TIER3
+HLT013_000142,AFR,Male,51,COHORT_C,GRCh38,WES,34.5,95.82,TIER1
+HLT013_000143,SAS,Female,89,COHORT_C,GRCh38,WES,32.3,94.25,TIER3
+HLT013_000144,AFR,Female,54,COHORT_C,GRCh38,WGS,31.1,88.07,TIER3
+HLT013_000145,AFR,Male,78,COHORT_C,GRCh38,WGS,28.4,92.33,TIER1
+HLT013_000146,EUR,Female,85,COHORT_A,GRCh38,WES,36.5,94.83,TIER1
+HLT013_000147,EUR,Male,80,COHORT_B,GRCh38,WGS,34.4,88.56,TIER1
+HLT013_000148,AFR,Male,66,COHORT_C,GRCh38,WGS,52.4,96.18,TIER3
+HLT013_000149,AFR,Male,81,COHORT_A,GRCh38,WES,46.1,92.76,TIER2
+HLT013_000150,EUR,Female,37,COHORT_A,GRCh38,WGS,36.4,90.09,TIER2
+HLT013_000151,AMR,Male,68,COHORT_C,GRCh38,WES,28.7,89.47,TIER1
+HLT013_000152,AMR,Male,19,COHORT_A,GRCh38,WES,59.7,94.29,TIER1
+HLT013_000153,EUR,Male,60,COHORT_C,GRCh38,WGS,58.2,93.66,TIER1
+HLT013_000154,AFR,Male,73,COHORT_C,GRCh38,WGS,49.5,91.16,TIER1
+HLT013_000155,EUR,Male,34,COHORT_B,GRCh38,WGS,35.5,96.66,TIER1
+HLT013_000156,EAS,Female,46,COHORT_C,GRCh38,WES,34.7,93.0,TIER2
+HLT013_000157,EUR,Female,56,COHORT_C,GRCh38,WGS,27.8,96.39,TIER1
+HLT013_000158,EAS,Female,87,COHORT_C,GRCh38,WGS,34.3,91.39,TIER3
+HLT013_000159,EAS,Male,53,COHORT_C,GRCh38,WGS,38.8,90.94,TIER1
+HLT013_000160,EAS,Female,38,COHORT_C,GRCh38,WGS,27.4,96.47,TIER1
+HLT013_000161,EUR,Female,85,COHORT_A,GRCh38,WES,30.3,99.0,TIER3
+HLT013_000162,AMR,Female,69,COHORT_A,GRCh38,WES,30.9,95.9,TIER1
+HLT013_000163,EUR,Female,69,COHORT_B,GRCh38,WGS,52.5,89.14,TIER1
+HLT013_000164,EUR,Female,82,COHORT_B,GRCh38,WGS,54.2,90.85,TIER1
+HLT013_000165,AFR,Male,44,COHORT_B,GRCh38,WGS,50.5,92.95,TIER1
+HLT013_000166,EUR,Male,50,COHORT_A,GRCh38,WES,39.7,91.65,TIER1
+HLT013_000167,AMR,Female,28,COHORT_B,GRCh38,WES,43.8,91.36,TIER1
+HLT013_000168,AMR,Female,70,COHORT_C,GRCh38,WES,52.2,94.79,TIER1
+HLT013_000169,EUR,Female,30,COHORT_A,GRCh38,WGS,42.2,97.12,TIER2
+HLT013_000170,SAS,Male,73,COHORT_B,GRCh38,WGS,50.3,91.12,TIER1
+HLT013_000171,EUR,Male,51,COHORT_B,GRCh38,WGS,27.5,96.02,TIER1
+HLT013_000172,AFR,Female,46,COHORT_A,GRCh38,WGS,46.9,91.28,TIER2
+HLT013_000173,EUR,Female,73,COHORT_A,GRCh38,WGS,47.2,93.29,TIER2
+HLT013_000174,SAS,Male,29,COHORT_B,GRCh38,WGS,59.5,97.34,TIER1
+HLT013_000175,EUR,Female,59,COHORT_A,GRCh38,WES,34.7,89.2,TIER3
+HLT013_000176,EUR,Female,65,COHORT_B,GRCh38,WGS,47.2,98.41,TIER1
+HLT013_000177,AFR,Male,36,COHORT_C,GRCh38,WGS,28.9,92.88,TIER2
+HLT013_000178,SAS,Female,66,COHORT_A,GRCh38,WGS,36.4,92.78,TIER3
+HLT013_000179,AMR,Female,54,COHORT_C,GRCh38,WGS,57.3,94.35,TIER1
+HLT013_000180,EAS,Male,51,COHORT_B,GRCh38,WGS,42.7,97.57,TIER2
+HLT013_000181,AMR,Male,19,COHORT_C,GRCh38,WES,51.6,90.55,TIER3
+HLT013_000182,AMR,Male,77,COHORT_A,GRCh38,WES,28.5,92.09,TIER3
+HLT013_000183,AFR,Female,50,COHORT_C,GRCh38,WGS,43.6,94.4,TIER1
+HLT013_000184,EUR,Female,60,COHORT_C,GRCh38,WES,46.8,91.37,TIER1
+HLT013_000185,EAS,Female,42,COHORT_A,GRCh38,WGS,37.9,89.56,TIER1
+HLT013_000186,EAS,Female,84,COHORT_C,GRCh38,WGS,44.2,97.87,TIER1
+HLT013_000187,EUR,Male,64,COHORT_C,GRCh38,WES,36.3,92.98,TIER2
+HLT013_000188,EUR,Female,58,COHORT_C,GRCh38,WES,38.6,89.26,TIER2
+HLT013_000189,EAS,Male,24,COHORT_A,GRCh38,WGS,37.5,96.72,TIER3
+HLT013_000190,EUR,Female,62,COHORT_A,GRCh38,WGS,42.8,89.12,TIER2
+HLT013_000191,SAS,Male,33,COHORT_A,GRCh38,WES,41.9,92.43,TIER3
+HLT013_000192,EUR,Female,20,COHORT_C,GRCh38,WES,46.2,95.31,TIER2
+HLT013_000193,EUR,Male,42,COHORT_A,GRCh38,WGS,52.6,91.0,TIER3
+HLT013_000194,AMR,Female,78,COHORT_B,GRCh38,WGS,59.4,95.19,TIER1
+HLT013_000195,EUR,Female,32,COHORT_A,GRCh38,WGS,42.0,89.33,TIER3
+HLT013_000196,EUR,Female,47,COHORT_C,GRCh38,WGS,33.6,89.39,TIER2
+HLT013_000197,AFR,Male,59,COHORT_B,GRCh38,WGS,46.4,90.46,TIER3
+HLT013_000198,AMR,Male,65,COHORT_B,GRCh38,WGS,33.1,89.65,TIER1
+HLT013_000199,EUR,Female,51,COHORT_A,GRCh38,WES,36.0,88.76,TIER1
+HLT013_000200,EUR,Male,63,COHORT_C,GRCh38,WES,58.0,91.41,TIER2
+HLT013_000201,EAS,Male,80,COHORT_B,GRCh38,WES,45.1,95.92,TIER2
+HLT013_000202,SAS,Female,61,COHORT_B,GRCh38,WES,36.0,88.75,TIER1
+HLT013_000203,AFR,Female,72,COHORT_A,GRCh38,WES,60.0,97.1,TIER1
+HLT013_000204,EUR,Male,65,COHORT_B,GRCh38,WGS,54.6,96.61,TIER2
+HLT013_000205,EUR,Female,51,COHORT_B,GRCh38,WGS,35.2,92.22,TIER3
+HLT013_000206,EUR,Female,22,COHORT_C,GRCh38,WES,49.6,93.39,TIER1
+HLT013_000207,EUR,Female,42,COHORT_C,GRCh38,WES,33.0,90.66,TIER2
+HLT013_000208,EAS,Female,55,COHORT_C,GRCh38,WGS,39.6,88.96,TIER2
+HLT013_000209,EUR,Male,36,COHORT_A,GRCh38,WES,53.3,97.89,TIER1
+HLT013_000210,AFR,Male,83,COHORT_A,GRCh38,WGS,33.2,93.86,TIER1
+HLT013_000211,EAS,Male,53,COHORT_B,GRCh38,WGS,52.2,95.08,TIER3
+HLT013_000212,AFR,Male,65,COHORT_C,GRCh38,WGS,34.7,89.39,TIER3
+HLT013_000213,EUR,Female,80,COHORT_A,GRCh38,WGS,25.5,94.49,TIER3
+HLT013_000214,AMR,Male,66,COHORT_B,GRCh38,WGS,57.3,94.97,TIER1
+HLT013_000215,EAS,Male,23,COHORT_C,GRCh38,WGS,30.4,97.29,TIER1
+HLT013_000216,EAS,Male,44,COHORT_B,GRCh38,WGS,56.5,95.12,TIER1
+HLT013_000217,EUR,Female,28,COHORT_A,GRCh38,WGS,48.9,98.65,TIER3
+HLT013_000218,EUR,Female,68,COHORT_A,GRCh38,WGS,54.8,89.42,TIER2
+HLT013_000219,SAS,Female,73,COHORT_B,GRCh38,WES,53.7,97.37,TIER1
+HLT013_000220,EUR,Female,71,COHORT_A,GRCh38,WES,39.5,94.74,TIER3
+HLT013_000221,EUR,Male,55,COHORT_C,GRCh38,WGS,31.5,94.19,TIER1
+HLT013_000222,AFR,Female,36,COHORT_B,GRCh38,WES,54.7,90.21,TIER3
+HLT013_000223,EAS,Female,85,COHORT_C,GRCh38,WGS,40.0,88.04,TIER2
+HLT013_000224,SAS,Male,39,COHORT_A,GRCh38,WGS,29.6,90.45,TIER2
+HLT013_000225,EUR,Female,37,COHORT_C,GRCh38,WES,48.2,89.76,TIER1
+HLT013_000226,SAS,Male,60,COHORT_C,GRCh38,WGS,25.1,89.35,TIER3
+HLT013_000227,EUR,Male,59,COHORT_A,GRCh38,WES,32.7,89.12,TIER1
+HLT013_000228,AFR,Male,54,COHORT_C,GRCh38,WES,40.9,95.05,TIER1
+HLT013_000229,EAS,Female,65,COHORT_C,GRCh38,WES,36.4,99.0,TIER3
+HLT013_000230,EUR,Female,23,COHORT_A,GRCh38,WGS,48.8,92.56,TIER2
+HLT013_000231,EUR,Male,44,COHORT_A,GRCh38,WGS,41.6,92.39,TIER2
+HLT013_000232,AFR,Female,73,COHORT_B,GRCh38,WGS,29.4,96.88,TIER2
+HLT013_000233,SAS,Female,77,COHORT_A,GRCh38,WES,40.1,93.9,TIER2
+HLT013_000234,AFR,Male,87,COHORT_B,GRCh38,WGS,31.0,97.25,TIER1
+HLT013_000235,SAS,Female,18,COHORT_B,GRCh38,WES,26.9,92.16,TIER2
+HLT013_000236,AMR,Female,22,COHORT_A,GRCh38,WGS,28.2,98.79,TIER2
+HLT013_000237,AFR,Female,34,COHORT_A,GRCh38,WGS,43.1,97.92,TIER1
+HLT013_000238,EAS,Female,80,COHORT_C,GRCh38,WES,27.8,90.1,TIER1
+HLT013_000239,EUR,Male,33,COHORT_C,GRCh38,WES,41.8,90.77,TIER3
+HLT013_000240,EUR,Female,78,COHORT_A,GRCh38,WGS,28.2,95.58,TIER3
+HLT013_000241,AMR,Female,32,COHORT_A,GRCh38,WGS,44.5,89.01,TIER3
+HLT013_000242,EAS,Male,46,COHORT_B,GRCh38,WGS,32.3,96.5,TIER1
+HLT013_000243,EUR,Male,64,COHORT_B,GRCh38,WES,37.8,94.43,TIER2
+HLT013_000244,AFR,Male,68,COHORT_B,GRCh38,WGS,26.0,88.68,TIER1
+HLT013_000245,EAS,Male,88,COHORT_A,GRCh38,WGS,32.3,91.02,TIER2
+HLT013_000246,AMR,Male,23,COHORT_A,GRCh38,WES,36.6,92.32,TIER2
+HLT013_000247,EAS,Male,50,COHORT_B,GRCh38,WES,48.1,93.77,TIER3
+HLT013_000248,AFR,Male,31,COHORT_B,GRCh38,WES,55.6,93.48,TIER2
+HLT013_000249,EUR,Male,42,COHORT_A,GRCh38,WGS,46.0,98.37,TIER1
+HLT013_000250,AFR,Female,82,COHORT_A,GRCh38,WGS,32.8,98.56,TIER2
+HLT013_000251,EAS,Male,56,COHORT_A,GRCh38,WES,44.1,92.37,TIER3
+HLT013_000252,AMR,Male,56,COHORT_C,GRCh38,WGS,44.6,91.79,TIER2
+HLT013_000253,AFR,Female,69,COHORT_B,GRCh38,WGS,42.9,95.06,TIER2
+HLT013_000254,EUR,Male,28,COHORT_B,GRCh38,WGS,50.8,98.22,TIER2
+HLT013_000255,EUR,Male,27,COHORT_A,GRCh38,WES,29.0,94.09,TIER2
+HLT013_000256,EAS,Male,77,COHORT_A,GRCh38,WES,50.2,89.19,TIER2
+HLT013_000257,AMR,Male,28,COHORT_A,GRCh38,WES,52.4,97.72,TIER2
+HLT013_000258,EUR,Female,43,COHORT_A,GRCh38,WGS,56.0,95.33,TIER2
+HLT013_000259,EUR,Male,39,COHORT_C,GRCh38,WES,35.8,93.21,TIER3
+HLT013_000260,AFR,Male,80,COHORT_C,GRCh38,WES,28.0,93.97,TIER3
+HLT013_000261,EUR,Male,62,COHORT_C,GRCh38,WGS,45.2,89.72,TIER3
+HLT013_000262,AMR,Male,86,COHORT_A,GRCh38,WGS,33.8,94.21,TIER3
+HLT013_000263,EUR,Female,64,COHORT_B,GRCh38,WES,45.1,95.21,TIER1
+HLT013_000264,EUR,Male,25,COHORT_B,GRCh38,WGS,37.2,94.71,TIER3
+HLT013_000265,SAS,Male,64,COHORT_C,GRCh38,WES,51.6,91.23,TIER3
+HLT013_000266,EUR,Female,54,COHORT_B,GRCh38,WES,32.7,95.94,TIER1
+HLT013_000267,EUR,Female,25,COHORT_A,GRCh38,WGS,45.7,88.28,TIER1
+HLT013_000268,EUR,Male,41,COHORT_B,GRCh38,WGS,32.0,88.4,TIER1
+HLT013_000269,EUR,Male,74,COHORT_C,GRCh38,WGS,29.9,96.26,TIER2
+HLT013_000270,EUR,Female,56,COHORT_B,GRCh38,WGS,30.6,90.5,TIER3
+HLT013_000271,EUR,Female,41,COHORT_C,GRCh38,WGS,27.2,91.1,TIER1
+HLT013_000272,EUR,Female,30,COHORT_B,GRCh38,WES,49.7,90.32,TIER1
+HLT013_000273,EUR,Male,81,COHORT_B,GRCh38,WGS,31.7,88.35,TIER1
+HLT013_000274,AFR,Male,58,COHORT_B,GRCh38,WGS,50.8,92.92,TIER1
+HLT013_000275,EAS,Male,36,COHORT_B,GRCh38,WGS,37.8,90.2,TIER1
+HLT013_000276,EUR,Female,29,COHORT_B,GRCh38,WGS,42.3,95.07,TIER2
+HLT013_000277,EUR,Male,51,COHORT_B,GRCh38,WES,39.4,93.49,TIER3
+HLT013_000278,AFR,Female,75,COHORT_B,GRCh38,WES,58.4,89.2,TIER3
+HLT013_000279,AMR,Female,44,COHORT_C,GRCh38,WES,32.4,95.09,TIER3
+HLT013_000280,AMR,Male,86,COHORT_A,GRCh38,WES,37.5,96.16,TIER1
+HLT013_000281,EUR,Female,87,COHORT_B,GRCh38,WGS,35.8,94.63,TIER1
+HLT013_000282,EUR,Male,23,COHORT_A,GRCh38,WGS,57.4,95.99,TIER3
+HLT013_000283,EUR,Female,88,COHORT_B,GRCh38,WGS,48.1,90.19,TIER3
+HLT013_000284,EUR,Female,18,COHORT_B,GRCh38,WES,39.1,93.63,TIER2
+HLT013_000285,AFR,Female,46,COHORT_B,GRCh38,WGS,32.5,94.73,TIER1
+HLT013_000286,AFR,Male,49,COHORT_C,GRCh38,WGS,57.8,92.95,TIER3
+HLT013_000287,EUR,Female,77,COHORT_A,GRCh38,WGS,48.0,94.67,TIER1
+HLT013_000288,EUR,Male,72,COHORT_B,GRCh38,WGS,50.0,96.68,TIER3
+HLT013_000289,AFR,Female,68,COHORT_B,GRCh38,WES,53.5,97.28,TIER1
+HLT013_000290,EUR,Female,40,COHORT_B,GRCh38,WES,37.8,92.17,TIER1
+HLT013_000291,AMR,Female,65,COHORT_A,GRCh38,WES,43.9,97.03,TIER2
+HLT013_000292,EUR,Male,25,COHORT_C,GRCh38,WES,50.3,93.21,TIER3
+HLT013_000293,SAS,Male,71,COHORT_C,GRCh38,WGS,27.2,95.04,TIER1
+HLT013_000294,EUR,Male,40,COHORT_B,GRCh38,WGS,32.8,89.74,TIER1
+HLT013_000295,AMR,Female,38,COHORT_C,GRCh38,WES,38.1,88.26,TIER3
+HLT013_000296,AMR,Female,46,COHORT_C,GRCh38,WES,47.8,93.0,TIER3
+HLT013_000297,SAS,Male,51,COHORT_C,GRCh38,WGS,33.7,94.54,TIER2
+HLT013_000298,AMR,Female,64,COHORT_A,GRCh38,WGS,59.5,90.64,TIER3
+HLT013_000299,EAS,Male,29,COHORT_B,GRCh38,WES,33.0,96.66,TIER3
+HLT013_000300,EAS,Male,27,COHORT_C,GRCh38,WES,27.5,93.39,TIER3
+HLT013_000301,EAS,Male,59,COHORT_C,GRCh38,WGS,42.5,90.39,TIER2
+HLT013_000302,EUR,Male,44,COHORT_A,GRCh38,WES,35.7,92.91,TIER3
+HLT013_000303,AFR,Male,65,COHORT_A,GRCh38,WGS,32.4,92.33,TIER2
+HLT013_000304,AFR,Male,36,COHORT_B,GRCh38,WGS,34.1,91.96,TIER1
+HLT013_000305,AMR,Male,26,COHORT_A,GRCh38,WES,42.2,98.27,TIER2
+HLT013_000306,AFR,Female,35,COHORT_A,GRCh38,WES,28.2,88.69,TIER2
+HLT013_000307,EUR,Male,45,COHORT_B,GRCh38,WES,57.3,98.12,TIER3
+HLT013_000308,EAS,Female,45,COHORT_C,GRCh38,WGS,49.0,94.99,TIER1
+HLT013_000309,EUR,Male,19,COHORT_B,GRCh38,WES,54.6,95.78,TIER2
+HLT013_000310,EUR,Female,32,COHORT_C,GRCh38,WGS,52.3,88.8,TIER2
+HLT013_000311,AFR,Male,29,COHORT_A,GRCh38,WGS,52.3,93.89,TIER1
+HLT013_000312,AFR,Female,28,COHORT_A,GRCh38,WGS,54.5,92.27,TIER3
+HLT013_000313,EUR,Female,71,COHORT_C,GRCh38,WGS,52.9,93.58,TIER3
+HLT013_000314,EUR,Female,71,COHORT_C,GRCh38,WES,52.9,88.14,TIER3
+HLT013_000315,EUR,Male,73,COHORT_A,GRCh38,WES,57.8,91.97,TIER2
+HLT013_000316,EUR,Male,83,COHORT_A,GRCh38,WES,27.3,95.03,TIER3
+HLT013_000317,EUR,Female,29,COHORT_B,GRCh38,WGS,33.3,93.24,TIER3
+HLT013_000318,EAS,Female,27,COHORT_B,GRCh38,WGS,25.8,97.17,TIER1
+HLT013_000319,EUR,Female,33,COHORT_B,GRCh38,WGS,30.9,90.08,TIER3
+HLT013_000320,SAS,Male,54,COHORT_A,GRCh38,WGS,25.5,92.06,TIER1
+HLT013_000321,AMR,Male,67,COHORT_C,GRCh38,WGS,37.6,97.8,TIER2
+HLT013_000322,AFR,Male,31,COHORT_C,GRCh38,WGS,26.1,95.95,TIER1
+HLT013_000323,EUR,Male,32,COHORT_A,GRCh38,WGS,39.2,95.56,TIER1
+HLT013_000324,AFR,Female,52,COHORT_B,GRCh38,WGS,49.8,96.37,TIER2
+HLT013_000325,AMR,Male,60,COHORT_A,GRCh38,WES,57.5,89.54,TIER1
+HLT013_000326,EAS,Male,37,COHORT_A,GRCh38,WGS,51.1,89.41,TIER3
+HLT013_000327,AMR,Female,39,COHORT_B,GRCh38,WES,38.1,93.99,TIER1
+HLT013_000328,AFR,Male,85,COHORT_C,GRCh38,WGS,33.6,91.54,TIER1
+HLT013_000329,EAS,Male,73,COHORT_C,GRCh38,WES,53.1,89.54,TIER2
+HLT013_000330,EUR,Male,56,COHORT_C,GRCh38,WGS,41.5,92.91,TIER1
+HLT013_000331,EAS,Female,53,COHORT_B,GRCh38,WGS,53.8,89.66,TIER3
+HLT013_000332,EUR,Male,20,COHORT_B,GRCh38,WGS,41.2,98.24,TIER2
+HLT013_000333,EAS,Female,36,COHORT_A,GRCh38,WES,54.1,90.14,TIER1
+HLT013_000334,AMR,Male,58,COHORT_B,GRCh38,WGS,51.3,97.98,TIER3
+HLT013_000335,EUR,Male,55,COHORT_B,GRCh38,WES,43.9,96.51,TIER3
+HLT013_000336,EAS,Male,35,COHORT_A,GRCh38,WGS,43.8,95.37,TIER1
+HLT013_000337,EUR,Male,59,COHORT_C,GRCh38,WGS,54.3,94.8,TIER1
+HLT013_000338,EAS,Male,86,COHORT_B,GRCh38,WES,43.0,88.4,TIER2
+HLT013_000339,EUR,Female,77,COHORT_C,GRCh38,WES,54.4,93.51,TIER2
+HLT013_000340,SAS,Male,32,COHORT_C,GRCh38,WGS,45.0,97.65,TIER2
+HLT013_000341,EUR,Male,76,COHORT_A,GRCh38,WES,25.0,98.37,TIER1
+HLT013_000342,SAS,Female,69,COHORT_C,GRCh38,WGS,43.8,96.54,TIER2
+HLT013_000343,AMR,Female,18,COHORT_C,GRCh38,WGS,49.2,93.36,TIER3
+HLT013_000344,AFR,Female,24,COHORT_A,GRCh38,WGS,58.0,91.08,TIER1
+HLT013_000345,EAS,Female,34,COHORT_A,GRCh38,WGS,52.4,98.11,TIER1
+HLT013_000346,EAS,Male,50,COHORT_C,GRCh38,WGS,36.1,97.57,TIER2
+HLT013_000347,SAS,Female,81,COHORT_C,GRCh38,WES,56.7,91.7,TIER2
+HLT013_000348,EUR,Female,57,COHORT_B,GRCh38,WES,27.9,96.64,TIER3
+HLT013_000349,AFR,Male,80,COHORT_A,GRCh38,WES,43.9,95.47,TIER2
+HLT013_000350,EUR,Male,64,COHORT_B,GRCh38,WGS,44.7,92.37,TIER3
+HLT013_000351,EAS,Male,18,COHORT_B,GRCh38,WES,52.1,92.29,TIER2
+HLT013_000352,EUR,Female,23,COHORT_A,GRCh38,WES,25.5,95.28,TIER1
+HLT013_000353,AFR,Male,78,COHORT_C,GRCh38,WES,51.5,94.24,TIER1
+HLT013_000354,AFR,Male,33,COHORT_A,GRCh38,WES,39.5,92.86,TIER2
+HLT013_000355,AFR,Female,89,COHORT_C,GRCh38,WES,57.9,92.01,TIER1
+HLT013_000356,AFR,Female,61,COHORT_C,GRCh38,WGS,52.1,90.01,TIER1
+HLT013_000357,EAS,Female,30,COHORT_C,GRCh38,WGS,30.2,89.11,TIER3
+HLT013_000358,EAS,Male,46,COHORT_B,GRCh38,WES,27.6,89.57,TIER2
+HLT013_000359,AFR,Male,89,COHORT_C,GRCh38,WES,50.7,93.1,TIER3
+HLT013_000360,AFR,Female,79,COHORT_C,GRCh38,WGS,26.3,98.23,TIER3
+HLT013_000361,SAS,Female,69,COHORT_A,GRCh38,WES,31.4,97.81,TIER1
+HLT013_000362,EUR,Female,40,COHORT_B,GRCh38,WES,29.6,95.85,TIER2
+HLT013_000363,EUR,Male,76,COHORT_B,GRCh38,WES,51.9,92.58,TIER2
+HLT013_000364,EUR,Female,39,COHORT_C,GRCh38,WGS,39.1,88.72,TIER2
+HLT013_000365,EAS,Male,25,COHORT_B,GRCh38,WES,43.8,90.5,TIER1
+HLT013_000366,AFR,Male,18,COHORT_A,GRCh38,WGS,50.3,97.72,TIER3
+HLT013_000367,EAS,Female,77,COHORT_C,GRCh38,WGS,37.9,91.45,TIER2
+HLT013_000368,EAS,Male,53,COHORT_A,GRCh38,WES,37.2,92.9,TIER2
+HLT013_000369,EUR,Male,70,COHORT_A,GRCh38,WGS,36.5,91.24,TIER2
+HLT013_000370,AMR,Male,36,COHORT_B,GRCh38,WGS,26.7,89.35,TIER2
+HLT013_000371,EAS,Female,72,COHORT_A,GRCh38,WGS,34.3,91.78,TIER2
+HLT013_000372,EUR,Female,48,COHORT_B,GRCh38,WGS,36.9,93.3,TIER2
+HLT013_000373,EUR,Female,65,COHORT_C,GRCh38,WES,39.6,88.28,TIER2
+HLT013_000374,EUR,Male,63,COHORT_C,GRCh38,WGS,56.4,98.31,TIER3
+HLT013_000375,EUR,Female,28,COHORT_C,GRCh38,WES,31.0,90.45,TIER1
+HLT013_000376,EUR,Male,27,COHORT_A,GRCh38,WGS,28.6,98.27,TIER1
+HLT013_000377,SAS,Female,68,COHORT_B,GRCh38,WGS,38.2,95.13,TIER2
+HLT013_000378,AFR,Male,63,COHORT_C,GRCh38,WES,37.7,98.14,TIER3
+HLT013_000379,EUR,Female,59,COHORT_C,GRCh38,WES,33.3,94.08,TIER2
+HLT013_000380,EAS,Female,47,COHORT_A,GRCh38,WGS,45.8,88.9,TIER1
+HLT013_000381,AFR,Male,18,COHORT_B,GRCh38,WGS,50.0,97.83,TIER1
+HLT013_000382,SAS,Male,72,COHORT_A,GRCh38,WES,41.8,97.59,TIER3
+HLT013_000383,EAS,Male,81,COHORT_C,GRCh38,WES,43.5,91.84,TIER3
+HLT013_000384,AFR,Male,63,COHORT_A,GRCh38,WGS,46.4,90.07,TIER3
+HLT013_000385,EUR,Male,77,COHORT_B,GRCh38,WES,55.7,88.5,TIER2
+HLT013_000386,SAS,Female,75,COHORT_A,GRCh38,WGS,56.3,88.01,TIER3
+HLT013_000387,EAS,Male,87,COHORT_A,GRCh38,WES,28.4,96.02,TIER2
+HLT013_000388,SAS,Male,57,COHORT_A,GRCh38,WES,58.8,92.64,TIER3
+HLT013_000389,EUR,Female,77,COHORT_A,GRCh38,WES,25.5,92.8,TIER3
+HLT013_000390,AMR,Male,31,COHORT_A,GRCh38,WES,52.2,92.49,TIER2
+HLT013_000391,EAS,Male,37,COHORT_C,GRCh38,WGS,27.7,94.93,TIER1
+HLT013_000392,EUR,Male,54,COHORT_B,GRCh38,WES,46.8,94.45,TIER1
+HLT013_000393,AFR,Male,18,COHORT_B,GRCh38,WES,38.5,97.81,TIER3
+HLT013_000394,EAS,Male,21,COHORT_C,GRCh38,WES,58.6,96.27,TIER3
+HLT013_000395,EUR,Male,80,COHORT_C,GRCh38,WGS,48.0,96.78,TIER3
+HLT013_000396,AFR,Female,73,COHORT_B,GRCh38,WES,38.4,93.48,TIER2
+HLT013_000397,AMR,Female,46,COHORT_A,GRCh38,WES,55.7,94.64,TIER2
+HLT013_000398,EUR,Female,64,COHORT_C,GRCh38,WGS,38.8,97.8,TIER1
+HLT013_000399,AFR,Female,87,COHORT_A,GRCh38,WES,52.9,91.78,TIER3
+HLT013_000400,AFR,Male,84,COHORT_C,GRCh38,WES,46.1,88.18,TIER3
+HLT013_000401,EUR,Male,73,COHORT_B,GRCh38,WGS,53.2,95.59,TIER2
+HLT013_000402,AMR,Female,71,COHORT_C,GRCh38,WES,42.8,90.44,TIER2
+HLT013_000403,EAS,Female,49,COHORT_B,GRCh38,WES,35.9,90.84,TIER1
+HLT013_000404,EUR,Male,82,COHORT_C,GRCh38,WGS,38.4,93.44,TIER3
+HLT013_000405,SAS,Male,80,COHORT_B,GRCh38,WES,50.0,90.99,TIER1
+HLT013_000406,AMR,Female,68,COHORT_A,GRCh38,WES,43.0,89.4,TIER3
+HLT013_000407,EUR,Male,51,COHORT_C,GRCh38,WGS,49.3,90.47,TIER2
+HLT013_000408,AMR,Female,83,COHORT_A,GRCh38,WES,35.6,90.15,TIER2
+HLT013_000409,EUR,Male,69,COHORT_B,GRCh38,WGS,25.3,96.67,TIER3
+HLT013_000410,SAS,Male,78,COHORT_A,GRCh38,WGS,51.7,91.78,TIER2
+HLT013_000411,EAS,Female,47,COHORT_C,GRCh38,WGS,42.8,92.16,TIER2
+HLT013_000412,EAS,Female,34,COHORT_C,GRCh38,WGS,45.9,92.2,TIER2
+HLT013_000413,EUR,Female,53,COHORT_C,GRCh38,WGS,45.7,89.2,TIER3
+HLT013_000414,AMR,Female,27,COHORT_A,GRCh38,WES,45.7,91.15,TIER3
+HLT013_000415,EUR,Male,32,COHORT_C,GRCh38,WES,44.9,88.89,TIER3
+HLT013_000416,EUR,Female,38,COHORT_C,GRCh38,WGS,29.6,89.92,TIER2
+HLT013_000417,EUR,Female,66,COHORT_B,GRCh38,WGS,53.4,95.38,TIER3
+HLT013_000418,EAS,Female,63,COHORT_B,GRCh38,WGS,57.3,98.91,TIER2
+HLT013_000419,EUR,Female,23,COHORT_B,GRCh38,WGS,36.6,96.49,TIER2
+HLT013_000420,AMR,Male,61,COHORT_C,GRCh38,WGS,54.1,97.57,TIER1
+HLT013_000421,EAS,Male,31,COHORT_A,GRCh38,WES,52.0,98.57,TIER1
+HLT013_000422,EUR,Male,30,COHORT_B,GRCh38,WGS,52.5,88.09,TIER2
+HLT013_000423,EUR,Female,44,COHORT_A,GRCh38,WGS,33.3,98.66,TIER1
+HLT013_000424,EUR,Male,64,COHORT_A,GRCh38,WGS,32.6,90.75,TIER2
+HLT013_000425,EAS,Male,55,COHORT_C,GRCh38,WES,32.4,97.22,TIER1
+HLT013_000426,AMR,Male,89,COHORT_C,GRCh38,WES,29.4,93.12,TIER2
+HLT013_000427,EUR,Male,27,COHORT_B,GRCh38,WES,51.5,90.75,TIER3
+HLT013_000428,AMR,Male,87,COHORT_C,GRCh38,WGS,35.9,93.83,TIER3
+HLT013_000429,EUR,Male,18,COHORT_C,GRCh38,WES,46.0,90.33,TIER2
+HLT013_000430,AMR,Male,35,COHORT_C,GRCh38,WGS,33.2,94.86,TIER3
+HLT013_000431,SAS,Female,51,COHORT_C,GRCh38,WGS,29.2,96.57,TIER1
+HLT013_000432,EAS,Male,40,COHORT_A,GRCh38,WES,33.8,98.11,TIER3
+HLT013_000433,EAS,Female,29,COHORT_B,GRCh38,WGS,43.4,91.53,TIER3
+HLT013_000434,AMR,Female,84,COHORT_B,GRCh38,WES,38.5,94.47,TIER2
+HLT013_000435,EUR,Female,62,COHORT_B,GRCh38,WGS,47.9,97.14,TIER1
+HLT013_000436,EUR,Female,42,COHORT_A,GRCh38,WGS,28.5,94.03,TIER2
+HLT013_000437,EUR,Female,72,COHORT_A,GRCh38,WGS,34.6,97.15,TIER3
+HLT013_000438,AFR,Male,29,COHORT_C,GRCh38,WES,27.5,95.28,TIER3
+HLT013_000439,EAS,Female,67,COHORT_C,GRCh38,WGS,50.1,95.94,TIER3
+HLT013_000440,EAS,Male,45,COHORT_B,GRCh38,WGS,48.2,89.12,TIER3
+HLT013_000441,AMR,Male,84,COHORT_B,GRCh38,WES,40.5,93.34,TIER1
+HLT013_000442,EUR,Male,29,COHORT_A,GRCh38,WGS,58.4,92.19,TIER1
+HLT013_000443,EAS,Male,70,COHORT_C,GRCh38,WGS,44.9,94.44,TIER1
+HLT013_000444,EUR,Female,61,COHORT_C,GRCh38,WGS,26.4,95.85,TIER1
+HLT013_000445,EUR,Male,45,COHORT_B,GRCh38,WES,29.0,93.32,TIER3
+HLT013_000446,EAS,Male,89,COHORT_C,GRCh38,WES,38.3,91.05,TIER1
+HLT013_000447,SAS,Male,89,COHORT_B,GRCh38,WGS,35.1,98.04,TIER3
+HLT013_000448,EAS,Male,52,COHORT_A,GRCh38,WES,43.7,90.6,TIER2
+HLT013_000449,EUR,Female,34,COHORT_A,GRCh38,WGS,32.9,97.25,TIER3
+HLT013_000450,EAS,Female,68,COHORT_A,GRCh38,WGS,56.6,94.58,TIER2
+HLT013_000451,EUR,Male,25,COHORT_B,GRCh38,WES,35.3,92.8,TIER2
+HLT013_000452,AMR,Female,53,COHORT_B,GRCh38,WES,32.6,93.97,TIER1
+HLT013_000453,EAS,Male,38,COHORT_B,GRCh38,WES,59.1,89.45,TIER3
+HLT013_000454,EUR,Male,20,COHORT_B,GRCh38,WGS,35.4,96.12,TIER1
+HLT013_000455,EUR,Female,63,COHORT_A,GRCh38,WES,57.9,98.96,TIER3
+HLT013_000456,EUR,Female,53,COHORT_A,GRCh38,WGS,41.3,96.54,TIER2
+HLT013_000457,SAS,Female,52,COHORT_B,GRCh38,WGS,45.3,90.28,TIER2
+HLT013_000458,AFR,Male,46,COHORT_C,GRCh38,WES,38.7,94.71,TIER3
+HLT013_000459,EAS,Male,83,COHORT_C,GRCh38,WES,30.0,89.48,TIER2
+HLT013_000460,EAS,Male,27,COHORT_C,GRCh38,WES,41.3,94.01,TIER1
+HLT013_000461,AFR,Female,84,COHORT_C,GRCh38,WGS,37.8,91.43,TIER2
+HLT013_000462,EUR,Male,70,COHORT_A,GRCh38,WGS,44.6,93.74,TIER1
+HLT013_000463,SAS,Male,22,COHORT_C,GRCh38,WGS,48.0,93.41,TIER1
+HLT013_000464,EUR,Female,18,COHORT_C,GRCh38,WES,59.7,96.46,TIER1
+HLT013_000465,AFR,Female,69,COHORT_C,GRCh38,WES,52.7,92.8,TIER3
+HLT013_000466,EAS,Male,29,COHORT_C,GRCh38,WGS,40.8,96.68,TIER3
+HLT013_000467,EAS,Female,62,COHORT_A,GRCh38,WGS,49.6,97.03,TIER1
+HLT013_000468,SAS,Female,37,COHORT_C,GRCh38,WES,49.8,89.91,TIER3
+HLT013_000469,EUR,Male,79,COHORT_B,GRCh38,WGS,29.2,88.44,TIER2
+HLT013_000470,AFR,Female,79,COHORT_A,GRCh38,WES,38.1,94.9,TIER2
+HLT013_000471,AFR,Male,71,COHORT_B,GRCh38,WES,36.6,89.12,TIER2
+HLT013_000472,AFR,Male,84,COHORT_A,GRCh38,WGS,35.2,89.57,TIER3
+HLT013_000473,EUR,Male,60,COHORT_A,GRCh38,WES,41.6,93.69,TIER3
+HLT013_000474,EUR,Female,24,COHORT_C,GRCh38,WGS,47.3,95.95,TIER3
+HLT013_000475,EUR,Female,59,COHORT_B,GRCh38,WES,27.6,92.41,TIER2
+HLT013_000476,EUR,Female,76,COHORT_C,GRCh38,WGS,53.3,94.59,TIER2
+HLT013_000477,AFR,Male,21,COHORT_B,GRCh38,WES,52.7,96.97,TIER3
+HLT013_000478,EAS,Female,41,COHORT_A,GRCh38,WES,55.2,88.76,TIER1
+HLT013_000479,EAS,Female,49,COHORT_B,GRCh38,WGS,39.4,90.11,TIER1
+HLT013_000480,AFR,Male,87,COHORT_B,GRCh38,WGS,44.2,88.65,TIER2
+HLT013_000481,AFR,Male,40,COHORT_B,GRCh38,WES,55.3,96.8,TIER1
+HLT013_000482,EUR,Male,22,COHORT_C,GRCh38,WES,49.0,98.26,TIER2
+HLT013_000483,AFR,Male,49,COHORT_A,GRCh38,WES,41.6,93.98,TIER2
+HLT013_000484,EUR,Male,74,COHORT_C,GRCh38,WES,33.8,93.15,TIER1
+HLT013_000485,EUR,Female,37,COHORT_B,GRCh38,WGS,47.6,91.57,TIER3
+HLT013_000486,AFR,Female,18,COHORT_A,GRCh38,WES,34.9,89.59,TIER3
+HLT013_000487,AFR,Male,60,COHORT_B,GRCh38,WGS,46.3,91.45,TIER3
+HLT013_000488,EUR,Female,80,COHORT_A,GRCh38,WGS,30.1,94.55,TIER3
+HLT013_000489,AFR,Female,75,COHORT_B,GRCh38,WGS,42.5,97.42,TIER3
+HLT013_000490,AFR,Male,65,COHORT_B,GRCh38,WGS,56.4,92.38,TIER3
+HLT013_000491,EAS,Female,63,COHORT_B,GRCh38,WES,48.5,90.37,TIER1
+HLT013_000492,EAS,Female,31,COHORT_C,GRCh38,WES,54.1,97.93,TIER2
+HLT013_000493,EAS,Male,38,COHORT_C,GRCh38,WGS,29.9,94.58,TIER1
+HLT013_000494,EUR,Male,75,COHORT_B,GRCh38,WGS,56.3,98.71,TIER2
+HLT013_000495,EAS,Male,81,COHORT_B,GRCh38,WGS,39.2,96.26,TIER1
+HLT013_000496,AFR,Male,55,COHORT_B,GRCh38,WES,28.9,96.94,TIER3
+HLT013_000497,AFR,Female,35,COHORT_C,GRCh38,WGS,27.9,93.83,TIER3
+HLT013_000498,EAS,Female,54,COHORT_C,GRCh38,WGS,34.9,94.73,TIER1
+HLT013_000499,EUR,Male,59,COHORT_A,GRCh38,WGS,37.1,98.04,TIER3
+HLT013_000500,AFR,Male,37,COHORT_C,GRCh38,WES,53.2,91.67,TIER2
+HLT013_000501,EAS,Male,74,COHORT_B,GRCh38,WES,36.7,94.74,TIER3
+HLT013_000502,AMR,Male,32,COHORT_C,GRCh38,WES,27.7,89.36,TIER2
+HLT013_000503,SAS,Female,75,COHORT_A,GRCh38,WGS,53.7,88.32,TIER3
+HLT013_000504,AFR,Male,63,COHORT_C,GRCh38,WGS,44.6,92.25,TIER3
+HLT013_000505,AFR,Female,59,COHORT_B,GRCh38,WGS,37.3,98.81,TIER1
+HLT013_000506,EAS,Male,48,COHORT_A,GRCh38,WES,35.0,90.41,TIER1
+HLT013_000507,EUR,Male,48,COHORT_C,GRCh38,WES,51.1,95.25,TIER1
+HLT013_000508,AMR,Female,63,COHORT_C,GRCh38,WGS,44.9,89.05,TIER3
+HLT013_000509,AFR,Male,35,COHORT_B,GRCh38,WGS,54.0,95.31,TIER3
+HLT013_000510,EUR,Male,44,COHORT_A,GRCh38,WES,44.7,89.3,TIER1
+HLT013_000511,EUR,Female,52,COHORT_C,GRCh38,WES,46.1,88.17,TIER1
+HLT013_000512,AMR,Male,49,COHORT_A,GRCh38,WES,35.7,98.15,TIER2
+HLT013_000513,EUR,Female,43,COHORT_B,GRCh38,WES,36.3,95.2,TIER2
+HLT013_000514,EUR,Male,26,COHORT_B,GRCh38,WES,59.5,98.71,TIER2
+HLT013_000515,EUR,Female,63,COHORT_C,GRCh38,WGS,26.3,90.97,TIER1
+HLT013_000516,EUR,Female,82,COHORT_B,GRCh38,WGS,42.5,89.13,TIER2
+HLT013_000517,EUR,Male,21,COHORT_A,GRCh38,WES,48.9,92.59,TIER2
+HLT013_000518,EAS,Female,59,COHORT_B,GRCh38,WGS,59.4,88.0,TIER2
+HLT013_000519,EUR,Female,54,COHORT_B,GRCh38,WGS,34.8,89.25,TIER1
+HLT013_000520,AMR,Male,24,COHORT_C,GRCh38,WGS,51.8,93.5,TIER3
+HLT013_000521,AMR,Female,72,COHORT_A,GRCh38,WGS,27.4,96.15,TIER3
+HLT013_000522,EUR,Female,65,COHORT_C,GRCh38,WES,35.1,94.06,TIER2
+HLT013_000523,EUR,Female,37,COHORT_B,GRCh38,WES,41.5,93.83,TIER1
+HLT013_000524,EAS,Male,40,COHORT_B,GRCh38,WES,34.2,96.59,TIER1
+HLT013_000525,EUR,Female,65,COHORT_B,GRCh38,WES,42.1,97.39,TIER1
+HLT013_000526,EUR,Female,68,COHORT_B,GRCh38,WGS,41.2,90.34,TIER1
+HLT013_000527,SAS,Female,40,COHORT_B,GRCh38,WGS,37.5,98.61,TIER1
+HLT013_000528,SAS,Female,21,COHORT_B,GRCh38,WES,59.7,91.63,TIER1
+HLT013_000529,EAS,Female,47,COHORT_A,GRCh38,WGS,39.6,95.12,TIER1
+HLT013_000530,EUR,Male,76,COHORT_C,GRCh38,WGS,44.3,91.46,TIER1
+HLT013_000531,EAS,Male,82,COHORT_C,GRCh38,WES,28.8,92.62,TIER2
+HLT013_000532,EAS,Male,66,COHORT_C,GRCh38,WES,59.7,91.44,TIER3
+HLT013_000533,EUR,Female,68,COHORT_A,GRCh38,WES,46.1,92.75,TIER1
+HLT013_000534,EAS,Female,38,COHORT_C,GRCh38,WGS,32.4,97.49,TIER1
+HLT013_000535,EUR,Male,54,COHORT_B,GRCh38,WGS,30.8,98.9,TIER1
+HLT013_000536,EUR,Male,32,COHORT_C,GRCh38,WES,27.1,90.66,TIER3
+HLT013_000537,AFR,Male,83,COHORT_C,GRCh38,WGS,44.9,91.57,TIER3
+HLT013_000538,EUR,Female,27,COHORT_B,GRCh38,WGS,40.9,98.9,TIER2
+HLT013_000539,EUR,Male,80,COHORT_B,GRCh38,WES,29.2,96.87,TIER2
+HLT013_000540,AMR,Female,30,COHORT_A,GRCh38,WGS,57.7,94.75,TIER1
+HLT013_000541,SAS,Female,23,COHORT_A,GRCh38,WGS,44.3,97.22,TIER3
+HLT013_000542,AFR,Male,22,COHORT_B,GRCh38,WGS,37.8,88.25,TIER3
+HLT013_000543,AMR,Male,38,COHORT_B,GRCh38,WGS,26.0,97.69,TIER3
+HLT013_000544,SAS,Male,69,COHORT_B,GRCh38,WES,51.8,91.21,TIER2
+HLT013_000545,EUR,Female,69,COHORT_B,GRCh38,WGS,44.0,90.29,TIER2
+HLT013_000546,AFR,Female,39,COHORT_C,GRCh38,WGS,38.3,95.32,TIER2
+HLT013_000547,EUR,Male,77,COHORT_C,GRCh38,WES,50.7,91.73,TIER3
+HLT013_000548,EUR,Male,71,COHORT_C,GRCh38,WES,49.4,88.63,TIER3
+HLT013_000549,EAS,Male,64,COHORT_B,GRCh38,WES,33.9,93.6,TIER3
+HLT013_000550,AFR,Female,37,COHORT_C,GRCh38,WGS,30.0,95.78,TIER3
+HLT013_000551,AFR,Female,42,COHORT_A,GRCh38,WGS,39.6,95.75,TIER3
+HLT013_000552,EUR,Male,76,COHORT_C,GRCh38,WES,28.8,90.26,TIER2
+HLT013_000553,EUR,Female,30,COHORT_A,GRCh38,WGS,46.3,91.08,TIER2
+HLT013_000554,AMR,Male,50,COHORT_A,GRCh38,WGS,43.1,98.94,TIER2
+HLT013_000555,EUR,Female,77,COHORT_A,GRCh38,WGS,42.6,91.9,TIER1
+HLT013_000556,EUR,Male,78,COHORT_B,GRCh38,WES,58.9,91.32,TIER3
+HLT013_000557,EUR,Female,57,COHORT_C,GRCh38,WGS,53.0,96.43,TIER3
+HLT013_000558,AFR,Male,75,COHORT_B,GRCh38,WES,36.9,93.35,TIER2
+HLT013_000559,AFR,Female,46,COHORT_C,GRCh38,WES,44.1,98.22,TIER2
+HLT013_000560,AFR,Female,53,COHORT_C,GRCh38,WGS,41.6,96.76,TIER1
+HLT013_000561,EUR,Female,67,COHORT_B,GRCh38,WGS,33.2,95.55,TIER1
+HLT013_000562,EUR,Male,32,COHORT_C,GRCh38,WGS,40.2,98.73,TIER1
+HLT013_000563,AMR,Female,47,COHORT_A,GRCh38,WGS,26.4,98.52,TIER2
+HLT013_000564,EAS,Male,30,COHORT_A,GRCh38,WES,59.2,96.52,TIER3
+HLT013_000565,EAS,Male,32,COHORT_B,GRCh38,WES,30.3,88.52,TIER1
+HLT013_000566,EAS,Male,45,COHORT_C,GRCh38,WES,48.0,98.4,TIER3
+HLT013_000567,EAS,Female,72,COHORT_B,GRCh38,WES,44.6,94.9,TIER3
+HLT013_000568,EUR,Female,22,COHORT_B,GRCh38,WGS,25.2,93.89,TIER3
+HLT013_000569,EUR,Female,47,COHORT_A,GRCh38,WES,51.2,88.74,TIER1
+HLT013_000570,AFR,Female,81,COHORT_A,GRCh38,WGS,51.5,92.41,TIER2
+HLT013_000571,EUR,Female,79,COHORT_C,GRCh38,WGS,36.5,92.87,TIER1
+HLT013_000572,AMR,Male,86,COHORT_B,GRCh38,WGS,53.0,93.48,TIER1
+HLT013_000573,AFR,Female,48,COHORT_B,GRCh38,WES,51.5,90.18,TIER2
+HLT013_000574,EAS,Female,64,COHORT_B,GRCh38,WGS,26.0,94.52,TIER3
+HLT013_000575,AMR,Female,64,COHORT_A,GRCh38,WGS,36.1,94.28,TIER2
+HLT013_000576,AFR,Male,18,COHORT_B,GRCh38,WES,28.1,92.73,TIER1
+HLT013_000577,AMR,Male,42,COHORT_C,GRCh38,WGS,54.8,98.85,TIER2
+HLT013_000578,AFR,Male,21,COHORT_B,GRCh38,WES,28.0,92.36,TIER3
+HLT013_000579,AMR,Female,81,COHORT_A,GRCh38,WGS,34.5,94.78,TIER3
+HLT013_000580,EUR,Female,51,COHORT_C,GRCh38,WGS,44.0,95.5,TIER1
+HLT013_000581,AFR,Male,58,COHORT_A,GRCh38,WES,47.0,88.69,TIER2
+HLT013_000582,AFR,Female,39,COHORT_A,GRCh38,WGS,53.9,89.05,TIER1
+HLT013_000583,EUR,Female,22,COHORT_A,GRCh38,WGS,59.8,95.22,TIER2
+HLT013_000584,EUR,Male,79,COHORT_A,GRCh38,WGS,50.6,98.69,TIER1
+HLT013_000585,AMR,Male,77,COHORT_C,GRCh38,WES,34.6,96.42,TIER2
+HLT013_000586,EAS,Male,44,COHORT_C,GRCh38,WGS,34.7,89.65,TIER3
+HLT013_000587,EUR,Male,78,COHORT_A,GRCh38,WGS,55.9,89.06,TIER2
+HLT013_000588,EUR,Female,68,COHORT_A,GRCh38,WES,54.1,94.17,TIER1
+HLT013_000589,EUR,Male,34,COHORT_C,GRCh38,WES,28.6,98.35,TIER2
+HLT013_000590,EUR,Male,73,COHORT_B,GRCh38,WGS,28.0,90.84,TIER2
+HLT013_000591,SAS,Male,20,COHORT_A,GRCh38,WGS,47.6,97.73,TIER1
+HLT013_000592,AFR,Female,64,COHORT_C,GRCh38,WGS,54.3,92.54,TIER3
+HLT013_000593,EUR,Female,61,COHORT_B,GRCh38,WES,58.1,90.53,TIER1
+HLT013_000594,AFR,Male,36,COHORT_A,GRCh38,WGS,27.8,97.87,TIER3
+HLT013_000595,EUR,Female,58,COHORT_A,GRCh38,WES,30.7,98.03,TIER1
+HLT013_000596,EUR,Female,33,COHORT_A,GRCh38,WGS,59.0,97.62,TIER1
+HLT013_000597,EAS,Male,76,COHORT_A,GRCh38,WES,54.5,91.64,TIER3
+HLT013_000598,EAS,Female,65,COHORT_C,GRCh38,WES,50.1,97.12,TIER3
+HLT013_000599,SAS,Female,84,COHORT_C,GRCh38,WGS,38.7,88.98,TIER3
+HLT013_000600,EAS,Male,66,COHORT_A,GRCh38,WGS,40.1,94.59,TIER2
+HLT013_000601,AFR,Female,26,COHORT_C,GRCh38,WGS,27.4,97.13,TIER3
+HLT013_000602,EAS,Female,73,COHORT_B,GRCh38,WGS,54.1,91.68,TIER3
+HLT013_000603,AMR,Male,65,COHORT_B,GRCh38,WES,38.9,90.8,TIER1
+HLT013_000604,EAS,Male,85,COHORT_B,GRCh38,WGS,59.1,88.38,TIER1
+HLT013_000605,SAS,Female,31,COHORT_A,GRCh38,WES,39.0,96.68,TIER1
+HLT013_000606,EAS,Female,35,COHORT_A,GRCh38,WGS,31.5,96.01,TIER1
+HLT013_000607,AMR,Male,68,COHORT_B,GRCh38,WES,30.7,90.12,TIER3
+HLT013_000608,EUR,Female,74,COHORT_C,GRCh38,WGS,39.5,97.15,TIER2
+HLT013_000609,EAS,Female,65,COHORT_B,GRCh38,WES,59.3,91.31,TIER2
+HLT013_000610,AFR,Male,58,COHORT_C,GRCh38,WES,41.3,90.19,TIER1
+HLT013_000611,AFR,Male,88,COHORT_C,GRCh38,WGS,47.7,93.5,TIER1
+HLT013_000612,EAS,Male,63,COHORT_B,GRCh38,WES,37.1,98.59,TIER2
+HLT013_000613,SAS,Male,30,COHORT_B,GRCh38,WES,33.4,96.66,TIER3
+HLT013_000614,SAS,Female,44,COHORT_C,GRCh38,WGS,36.1,98.18,TIER1
+HLT013_000615,EUR,Male,72,COHORT_C,GRCh38,WES,45.6,97.06,TIER2
+HLT013_000616,EAS,Female,41,COHORT_C,GRCh38,WGS,45.9,95.68,TIER3
+HLT013_000617,EAS,Female,29,COHORT_A,GRCh38,WES,58.7,88.1,TIER2
+HLT013_000618,EUR,Female,68,COHORT_C,GRCh38,WGS,53.7,92.9,TIER2
+HLT013_000619,EUR,Female,38,COHORT_A,GRCh38,WES,43.3,92.28,TIER1
+HLT013_000620,EUR,Female,71,COHORT_C,GRCh38,WGS,26.2,94.87,TIER1
+HLT013_000621,EAS,Male,65,COHORT_A,GRCh38,WGS,29.2,89.71,TIER2
+HLT013_000622,AFR,Female,58,COHORT_B,GRCh38,WES,38.2,89.68,TIER2
+HLT013_000623,SAS,Male,47,COHORT_C,GRCh38,WGS,29.5,89.64,TIER1
+HLT013_000624,AFR,Male,46,COHORT_B,GRCh38,WES,55.1,94.74,TIER1
+HLT013_000625,SAS,Female,26,COHORT_B,GRCh38,WGS,59.6,95.73,TIER1
+HLT013_000626,AFR,Male,77,COHORT_A,GRCh38,WGS,38.3,97.72,TIER2
+HLT013_000627,EAS,Female,47,COHORT_A,GRCh38,WGS,39.6,88.17,TIER1
+HLT013_000628,EUR,Male,25,COHORT_A,GRCh38,WGS,29.6,94.57,TIER2
+HLT013_000629,AFR,Female,45,COHORT_C,GRCh38,WGS,28.8,89.8,TIER1
+HLT013_000630,AMR,Male,28,COHORT_B,GRCh38,WGS,46.5,95.17,TIER3
+HLT013_000631,SAS,Female,28,COHORT_A,GRCh38,WGS,59.5,97.21,TIER3
+HLT013_000632,AMR,Female,31,COHORT_B,GRCh38,WGS,25.8,92.45,TIER1
+HLT013_000633,EUR,Female,42,COHORT_A,GRCh38,WES,49.2,92.17,TIER1
+HLT013_000634,EUR,Male,34,COHORT_C,GRCh38,WES,51.5,91.43,TIER3
+HLT013_000635,EUR,Male,72,COHORT_C,GRCh38,WGS,34.9,97.84,TIER1
+HLT013_000636,EUR,Male,78,COHORT_A,GRCh38,WES,30.4,88.52,TIER3
+HLT013_000637,EAS,Male,85,COHORT_C,GRCh38,WGS,57.4,92.74,TIER1
+HLT013_000638,EAS,Female,44,COHORT_B,GRCh38,WES,58.7,88.06,TIER1
+HLT013_000639,EAS,Male,23,COHORT_C,GRCh38,WGS,37.2,92.03,TIER3
+HLT013_000640,AMR,Male,70,COHORT_A,GRCh38,WES,59.8,96.78,TIER3
+HLT013_000641,EAS,Male,58,COHORT_B,GRCh38,WGS,39.6,88.47,TIER1
+HLT013_000642,AMR,Female,38,COHORT_B,GRCh38,WGS,39.5,92.12,TIER2
+HLT013_000643,EUR,Male,65,COHORT_C,GRCh38,WES,59.9,94.38,TIER1
+HLT013_000644,EUR,Female,23,COHORT_B,GRCh38,WES,29.3,89.6,TIER2
+HLT013_000645,EAS,Female,80,COHORT_C,GRCh38,WGS,51.5,90.25,TIER2
+HLT013_000646,AMR,Female,62,COHORT_B,GRCh38,WES,56.8,94.99,TIER3
+HLT013_000647,EUR,Male,54,COHORT_B,GRCh38,WGS,25.0,97.96,TIER2
+HLT013_000648,AFR,Female,31,COHORT_B,GRCh38,WGS,26.0,88.61,TIER3
+HLT013_000649,EAS,Female,32,COHORT_B,GRCh38,WGS,46.4,90.49,TIER1
+HLT013_000650,EUR,Male,41,COHORT_C,GRCh38,WES,48.9,96.71,TIER1
+HLT013_000651,AFR,Female,31,COHORT_C,GRCh38,WGS,30.5,93.19,TIER1
+HLT013_000652,AMR,Male,76,COHORT_A,GRCh38,WES,45.0,92.56,TIER3
+HLT013_000653,EAS,Female,71,COHORT_B,GRCh38,WGS,59.2,98.66,TIER1
+HLT013_000654,EUR,Male,53,COHORT_C,GRCh38,WES,56.5,98.09,TIER3
+HLT013_000655,AMR,Male,44,COHORT_A,GRCh38,WGS,50.0,96.59,TIER1
+HLT013_000656,EUR,Male,43,COHORT_B,GRCh38,WGS,57.4,95.96,TIER2
+HLT013_000657,AMR,Male,56,COHORT_A,GRCh38,WES,53.8,95.1,TIER2
+HLT013_000658,EUR,Female,64,COHORT_B,GRCh38,WES,46.3,95.45,TIER3
+HLT013_000659,AFR,Female,30,COHORT_B,GRCh38,WES,26.5,91.3,TIER2
+HLT013_000660,EUR,Male,84,COHORT_A,GRCh38,WGS,37.7,91.89,TIER1
+HLT013_000661,EUR,Female,73,COHORT_C,GRCh38,WGS,35.4,93.29,TIER1
+HLT013_000662,AMR,Male,53,COHORT_C,GRCh38,WGS,51.9,91.5,TIER2
+HLT013_000663,EUR,Female,48,COHORT_A,GRCh38,WGS,38.5,90.96,TIER2
+HLT013_000664,EUR,Female,43,COHORT_B,GRCh38,WGS,51.7,94.42,TIER2
+HLT013_000665,EUR,Male,64,COHORT_B,GRCh38,WES,40.3,94.01,TIER2
+HLT013_000666,EAS,Female,18,COHORT_C,GRCh38,WGS,27.7,93.71,TIER1
+HLT013_000667,AMR,Male,23,COHORT_A,GRCh38,WGS,55.4,93.09,TIER1
+HLT013_000668,SAS,Female,28,COHORT_A,GRCh38,WGS,34.9,91.41,TIER1
+HLT013_000669,EUR,Female,48,COHORT_B,GRCh38,WGS,34.4,92.86,TIER3
+HLT013_000670,AFR,Male,31,COHORT_A,GRCh38,WGS,44.8,95.13,TIER2
+HLT013_000671,EUR,Male,89,COHORT_B,GRCh38,WGS,50.1,91.55,TIER2
+HLT013_000672,AFR,Male,21,COHORT_A,GRCh38,WES,42.4,97.52,TIER1
+HLT013_000673,SAS,Female,50,COHORT_A,GRCh38,WES,27.4,92.66,TIER2
+HLT013_000674,EAS,Female,73,COHORT_A,GRCh38,WES,28.6,88.08,TIER2
+HLT013_000675,AFR,Female,49,COHORT_B,GRCh38,WGS,32.1,88.02,TIER3
+HLT013_000676,EUR,Male,24,COHORT_B,GRCh38,WES,47.2,95.7,TIER1
+HLT013_000677,AMR,Male,50,COHORT_B,GRCh38,WGS,33.6,93.14,TIER1
+HLT013_000678,AFR,Female,20,COHORT_A,GRCh38,WES,39.6,96.93,TIER3
+HLT013_000679,EUR,Female,67,COHORT_B,GRCh38,WES,55.8,91.33,TIER1
+HLT013_000680,EUR,Female,44,COHORT_A,GRCh38,WES,38.4,90.08,TIER2
+HLT013_000681,EUR,Male,30,COHORT_B,GRCh38,WGS,30.7,96.34,TIER1
+HLT013_000682,EUR,Female,72,COHORT_A,GRCh38,WGS,35.1,90.44,TIER2
+HLT013_000683,EUR,Male,75,COHORT_A,GRCh38,WGS,58.4,95.85,TIER2
+HLT013_000684,AFR,Female,77,COHORT_A,GRCh38,WGS,25.3,89.59,TIER3
+HLT013_000685,EAS,Male,35,COHORT_A,GRCh38,WGS,46.6,94.43,TIER3
+HLT013_000686,EUR,Male,54,COHORT_B,GRCh38,WGS,40.4,97.08,TIER3
+HLT013_000687,AFR,Female,78,COHORT_A,GRCh38,WES,25.7,97.88,TIER1
+HLT013_000688,SAS,Male,26,COHORT_B,GRCh38,WES,38.1,90.62,TIER1
+HLT013_000689,EAS,Male,52,COHORT_C,GRCh38,WGS,43.3,96.94,TIER2
+HLT013_000690,AFR,Female,39,COHORT_B,GRCh38,WES,41.3,97.83,TIER1
+HLT013_000691,EUR,Male,25,COHORT_C,GRCh38,WGS,41.4,96.38,TIER1
+HLT013_000692,AMR,Male,25,COHORT_C,GRCh38,WGS,41.8,91.89,TIER2
+HLT013_000693,EUR,Female,31,COHORT_A,GRCh38,WGS,32.7,95.08,TIER3
+HLT013_000694,EUR,Female,42,COHORT_B,GRCh38,WES,59.4,94.21,TIER3
+HLT013_000695,AMR,Female,25,COHORT_A,GRCh38,WES,58.6,94.24,TIER2
+HLT013_000696,AFR,Female,36,COHORT_C,GRCh38,WGS,35.9,97.03,TIER2
+HLT013_000697,EAS,Male,75,COHORT_C,GRCh38,WGS,30.8,96.35,TIER1
+HLT013_000698,AFR,Female,31,COHORT_B,GRCh38,WES,45.1,94.04,TIER1
+HLT013_000699,EAS,Male,28,COHORT_A,GRCh38,WGS,55.2,91.05,TIER3
+HLT013_000700,EUR,Male,63,COHORT_B,GRCh38,WGS,37.1,96.3,TIER3
+HLT013_000701,EUR,Female,88,COHORT_C,GRCh38,WGS,36.1,88.6,TIER3
+HLT013_000702,EUR,Female,41,COHORT_A,GRCh38,WGS,53.0,95.5,TIER3
+HLT013_000703,EUR,Male,82,COHORT_A,GRCh38,WGS,33.6,91.51,TIER1
+HLT013_000704,AMR,Female,53,COHORT_A,GRCh38,WES,53.5,90.45,TIER3
+HLT013_000705,EUR,Male,42,COHORT_C,GRCh38,WES,54.0,97.46,TIER3
+HLT013_000706,AFR,Female,71,COHORT_B,GRCh38,WES,48.5,90.77,TIER3
+HLT013_000707,EAS,Male,85,COHORT_B,GRCh38,WGS,27.2,90.12,TIER1
+HLT013_000708,EAS,Female,89,COHORT_B,GRCh38,WGS,34.4,92.48,TIER3
+HLT013_000709,AFR,Male,56,COHORT_C,GRCh38,WGS,59.2,94.19,TIER3
+HLT013_000710,AFR,Male,26,COHORT_C,GRCh38,WES,49.0,90.44,TIER3
+HLT013_000711,SAS,Female,35,COHORT_B,GRCh38,WGS,44.5,89.82,TIER3
+HLT013_000712,EAS,Female,25,COHORT_C,GRCh38,WGS,51.8,89.58,TIER3
+HLT013_000713,AMR,Male,52,COHORT_B,GRCh38,WGS,52.7,98.56,TIER3
+HLT013_000714,AMR,Male,49,COHORT_A,GRCh38,WES,27.2,98.35,TIER2
+HLT013_000715,EAS,Male,24,COHORT_C,GRCh38,WES,39.5,89.71,TIER2
+HLT013_000716,EUR,Female,85,COHORT_A,GRCh38,WGS,26.4,91.43,TIER2
+HLT013_000717,AFR,Male,61,COHORT_A,GRCh38,WGS,47.0,92.49,TIER3
+HLT013_000718,EUR,Female,33,COHORT_C,GRCh38,WGS,53.4,94.45,TIER3
+HLT013_000719,EAS,Male,83,COHORT_B,GRCh38,WGS,27.1,96.15,TIER2
+HLT013_000720,SAS,Male,43,COHORT_C,GRCh38,WES,44.0,93.17,TIER1
+HLT013_000721,AFR,Female,18,COHORT_A,GRCh38,WGS,29.7,88.28,TIER1
+HLT013_000722,AFR,Female,48,COHORT_C,GRCh38,WGS,46.1,97.96,TIER1
+HLT013_000723,EUR,Male,66,COHORT_A,GRCh38,WES,39.5,89.29,TIER1
+HLT013_000724,SAS,Female,22,COHORT_C,GRCh38,WGS,48.7,95.49,TIER2
+HLT013_000725,EUR,Male,70,COHORT_B,GRCh38,WES,57.6,92.23,TIER1
+HLT013_000726,EUR,Male,53,COHORT_C,GRCh38,WGS,42.4,98.55,TIER1
+HLT013_000727,EUR,Male,58,COHORT_C,GRCh38,WGS,49.2,96.29,TIER2
+HLT013_000728,EUR,Male,47,COHORT_C,GRCh38,WGS,46.0,98.92,TIER2
+HLT013_000729,AFR,Male,64,COHORT_A,GRCh38,WGS,25.4,95.27,TIER3
+HLT013_000730,AFR,Male,48,COHORT_B,GRCh38,WGS,29.1,94.06,TIER3
+HLT013_000731,EUR,Male,45,COHORT_A,GRCh38,WGS,34.4,88.64,TIER3
+HLT013_000732,EUR,Male,89,COHORT_B,GRCh38,WES,57.5,92.89,TIER1
+HLT013_000733,EUR,Female,77,COHORT_C,GRCh38,WGS,54.1,90.5,TIER1
+HLT013_000734,EUR,Female,82,COHORT_A,GRCh38,WGS,39.7,95.1,TIER3
+HLT013_000735,EUR,Female,63,COHORT_B,GRCh38,WGS,58.8,97.2,TIER1
+HLT013_000736,EAS,Male,53,COHORT_B,GRCh38,WGS,56.6,93.43,TIER2
+HLT013_000737,EUR,Female,33,COHORT_A,GRCh38,WGS,49.0,98.5,TIER1
+HLT013_000738,EUR,Female,35,COHORT_A,GRCh38,WGS,27.1,98.3,TIER3
+HLT013_000739,EUR,Female,40,COHORT_B,GRCh38,WGS,43.7,95.53,TIER1
+HLT013_000740,AFR,Male,78,COHORT_C,GRCh38,WGS,51.3,94.48,TIER1
+HLT013_000741,EUR,Female,23,COHORT_B,GRCh38,WGS,50.0,95.59,TIER1
+HLT013_000742,EUR,Male,47,COHORT_C,GRCh38,WGS,57.6,93.03,TIER2
+HLT013_000743,AMR,Male,65,COHORT_A,GRCh38,WES,44.3,95.7,TIER1
+HLT013_000744,EUR,Male,44,COHORT_A,GRCh38,WGS,31.3,98.29,TIER1
+HLT013_000745,AFR,Male,49,COHORT_A,GRCh38,WGS,48.1,93.16,TIER2
+HLT013_000746,AFR,Female,46,COHORT_B,GRCh38,WGS,37.4,91.11,TIER1
+HLT013_000747,EUR,Female,79,COHORT_A,GRCh38,WGS,47.3,97.47,TIER1
+HLT013_000748,AFR,Female,85,COHORT_B,GRCh38,WES,28.3,92.38,TIER3
+HLT013_000749,EAS,Male,39,COHORT_A,GRCh38,WGS,54.3,91.05,TIER3
+HLT013_000750,AMR,Male,73,COHORT_B,GRCh38,WES,25.4,91.04,TIER2
+HLT013_000751,EUR,Male,22,COHORT_A,GRCh38,WGS,28.2,94.67,TIER1
+HLT013_000752,EUR,Male,85,COHORT_C,GRCh38,WGS,33.3,98.73,TIER3
+HLT013_000753,EUR,Female,29,COHORT_B,GRCh38,WES,33.0,91.08,TIER3
+HLT013_000754,AFR,Male,30,COHORT_A,GRCh38,WGS,28.9,98.65,TIER1
+HLT013_000755,EAS,Male,55,COHORT_B,GRCh38,WGS,40.2,98.65,TIER1
+HLT013_000756,EUR,Male,63,COHORT_B,GRCh38,WGS,42.9,96.26,TIER2
+HLT013_000757,EUR,Female,45,COHORT_C,GRCh38,WGS,40.2,95.15,TIER2
+HLT013_000758,SAS,Male,31,COHORT_C,GRCh38,WGS,31.4,98.34,TIER1
+HLT013_000759,EUR,Female,83,COHORT_A,GRCh38,WGS,33.8,96.85,TIER1
+HLT013_000760,AFR,Male,75,COHORT_A,GRCh38,WES,29.7,98.41,TIER2
+HLT013_000761,EAS,Male,34,COHORT_A,GRCh38,WGS,47.0,93.86,TIER3
+HLT013_000762,EUR,Male,49,COHORT_B,GRCh38,WGS,44.8,93.26,TIER2
+HLT013_000763,EUR,Female,26,COHORT_B,GRCh38,WES,40.9,97.05,TIER2
+HLT013_000764,EUR,Male,83,COHORT_B,GRCh38,WES,45.7,98.7,TIER2
+HLT013_000765,AMR,Male,50,COHORT_A,GRCh38,WGS,53.9,97.83,TIER3
+HLT013_000766,EUR,Female,62,COHORT_C,GRCh38,WGS,51.2,92.99,TIER2
+HLT013_000767,EUR,Female,35,COHORT_A,GRCh38,WES,31.9,90.96,TIER3
+HLT013_000768,EUR,Male,81,COHORT_C,GRCh38,WGS,59.7,95.66,TIER1
+HLT013_000769,EUR,Male,22,COHORT_C,GRCh38,WES,45.7,97.86,TIER2
+HLT013_000770,EAS,Female,62,COHORT_A,GRCh38,WGS,48.9,90.77,TIER3
+HLT013_000771,EUR,Male,58,COHORT_A,GRCh38,WGS,57.5,88.64,TIER1
+HLT013_000772,AFR,Male,87,COHORT_C,GRCh38,WES,44.2,94.3,TIER1
+HLT013_000773,AFR,Male,46,COHORT_B,GRCh38,WGS,49.3,90.51,TIER2
+HLT013_000774,AMR,Male,27,COHORT_C,GRCh38,WGS,36.8,88.16,TIER3
+HLT013_000775,EUR,Female,25,COHORT_A,GRCh38,WES,57.3,93.16,TIER1
+HLT013_000776,AMR,Male,33,COHORT_A,GRCh38,WES,25.7,95.68,TIER1
+HLT013_000777,EAS,Female,45,COHORT_A,GRCh38,WGS,40.1,94.89,TIER1
+HLT013_000778,EUR,Female,54,COHORT_C,GRCh38,WES,40.6,90.75,TIER1
+HLT013_000779,EAS,Male,71,COHORT_A,GRCh38,WES,38.8,90.06,TIER3
+HLT013_000780,AMR,Female,73,COHORT_A,GRCh38,WGS,45.6,93.06,TIER2
+HLT013_000781,EUR,Male,79,COHORT_B,GRCh38,WGS,44.7,92.55,TIER2
+HLT013_000782,AMR,Male,36,COHORT_A,GRCh38,WES,45.0,95.93,TIER3
+HLT013_000783,AFR,Female,76,COHORT_C,GRCh38,WES,41.8,96.85,TIER3
+HLT013_000784,EAS,Female,55,COHORT_C,GRCh38,WES,37.5,97.6,TIER3
+HLT013_000785,SAS,Male,45,COHORT_C,GRCh38,WES,34.3,94.74,TIER1
+HLT013_000786,EUR,Male,71,COHORT_A,GRCh38,WES,55.4,91.64,TIER2
+HLT013_000787,AMR,Female,69,COHORT_B,GRCh38,WGS,46.4,89.67,TIER1
+HLT013_000788,EUR,Male,60,COHORT_B,GRCh38,WGS,58.2,92.32,TIER2
+HLT013_000789,EAS,Female,78,COHORT_A,GRCh38,WES,47.1,94.89,TIER3
+HLT013_000790,EAS,Male,46,COHORT_A,GRCh38,WGS,25.5,92.06,TIER1
+HLT013_000791,EUR,Male,69,COHORT_A,GRCh38,WES,38.2,98.17,TIER1
+HLT013_000792,AFR,Male,52,COHORT_C,GRCh38,WES,26.8,89.92,TIER1
+HLT013_000793,EUR,Female,39,COHORT_B,GRCh38,WGS,36.3,93.9,TIER1
+HLT013_000794,EUR,Female,27,COHORT_A,GRCh38,WES,46.3,97.92,TIER2
+HLT013_000795,EUR,Male,28,COHORT_B,GRCh38,WGS,53.1,92.77,TIER3
+HLT013_000796,EUR,Female,74,COHORT_B,GRCh38,WGS,44.1,91.25,TIER1
+HLT013_000797,EUR,Male,22,COHORT_A,GRCh38,WGS,51.4,90.99,TIER3
+HLT013_000798,EUR,Male,68,COHORT_C,GRCh38,WGS,56.6,92.46,TIER3
+HLT013_000799,EAS,Female,43,COHORT_A,GRCh38,WGS,30.0,89.82,TIER3
+HLT013_000800,EAS,Male,64,COHORT_A,GRCh38,WGS,50.5,90.97,TIER3
+HLT013_000801,EAS,Male,22,COHORT_C,GRCh38,WGS,32.9,98.39,TIER1
+HLT013_000802,EUR,Female,37,COHORT_A,GRCh38,WGS,56.2,95.68,TIER3
+HLT013_000803,AMR,Female,64,COHORT_A,GRCh38,WGS,58.4,92.96,TIER2
+HLT013_000804,AFR,Male,54,COHORT_A,GRCh38,WES,48.7,92.7,TIER1
+HLT013_000805,EUR,Male,35,COHORT_B,GRCh38,WGS,50.6,91.6,TIER1
+HLT013_000806,EUR,Female,26,COHORT_B,GRCh38,WGS,42.7,95.37,TIER1
+HLT013_000807,EAS,Male,22,COHORT_C,GRCh38,WES,35.5,98.16,TIER1
+HLT013_000808,EUR,Male,73,COHORT_A,GRCh38,WGS,44.6,90.17,TIER3
+HLT013_000809,AFR,Female,57,COHORT_B,GRCh38,WGS,26.7,97.76,TIER2
+HLT013_000810,SAS,Male,24,COHORT_A,GRCh38,WGS,53.0,95.48,TIER3
+HLT013_000811,EUR,Male,59,COHORT_A,GRCh38,WGS,53.9,93.19,TIER2
+HLT013_000812,EUR,Female,43,COHORT_C,GRCh38,WES,39.1,92.24,TIER3
+HLT013_000813,SAS,Male,73,COHORT_A,GRCh38,WES,50.2,96.81,TIER2
+HLT013_000814,AFR,Male,88,COHORT_C,GRCh38,WGS,47.9,94.98,TIER2
+HLT013_000815,EUR,Female,57,COHORT_B,GRCh38,WGS,57.7,90.94,TIER2
+HLT013_000816,AMR,Female,19,COHORT_C,GRCh38,WGS,35.0,98.65,TIER1
+HLT013_000817,AMR,Male,86,COHORT_A,GRCh38,WGS,53.0,92.41,TIER2
+HLT013_000818,AFR,Female,22,COHORT_A,GRCh38,WGS,42.2,95.45,TIER1
+HLT013_000819,EAS,Male,55,COHORT_A,GRCh38,WGS,43.0,97.42,TIER1
+HLT013_000820,EUR,Female,50,COHORT_B,GRCh38,WGS,39.8,95.14,TIER2
+HLT013_000821,EUR,Male,60,COHORT_C,GRCh38,WGS,35.0,92.39,TIER1
+HLT013_000822,AFR,Male,33,COHORT_B,GRCh38,WES,37.9,90.17,TIER1
+HLT013_000823,EUR,Male,58,COHORT_C,GRCh38,WGS,34.7,92.59,TIER2
+HLT013_000824,EAS,Female,36,COHORT_B,GRCh38,WES,53.1,91.66,TIER2
+HLT013_000825,AMR,Female,20,COHORT_B,GRCh38,WGS,25.1,98.2,TIER1
+HLT013_000826,EUR,Female,36,COHORT_A,GRCh38,WGS,33.7,91.89,TIER2
+HLT013_000827,AFR,Male,26,COHORT_A,GRCh38,WES,33.8,98.43,TIER2
+HLT013_000828,EUR,Male,21,COHORT_C,GRCh38,WGS,49.6,91.04,TIER3
+HLT013_000829,AMR,Female,86,COHORT_C,GRCh38,WGS,48.1,98.42,TIER3
+HLT013_000830,EUR,Male,51,COHORT_A,GRCh38,WGS,34.0,98.59,TIER2
+HLT013_000831,EAS,Male,85,COHORT_B,GRCh38,WGS,32.9,88.57,TIER3
+HLT013_000832,AFR,Female,19,COHORT_A,GRCh38,WES,41.3,95.0,TIER1
+HLT013_000833,EUR,Male,31,COHORT_A,GRCh38,WES,32.9,92.83,TIER2
+HLT013_000834,EAS,Male,65,COHORT_A,GRCh38,WES,43.4,97.67,TIER1
+HLT013_000835,EAS,Female,42,COHORT_A,GRCh38,WES,46.6,90.91,TIER2
+HLT013_000836,AFR,Female,48,COHORT_A,GRCh38,WES,28.6,94.97,TIER3
+HLT013_000837,EAS,Female,66,COHORT_A,GRCh38,WES,54.6,93.19,TIER2
+HLT013_000838,SAS,Female,36,COHORT_A,GRCh38,WES,33.9,94.52,TIER1
+HLT013_000839,AFR,Female,67,COHORT_C,GRCh38,WES,44.4,96.64,TIER2
+HLT013_000840,AFR,Male,80,COHORT_C,GRCh38,WES,46.4,90.21,TIER2
+HLT013_000841,EUR,Male,23,COHORT_A,GRCh38,WES,50.1,96.85,TIER3
+HLT013_000842,EAS,Male,36,COHORT_B,GRCh38,WES,32.3,94.6,TIER3
+HLT013_000843,AFR,Male,38,COHORT_B,GRCh38,WGS,41.9,94.5,TIER2
+HLT013_000844,AFR,Male,46,COHORT_B,GRCh38,WES,26.9,89.54,TIER3
+HLT013_000845,EUR,Male,49,COHORT_C,GRCh38,WGS,59.9,89.28,TIER1
+HLT013_000846,AMR,Female,64,COHORT_C,GRCh38,WES,53.9,96.32,TIER2
+HLT013_000847,EUR,Female,48,COHORT_B,GRCh38,WGS,49.2,93.63,TIER1
+HLT013_000848,EAS,Male,58,COHORT_A,GRCh38,WGS,32.1,92.03,TIER3
+HLT013_000849,EUR,Female,72,COHORT_B,GRCh38,WGS,49.3,90.6,TIER2
+HLT013_000850,SAS,Male,31,COHORT_A,GRCh38,WGS,33.9,89.47,TIER1
+HLT013_000851,EUR,Female,24,COHORT_A,GRCh38,WGS,56.5,97.38,TIER1
+HLT013_000852,EUR,Male,85,COHORT_B,GRCh38,WGS,32.5,92.39,TIER3
+HLT013_000853,AMR,Male,67,COHORT_B,GRCh38,WGS,41.1,90.56,TIER3
+HLT013_000854,AMR,Female,44,COHORT_B,GRCh38,WES,54.8,98.2,TIER3
+HLT013_000855,EUR,Female,89,COHORT_C,GRCh38,WES,31.1,92.35,TIER1
+HLT013_000856,AFR,Female,23,COHORT_C,GRCh38,WES,39.1,92.64,TIER2
+HLT013_000857,EAS,Male,24,COHORT_C,GRCh38,WES,51.4,97.35,TIER1
+HLT013_000858,AMR,Female,32,COHORT_A,GRCh38,WGS,36.2,93.21,TIER1
+HLT013_000859,EUR,Male,86,COHORT_A,GRCh38,WGS,37.8,96.97,TIER2
+HLT013_000860,AFR,Female,64,COHORT_C,GRCh38,WGS,41.1,88.44,TIER2
+HLT013_000861,EAS,Female,70,COHORT_B,GRCh38,WES,32.6,91.11,TIER3
+HLT013_000862,EAS,Female,26,COHORT_B,GRCh38,WES,36.1,92.89,TIER3
+HLT013_000863,EAS,Male,71,COHORT_A,GRCh38,WES,54.8,88.87,TIER3
+HLT013_000864,AFR,Male,48,COHORT_B,GRCh38,WGS,57.5,95.8,TIER1
+HLT013_000865,EUR,Female,18,COHORT_B,GRCh38,WES,47.0,91.19,TIER1
+HLT013_000866,AMR,Female,82,COHORT_A,GRCh38,WES,36.8,89.64,TIER1
+HLT013_000867,AMR,Female,77,COHORT_B,GRCh38,WES,56.6,95.04,TIER2
+HLT013_000868,EAS,Female,74,COHORT_B,GRCh38,WGS,39.3,88.59,TIER1
+HLT013_000869,EUR,Male,24,COHORT_C,GRCh38,WGS,56.0,93.14,TIER3
+HLT013_000870,EUR,Female,62,COHORT_C,GRCh38,WGS,36.2,98.65,TIER2
+HLT013_000871,EAS,Female,70,COHORT_A,GRCh38,WES,25.7,96.57,TIER3
+HLT013_000872,EUR,Female,37,COHORT_B,GRCh38,WGS,47.1,88.77,TIER2
+HLT013_000873,SAS,Female,44,COHORT_B,GRCh38,WES,29.1,93.71,TIER2
+HLT013_000874,EUR,Female,60,COHORT_C,GRCh38,WGS,55.9,89.33,TIER3
+HLT013_000875,EAS,Male,55,COHORT_A,GRCh38,WGS,56.1,96.53,TIER2
+HLT013_000876,AMR,Female,28,COHORT_C,GRCh38,WGS,39.8,91.02,TIER3
+HLT013_000877,EUR,Female,55,COHORT_C,GRCh38,WGS,37.3,96.56,TIER3
+HLT013_000878,EUR,Male,78,COHORT_B,GRCh38,WGS,26.3,92.73,TIER3
+HLT013_000879,EAS,Female,56,COHORT_C,GRCh38,WGS,37.6,88.06,TIER3
+HLT013_000880,AFR,Male,28,COHORT_A,GRCh38,WES,48.0,93.55,TIER3
+HLT013_000881,AFR,Female,20,COHORT_C,GRCh38,WGS,26.1,88.6,TIER2
+HLT013_000882,EAS,Male,18,COHORT_B,GRCh38,WGS,31.4,91.3,TIER3
+HLT013_000883,SAS,Male,40,COHORT_A,GRCh38,WES,26.3,89.87,TIER1
+HLT013_000884,AFR,Female,54,COHORT_B,GRCh38,WES,39.3,98.41,TIER3
+HLT013_000885,EUR,Female,55,COHORT_C,GRCh38,WES,26.0,92.03,TIER2
+HLT013_000886,EUR,Male,77,COHORT_A,GRCh38,WGS,38.8,93.43,TIER1
+HLT013_000887,EUR,Female,69,COHORT_A,GRCh38,WGS,29.7,90.71,TIER3
+HLT013_000888,EUR,Female,55,COHORT_A,GRCh38,WES,44.6,95.05,TIER3
+HLT013_000889,EUR,Male,19,COHORT_A,GRCh38,WES,30.5,98.98,TIER1
+HLT013_000890,EAS,Male,77,COHORT_C,GRCh38,WES,42.8,89.96,TIER1
+HLT013_000891,EUR,Male,69,COHORT_A,GRCh38,WGS,30.5,97.23,TIER1
+HLT013_000892,SAS,Male,78,COHORT_B,GRCh38,WGS,47.7,94.23,TIER1
+HLT013_000893,EUR,Male,44,COHORT_C,GRCh38,WES,43.8,91.79,TIER2
+HLT013_000894,EUR,Male,28,COHORT_A,GRCh38,WGS,57.4,89.15,TIER2
+HLT013_000895,EAS,Female,51,COHORT_A,GRCh38,WGS,46.1,93.57,TIER2
+HLT013_000896,AMR,Male,24,COHORT_C,GRCh38,WGS,42.5,98.82,TIER3
+HLT013_000897,EUR,Female,24,COHORT_B,GRCh38,WES,26.6,92.9,TIER2
+HLT013_000898,EUR,Male,22,COHORT_C,GRCh38,WGS,56.1,97.03,TIER2
+HLT013_000899,EUR,Female,79,COHORT_C,GRCh38,WGS,58.0,97.33,TIER1
+HLT013_000900,AFR,Female,39,COHORT_A,GRCh38,WGS,39.9,96.2,TIER3
+HLT013_000901,AFR,Female,31,COHORT_A,GRCh38,WGS,46.3,90.99,TIER1
+HLT013_000902,EUR,Female,24,COHORT_B,GRCh38,WGS,59.1,88.26,TIER1
+HLT013_000903,EUR,Male,86,COHORT_C,GRCh38,WGS,56.8,94.36,TIER2
+HLT013_000904,AFR,Female,22,COHORT_C,GRCh38,WGS,38.5,89.27,TIER3
+HLT013_000905,SAS,Female,88,COHORT_C,GRCh38,WES,36.9,88.08,TIER1
+HLT013_000906,EAS,Female,57,COHORT_B,GRCh38,WGS,27.1,90.61,TIER2
+HLT013_000907,AFR,Female,29,COHORT_A,GRCh38,WGS,41.4,88.11,TIER2
+HLT013_000908,EUR,Female,77,COHORT_A,GRCh38,WGS,41.9,94.85,TIER3
+HLT013_000909,EUR,Female,19,COHORT_B,GRCh38,WGS,53.1,88.37,TIER2
+HLT013_000910,EUR,Female,18,COHORT_B,GRCh38,WGS,55.7,90.78,TIER2
+HLT013_000911,EAS,Female,21,COHORT_B,GRCh38,WGS,49.7,89.66,TIER3
+HLT013_000912,AMR,Female,21,COHORT_C,GRCh38,WGS,38.8,90.89,TIER2
+HLT013_000913,AMR,Male,64,COHORT_A,GRCh38,WGS,56.2,89.85,TIER3
+HLT013_000914,SAS,Male,61,COHORT_B,GRCh38,WES,26.4,95.65,TIER3
+HLT013_000915,SAS,Female,60,COHORT_B,GRCh38,WES,41.6,88.83,TIER2
+HLT013_000916,SAS,Male,80,COHORT_C,GRCh38,WGS,44.4,96.07,TIER1
+HLT013_000917,EUR,Male,86,COHORT_C,GRCh38,WES,52.8,91.22,TIER1
+HLT013_000918,EUR,Male,63,COHORT_C,GRCh38,WES,50.8,88.31,TIER2
+HLT013_000919,EUR,Female,43,COHORT_B,GRCh38,WGS,29.9,93.8,TIER3
+HLT013_000920,AFR,Male,33,COHORT_B,GRCh38,WGS,46.4,94.18,TIER3
+HLT013_000921,EUR,Male,60,COHORT_A,GRCh38,WES,26.9,88.91,TIER3
+HLT013_000922,AMR,Female,52,COHORT_A,GRCh38,WES,33.5,88.1,TIER2
+HLT013_000923,EAS,Female,85,COHORT_C,GRCh38,WGS,52.3,93.67,TIER3
+HLT013_000924,AFR,Female,37,COHORT_C,GRCh38,WES,30.4,98.46,TIER2
+HLT013_000925,EUR,Female,46,COHORT_C,GRCh38,WGS,29.7,90.58,TIER1
+HLT013_000926,EUR,Female,46,COHORT_A,GRCh38,WES,26.9,97.57,TIER2
+HLT013_000927,EUR,Male,61,COHORT_C,GRCh38,WES,26.7,97.18,TIER1
+HLT013_000928,AMR,Male,37,COHORT_C,GRCh38,WES,56.4,98.62,TIER3
+HLT013_000929,AFR,Female,48,COHORT_B,GRCh38,WES,53.4,93.02,TIER1
+HLT013_000930,EAS,Female,31,COHORT_B,GRCh38,WES,34.2,92.33,TIER3
+HLT013_000931,EUR,Male,60,COHORT_A,GRCh38,WGS,29.4,89.11,TIER3
+HLT013_000932,EUR,Male,41,COHORT_B,GRCh38,WES,40.6,94.44,TIER2
+HLT013_000933,AFR,Female,19,COHORT_B,GRCh38,WES,50.4,97.41,TIER3
+HLT013_000934,EAS,Female,68,COHORT_A,GRCh38,WGS,52.3,96.1,TIER2
+HLT013_000935,EAS,Female,81,COHORT_C,GRCh38,WGS,45.3,96.78,TIER3
+HLT013_000936,EUR,Male,87,COHORT_B,GRCh38,WGS,55.7,96.94,TIER2
+HLT013_000937,SAS,Female,61,COHORT_B,GRCh38,WES,41.5,89.23,TIER2
+HLT013_000938,EUR,Female,18,COHORT_A,GRCh38,WGS,33.5,90.59,TIER2
+HLT013_000939,AMR,Male,79,COHORT_B,GRCh38,WGS,29.6,93.21,TIER1
+HLT013_000940,EUR,Male,73,COHORT_B,GRCh38,WGS,28.0,88.64,TIER2
+HLT013_000941,EUR,Female,33,COHORT_B,GRCh38,WES,38.1,98.67,TIER2
+HLT013_000942,AMR,Male,39,COHORT_B,GRCh38,WGS,32.2,90.73,TIER3
+HLT013_000943,EUR,Male,59,COHORT_B,GRCh38,WGS,33.8,90.69,TIER1
+HLT013_000944,AFR,Female,73,COHORT_C,GRCh38,WGS,47.4,95.47,TIER3
+HLT013_000945,AFR,Male,42,COHORT_B,GRCh38,WGS,58.5,96.24,TIER1
+HLT013_000946,EUR,Male,18,COHORT_B,GRCh38,WGS,42.7,95.12,TIER2
+HLT013_000947,EAS,Male,34,COHORT_A,GRCh38,WGS,43.4,97.11,TIER3
+HLT013_000948,AMR,Male,35,COHORT_C,GRCh38,WGS,46.4,94.14,TIER2
+HLT013_000949,AMR,Male,88,COHORT_A,GRCh38,WGS,50.4,98.74,TIER3
+HLT013_000950,EUR,Female,66,COHORT_B,GRCh38,WES,53.3,90.78,TIER3
+HLT013_000951,AFR,Female,21,COHORT_C,GRCh38,WGS,27.7,94.22,TIER2
+HLT013_000952,EUR,Female,47,COHORT_B,GRCh38,WES,41.3,88.22,TIER1
+HLT013_000953,EUR,Male,64,COHORT_C,GRCh38,WGS,26.2,94.84,TIER3
+HLT013_000954,EUR,Male,28,COHORT_C,GRCh38,WGS,28.8,91.23,TIER1
+HLT013_000955,SAS,Male,21,COHORT_A,GRCh38,WES,42.6,93.92,TIER2
+HLT013_000956,AMR,Male,28,COHORT_A,GRCh38,WGS,48.2,91.82,TIER1
+HLT013_000957,EAS,Male,55,COHORT_B,GRCh38,WES,51.1,93.18,TIER1
+HLT013_000958,AFR,Female,47,COHORT_A,GRCh38,WGS,35.0,89.79,TIER1
+HLT013_000959,AFR,Male,61,COHORT_C,GRCh38,WGS,45.4,94.82,TIER3
+HLT013_000960,AFR,Female,64,COHORT_B,GRCh38,WGS,59.6,88.61,TIER3
+HLT013_000961,AFR,Female,30,COHORT_B,GRCh38,WGS,43.9,93.55,TIER2
+HLT013_000962,AFR,Male,77,COHORT_A,GRCh38,WGS,29.8,93.83,TIER1
+HLT013_000963,EUR,Female,26,COHORT_C,GRCh38,WES,26.9,88.87,TIER2
+HLT013_000964,EUR,Female,52,COHORT_B,GRCh38,WES,29.7,95.2,TIER1
+HLT013_000965,SAS,Male,65,COHORT_C,GRCh38,WGS,52.4,98.15,TIER2
+HLT013_000966,AFR,Female,50,COHORT_B,GRCh38,WGS,28.6,96.81,TIER3
+HLT013_000967,SAS,Female,50,COHORT_C,GRCh38,WES,30.0,97.41,TIER3
+HLT013_000968,EUR,Female,38,COHORT_C,GRCh38,WGS,49.8,95.9,TIER3
+HLT013_000969,AFR,Male,80,COHORT_C,GRCh38,WGS,43.8,97.83,TIER3
+HLT013_000970,EUR,Female,42,COHORT_A,GRCh38,WES,59.7,98.0,TIER2
+HLT013_000971,EUR,Male,50,COHORT_A,GRCh38,WGS,37.0,89.43,TIER1
+HLT013_000972,EUR,Female,25,COHORT_B,GRCh38,WGS,42.9,97.63,TIER1
+HLT013_000973,EUR,Male,19,COHORT_A,GRCh38,WGS,33.9,98.2,TIER2
+HLT013_000974,AMR,Female,20,COHORT_C,GRCh38,WGS,58.6,88.22,TIER1
+HLT013_000975,EUR,Male,25,COHORT_A,GRCh38,WES,38.5,98.4,TIER3
+HLT013_000976,EAS,Female,50,COHORT_A,GRCh38,WGS,36.9,98.6,TIER3
+HLT013_000977,AFR,Female,31,COHORT_C,GRCh38,WGS,51.2,91.95,TIER2
+HLT013_000978,AFR,Male,82,COHORT_B,GRCh38,WGS,51.2,96.79,TIER3
+HLT013_000979,AFR,Male,50,COHORT_C,GRCh38,WES,47.8,91.82,TIER3
+HLT013_000980,EUR,Female,20,COHORT_A,GRCh38,WGS,52.3,88.04,TIER3
+HLT013_000981,SAS,Male,48,COHORT_B,GRCh38,WGS,42.5,94.51,TIER1
+HLT013_000982,AMR,Male,37,COHORT_B,GRCh38,WGS,54.2,92.24,TIER2
+HLT013_000983,EAS,Male,34,COHORT_B,GRCh38,WGS,36.4,93.61,TIER2
+HLT013_000984,AFR,Male,31,COHORT_A,GRCh38,WGS,35.1,94.86,TIER3
+HLT013_000985,EUR,Male,50,COHORT_B,GRCh38,WES,43.4,91.04,TIER1
+HLT013_000986,SAS,Male,20,COHORT_A,GRCh38,WGS,41.4,97.02,TIER3
+HLT013_000987,EUR,Male,80,COHORT_A,GRCh38,WGS,52.8,91.09,TIER1
+HLT013_000988,EUR,Male,83,COHORT_A,GRCh38,WGS,55.4,91.55,TIER1
+HLT013_000989,EUR,Female,32,COHORT_A,GRCh38,WES,32.9,97.03,TIER2
+HLT013_000990,EAS,Male,24,COHORT_A,GRCh38,WES,35.6,97.07,TIER2
+HLT013_000991,EAS,Female,71,COHORT_C,GRCh38,WGS,46.1,89.71,TIER3
+HLT013_000992,EAS,Male,56,COHORT_B,GRCh38,WES,32.3,88.35,TIER2
+HLT013_000993,EAS,Male,27,COHORT_A,GRCh38,WES,36.1,94.51,TIER2
+HLT013_000994,EUR,Male,59,COHORT_B,GRCh38,WES,41.3,88.49,TIER1
+HLT013_000995,SAS,Female,69,COHORT_B,GRCh38,WGS,47.0,96.67,TIER1
+HLT013_000996,AFR,Male,67,COHORT_A,GRCh38,WES,37.2,92.52,TIER1
+HLT013_000997,EAS,Male,55,COHORT_B,GRCh38,WES,32.0,91.49,TIER3
+HLT013_000998,EUR,Female,24,COHORT_C,GRCh38,WGS,31.6,98.9,TIER3
+HLT013_000999,SAS,Male,87,COHORT_B,GRCh38,WGS,26.0,94.25,TIER1
+HLT013_001000,EUR,Female,26,COHORT_B,GRCh38,WGS,32.7,96.67,TIER3

gene_expression.csv ADDED Viewed

The diff for this file is too large to render. See raw diff

metadata.json ADDED Viewed

	@@ -0,0 +1,35 @@

+{
+  "sku": "HLT013",
+  "product": "Synthetic Genomics Dataset",
+  "version": "1.0",
+  "generated_at": "2026-05-17T20:04:15.628234",
+  "seed": 42,
+  "n_individuals": 1000,
+  "genome_build": "GRCh38/hg38",
+  "ancestry_dist": {
+    "AFR": 201.0,
+    "AMR": 119.0,
+    "EAS": 200.0,
+    "EUR": 402.0,
+    "SAS": 78.0
+  },
+  "n_snps_representative": 500,
+  "n_indels_representative": 100,
+  "titv_ratio_observed": 2.311,
+  "titv_target_genome": 2.06,
+  "n_genes_expressed": 2000,
+  "n_tissues": 5,
+  "n_cell_types": 10,
+  "n_prs_traits": 50,
+  "n_pgx_genes": 25,
+  "output_files": [
+    "hlt013_cohort_manifest.csv",
+    "hlt013_variants_annotated.csv",
+    "hlt013_gene_expression.csv",
+    "hlt013_scrna_pbmc.csv",
+    "hlt013_polygenic_risk_scores.csv",
+    "hlt013_pharmacogenomics.csv"
+  ],
+  "generation_time_sec": 1.11,
+  "generator": "XpertSystems.ai HLT013 v1.0"
+}

pharmacogenomics.csv ADDED Viewed

The diff for this file is too large to render. See raw diff

polygenic_risk_scores.csv ADDED Viewed

The diff for this file is too large to render. See raw diff

scrna_pbmc.csv ADDED Viewed

The diff for this file is too large to render. See raw diff

variants_annotated.csv ADDED Viewed

	@@ -0,0 +1,601 @@

+CHROM,POS,RSID,REF,ALT,GT,GQ,DP,AF_gnomAD,consequence,CADD_phred,ClinVar_sig,HWE_pval,variant_type
+1,10981173,rs110981173,C,T,0/0,27,26,0.0778,intron_variant,0.0,Benign,0.6191,SNP
+1,16388945,rs116388945,T,C,0/1,23,17,0.212,intron_variant,2.55,Benign,0.0411,SNP
+1,19064155,rs119064155,G,A,0/0,21,68,0.3102,intron_variant,2.96,Benign,0.4623,SNP
+1,23488511,rs123488511,C,T,1/1,33,18,0.4665,intergenic_variant,0.14,Benign,0.5227,SNP
+1,32993831,rs132993831,G,T,0/1,46,40,0.4904,intergenic_variant,1.84,Benign,0.2151,SNP
+1,43719676,rs143719676,G,A,0/0,49,60,0.0358,intron_variant,2.63,Benign,0.1405,SNP
+1,44946680,rs144946680,C,T,0/1,52,79,0.0699,intergenic_variant,0.18,Likely_benign,0.1893,SNP
+1,69870669,rs169870669,C,G,1/1,33,70,0.3956,intron_variant,0.0,Likely_benign,0.3448,SNP
+1,72823862,rs172823862,T,G,0/0,26,23,0.136,intron_variant,0.0,Benign,0.0977,SNP
+1,76001928,rs176001928,G,A,0/1,21,79,0.4425,intergenic_variant,1.13,Benign,0.9474,SNP
+1,76106099,rs176106099,A,G,0/1,25,57,0.3321,intergenic_variant,1.49,Benign,0.4056,SNP
+1,80136902,rs180136902,G,A,0/0,22,26,0.0568,intergenic_variant,0.0,Likely_benign,0.8092,SNP
+1,85978048,rs185978048,G,T,0/1,54,44,0.4164,synonymous_variant,2.19,Benign,0.9744,SNP
+1,98428870,rs198428870,G,A,0/0,30,74,0.089,intron_variant,2.64,Likely_benign,0.0817,SNP
+1,99567925,rs199567925,G,T,0/0,52,40,0.2123,intergenic_variant,1.93,Benign,0.652,SNP
+1,103638350,rs1103638350,T,C,0/0,42,26,0.2765,synonymous_variant,7.53,Benign,0.8715,SNP
+1,108627683,rs1108627683,C,A,0/1,41,71,0.2509,intergenic_variant,2.92,Benign,0.6346,SNP
+1,112489312,rs1112489312,C,T,0/1,38,76,0.3434,intergenic_variant,0.0,Benign,0.4296,SNP
+1,113291426,rs1113291426,A,G,1/1,52,78,0.3267,missense_variant,32.04,Likely_benign,0.4316,SNP
+1,114629016,rs1114629016,G,T,0/1,21,77,0.496,intergenic_variant,0.2,Benign,0.0369,SNP
+1,115332564,rs1115332564,C,T,0/0,23,71,0.4997,intergenic_variant,2.57,Benign,0.5351,SNP
+1,118229822,rs1118229822,C,T,0/0,36,44,0.2587,intron_variant,1.64,VUS,0.9935,SNP
+1,124169403,rs1124169403,G,A,0/0,35,27,0.0485,intergenic_variant,0.38,VUS,0.9587,SNP
+1,131316747,rs1131316747,C,T,1/1,41,55,0.3642,intron_variant,0.0,Likely_benign,0.0414,SNP
+1,132767467,rs1132767467,C,T,0/0,49,29,0.4884,intergenic_variant,0.74,Benign,0.7061,SNP
+1,138812455,rs1138812455,C,T,0/0,43,45,0.1598,intergenic_variant,0.0,Benign,0.3025,SNP
+1,145722700,rs1145722700,C,G,0/1,30,57,0.2311,intergenic_variant,2.45,Likely_benign,0.9031,SNP
+1,149698314,rs1149698314,A,C,1/1,33,76,0.213,intergenic_variant,3.28,Benign,0.0461,SNP
+1,153225194,rs1153225194,T,G,0/0,50,33,0.0267,intergenic_variant,0.0,Benign,0.9359,SNP
+1,157778583,rs1157778583,A,T,0/0,28,31,0.3365,intergenic_variant,1.45,Likely_benign,0.8376,SNP
+1,161591809,rs1161591809,C,G,0/0,40,62,0.1773,intron_variant,0.05,Benign,0.1184,SNP
+1,164213076,rs1164213076,G,A,0/0,41,15,0.3939,intergenic_variant,0.06,Benign,0.0608,SNP
+1,164639163,rs1164639163,A,G,0/0,50,51,0.4162,intergenic_variant,2.16,Likely_pathogenic,0.8349,SNP
+1,164650176,rs1164650176,G,A,0/1,48,63,0.4108,intergenic_variant,0.94,Benign,0.1566,SNP
+1,169137777,rs1169137777,G,A,0/1,38,50,0.2089,intergenic_variant,3.61,Benign,0.5354,SNP
+1,179420690,rs1179420690,G,A,0/0,32,39,0.1615,intergenic_variant,0.28,Benign,0.9158,SNP
+1,181061026,rs1181061026,C,T,0/1,34,68,0.3747,intron_variant,3.5,Benign,0.5679,SNP
+1,186075364,rs1186075364,A,G,0/0,36,39,0.4009,intergenic_variant,1.15,Benign,0.3978,SNP
+1,186872750,rs1186872750,T,C,0/1,28,61,0.2461,synonymous_variant,4.89,Likely_benign,0.4456,SNP
+1,187204726,rs1187204726,C,T,0/1,45,45,0.4466,missense_variant,10.73,Likely_benign,0.0641,SNP
+1,196299261,rs1196299261,T,A,0/1,28,16,0.0728,intergenic_variant,0.93,Benign,0.9688,SNP
+1,198839309,rs1198839309,A,G,1/1,45,49,0.4397,intergenic_variant,0.83,Benign,0.3113,SNP
+1,210773007,rs1210773007,A,G,0/0,50,18,0.049,intergenic_variant,0.0,Likely_benign,0.1902,SNP
+1,218738102,rs1218738102,T,C,0/0,58,75,0.0776,intron_variant,2.82,Benign,0.2868,SNP
+1,222298054,rs1222298054,T,G,0/0,24,54,0.2674,intergenic_variant,1.98,Benign,0.9644,SNP
+1,229579235,rs1229579235,T,A,0/0,50,39,0.0347,intron_variant,2.69,Benign,0.0952,SNP
+1,236573749,rs1236573749,T,A,0/0,23,46,0.0274,intron_variant,4.57,Benign,0.8674,SNP
+1,245530538,rs1245530538,A,G,0/0,33,55,0.0013,intron_variant,4.4,Benign,0.7081,SNP
+1,245973768,rs1245973768,T,C,0/1,27,31,0.2187,intron_variant,0.75,Benign,0.8302,SNP
+1,246925092,rs1246925092,G,C,0/1,26,33,0.3875,stop_gained,37.27,Benign,0.9759,SNP
+2,5295393,rs205295393,C,G,1/1,51,45,0.2845,intron_variant,0.0,Likely_benign,0.6024,SNP
+2,8804849,rs208804849,C,G,0/1,55,30,0.2765,intron_variant,0.0,Benign,0.7378,SNP
+2,13604483,rs213604483,T,C,0/1,40,33,0.4185,intergenic_variant,0.19,Benign,0.0728,SNP
+2,17569874,rs217569874,C,A,0/0,49,27,0.0552,intron_variant,3.96,Benign,0.5162,SNP
+2,25545809,rs225545809,C,T,0/0,52,66,0.1134,missense_variant,8.8,Benign,0.4821,SNP
+2,27608789,rs227608789,G,A,0/1,50,28,0.3967,intron_variant,2.78,Benign,0.9218,SNP
+2,41192226,rs241192226,A,G,0/1,23,73,0.4241,intergenic_variant,0.19,Benign,0.494,SNP
+2,42873155,rs242873155,T,C,0/1,25,50,0.4974,synonymous_variant,2.97,Benign,0.4689,SNP
+2,44193548,rs244193548,T,G,0/1,35,67,0.4366,intron_variant,1.22,Likely_benign,0.9622,SNP
+2,46328608,rs246328608,G,T,0/1,33,56,0.4451,intron_variant,3.25,Benign,0.4511,SNP
+2,47591899,rs247591899,G,A,0/1,49,32,0.1579,intron_variant,0.43,Benign,0.1817,SNP
+2,57526073,rs257526073,G,A,0/0,26,54,0.2014,intron_variant,0.0,Benign,0.2177,SNP
+2,57694145,rs257694145,T,C,0/0,34,32,0.1348,intergenic_variant,0.0,Likely_benign,0.0961,SNP
+2,60644902,rs260644902,T,C,0/0,29,22,0.3035,intergenic_variant,0.2,Benign,0.0016,SNP
+2,69662367,rs269662367,C,T,0/0,27,31,0.4695,intergenic_variant,0.0,Benign,0.4325,SNP
+2,80528084,rs280528084,C,T,0/1,26,32,0.173,intron_variant,2.32,Likely_benign,0.7695,SNP
+2,104808465,rs2104808465,G,A,0/0,27,23,0.2789,intron_variant,0.57,Benign,0.7337,SNP
+2,105579603,rs2105579603,A,G,0/0,42,16,0.1489,intron_variant,6.25,Likely_benign,0.0331,SNP
+2,105889642,rs2105889642,T,A,0/0,36,76,0.0857,intergenic_variant,0.0,Benign,0.5704,SNP
+2,108801471,rs2108801471,T,C,0/0,37,48,0.0984,intron_variant,1.91,Benign,0.1551,SNP
+2,109274508,rs2109274508,G,C,0/0,39,41,0.0299,synonymous_variant,0.0,Benign,0.9411,SNP
+2,119509924,rs2119509924,C,A,0/1,49,75,0.4747,intergenic_variant,0.26,VUS,0.1682,SNP
+2,121576400,rs2121576400,C,T,0/0,54,29,0.202,intron_variant,1.78,Benign,0.627,SNP
+2,124394943,rs2124394943,C,G,0/1,41,41,0.4172,intron_variant,0.0,Benign,0.3269,SNP
+2,127009696,rs2127009696,G,A,0/0,45,70,0.341,intron_variant,1.97,Benign,0.6419,SNP
+2,128101922,rs2128101922,T,C,0/0,49,56,0.0968,intergenic_variant,3.85,Benign,0.4128,SNP
+2,129825659,rs2129825659,G,A,0/0,47,40,0.0886,intron_variant,0.59,Benign,0.7599,SNP
+2,132684557,rs2132684557,T,C,0/1,25,31,0.4062,3_prime_UTR_variant,4.04,Benign,0.2314,SNP
+2,147007719,rs2147007719,T,C,0/0,59,17,0.1331,intron_variant,3.55,Benign,0.9059,SNP
+2,148027404,rs2148027404,G,A,1/1,26,20,0.4567,missense_variant,13.56,Benign,0.5007,SNP
+2,149248939,rs2149248939,C,A,0/0,36,25,0.0709,5_prime_UTR_variant,1.1,Benign,0.7563,SNP
+2,152543511,rs2152543511,G,A,0/1,46,66,0.3392,intergenic_variant,0.0,Benign,0.8499,SNP
+2,153852442,rs2153852442,C,T,0/1,36,56,0.4074,intron_variant,2.78,Benign,0.9988,SNP
+2,159099241,rs2159099241,G,A,0/0,29,43,0.1184,intergenic_variant,0.83,Benign,0.2247,SNP
+2,162963122,rs2162963122,T,C,0/0,56,65,0.1388,5_prime_UTR_variant,0.0,Benign,0.2876,SNP
+2,167838320,rs2167838320,C,T,1/1,22,25,0.4823,intergenic_variant,1.19,Benign,0.2512,SNP
+2,178317714,rs2178317714,G,A,0/1,29,28,0.133,intergenic_variant,0.12,Benign,0.2636,SNP
+2,179449346,rs2179449346,A,C,0/0,59,40,0.2155,synonymous_variant,0.25,Benign,0.5829,SNP
+2,180001422,rs2180001422,G,C,0/0,49,74,0.2168,intergenic_variant,1.91,Benign,0.9935,SNP
+2,182984216,rs2182984216,C,T,0/1,23,54,0.1273,intron_variant,0.0,Likely_benign,0.9903,SNP
+2,190195388,rs2190195388,C,A,0/1,50,70,0.3881,intergenic_variant,2.57,Benign,0.5272,SNP
+2,191338253,rs2191338253,G,C,0/0,58,31,0.3862,5_prime_UTR_variant,0.0,Likely_benign,0.6394,SNP
+2,201347041,rs2201347041,A,T,0/0,23,70,0.1898,synonymous_variant,0.0,Benign,0.8601,SNP
+2,204860166,rs2204860166,G,T,0/1,36,19,0.4177,intergenic_variant,3.88,Likely_benign,0.933,SNP
+2,224819619,rs2224819619,G,A,0/0,38,29,0.1073,intron_variant,3.75,Benign,0.2047,SNP
+2,229547872,rs2229547872,C,T,0/0,25,48,0.0031,intergenic_variant,1.15,Benign,0.529,SNP
+2,233253265,rs2233253265,A,G,1/1,28,18,0.286,intron_variant,0.0,Benign,0.833,SNP
+2,242336395,rs2242336395,C,T,0/1,26,70,0.497,intron_variant,0.44,VUS,0.3039,SNP
+2,244341234,rs2244341234,A,G,0/0,27,71,0.0203,intron_variant,1.65,Benign,0.4404,SNP
+2,247670741,rs2247670741,C,T,0/0,36,50,0.1048,intergenic_variant,1.06,Benign,0.9856,SNP
+3,5571771,rs305571771,T,C,0/0,35,54,0.0119,intergenic_variant,0.43,Benign,0.3397,SNP
+3,11550996,rs311550996,G,A,0/0,36,24,0.2581,intron_variant,2.15,VUS,0.7041,SNP
+3,12367427,rs312367427,A,G,0/0,35,61,0.1731,splice_region_variant,11.61,Likely_benign,0.2052,SNP
+3,12396882,rs312396882,C,T,0/1,42,42,0.2112,missense_variant,11.68,Likely_benign,0.0945,SNP
+3,21630460,rs321630460,T,G,0/0,28,61,0.051,intron_variant,2.0,Benign,0.8881,SNP
+3,26489348,rs326489348,G,C,0/0,48,59,0.3916,intron_variant,3.19,Benign,0.7644,SNP
+3,26990508,rs326990508,T,A,0/1,47,79,0.4713,intergenic_variant,1.48,Benign,0.2006,SNP
+3,35638013,rs335638013,G,A,0/0,38,46,0.0121,intron_variant,4.02,Benign,0.293,SNP
+3,41257372,rs341257372,A,T,0/0,27,37,0.3011,intron_variant,1.31,Benign,0.9721,SNP
+3,44805712,rs344805712,T,C,0/0,40,49,0.3822,intron_variant,0.84,Benign,0.7085,SNP
+3,45200956,rs345200956,T,A,0/0,46,25,0.1431,synonymous_variant,11.56,Benign,0.6109,SNP
+3,50925608,rs350925608,G,A,0/0,34,22,0.394,intergenic_variant,1.59,Benign,0.3083,SNP
+3,55948074,rs355948074,T,G,0/1,30,48,0.3165,intron_variant,0.06,Benign,0.2998,SNP
+3,56440655,rs356440655,A,G,0/0,40,68,0.4647,intron_variant,0.11,Benign,0.0405,SNP
+3,56645361,rs356645361,T,C,1/1,34,49,0.4905,intergenic_variant,0.0,Benign,0.7288,SNP
+3,61889676,rs361889676,A,T,0/0,36,65,0.0221,missense_variant,24.57,Benign,0.0441,SNP
+3,62409655,rs362409655,T,C,0/0,33,26,0.223,intergenic_variant,0.45,Benign,0.0059,SNP
+3,76825130,rs376825130,A,G,0/0,32,44,0.2739,splice_region_variant,19.02,Benign,0.7298,SNP
+3,81683466,rs381683466,G,A,0/0,48,54,0.0742,intron_variant,1.37,Benign,0.9489,SNP
+3,88333349,rs388333349,T,A,0/1,38,37,0.1688,intergenic_variant,2.1,Likely_benign,0.7567,SNP
+3,90029324,rs390029324,A,G,0/0,38,15,0.4938,intron_variant,0.0,Benign,0.4722,SNP
+3,90181567,rs390181567,A,C,0/0,46,19,0.0091,intergenic_variant,0.0,Benign,0.4866,SNP
+3,103636680,rs3103636680,T,C,0/0,34,75,0.2268,intron_variant,1.95,VUS,0.4367,SNP
+3,109105429,rs3109105429,A,C,0/1,24,54,0.4215,intron_variant,2.7,Benign,0.3253,SNP
+3,109897132,rs3109897132,G,C,0/0,54,32,0.1626,intron_variant,2.17,VUS,0.5222,SNP
+3,113793988,rs3113793988,T,C,0/0,22,31,0.2404,intron_variant,0.0,Likely_benign,0.4317,SNP
+3,118784865,rs3118784865,G,A,1/1,42,17,0.489,intergenic_variant,2.02,Benign,0.5986,SNP
+3,120523847,rs3120523847,C,G,0/0,30,76,0.238,intergenic_variant,0.0,Benign,0.8982,SNP
+3,130445626,rs3130445626,C,T,0/0,28,22,0.0663,intergenic_variant,0.22,Benign,0.995,SNP
+3,135818847,rs3135818847,G,A,0/0,21,64,0.0268,intergenic_variant,0.0,Likely_pathogenic,0.0797,SNP
+3,141694923,rs3141694923,G,C,0/1,56,30,0.4728,intergenic_variant,2.95,Benign,0.3853,SNP
+3,143617044,rs3143617044,G,A,0/1,37,36,0.1336,intergenic_variant,1.95,Benign,0.1815,SNP
+3,150618382,rs3150618382,A,G,0/1,33,32,0.2525,intergenic_variant,1.91,Benign,0.3528,SNP
+3,151902890,rs3151902890,G,A,0/0,49,68,0.0463,intergenic_variant,2.87,Benign,0.2882,SNP
+3,152353618,rs3152353618,G,A,0/0,21,17,0.2124,synonymous_variant,11.94,Likely_benign,0.1754,SNP
+3,154942693,rs3154942693,G,A,0/1,42,37,0.4651,intergenic_variant,0.0,Benign,0.7643,SNP
+3,157606180,rs3157606180,A,G,0/0,39,33,0.2517,synonymous_variant,0.0,Likely_benign,0.4968,SNP
+3,160686266,rs3160686266,G,A,0/1,42,32,0.4856,intergenic_variant,0.08,Likely_benign,0.9193,SNP
+3,173295465,rs3173295465,G,A,0/0,24,27,0.1302,intergenic_variant,0.0,Benign,0.0336,SNP
+3,177398516,rs3177398516,A,G,0/0,58,74,0.2528,intron_variant,0.0,Benign,0.0679,SNP
+3,177472028,rs3177472028,T,C,0/0,29,39,0.4299,intergenic_variant,0.55,Likely_benign,0.4039,SNP
+3,182949323,rs3182949323,G,A,0/0,47,42,0.2247,intergenic_variant,0.0,Likely_benign,0.0812,SNP
+3,184592920,rs3184592920,C,T,0/0,49,40,0.1405,intron_variant,2.17,Likely_benign,0.2635,SNP
+3,192329658,rs3192329658,G,A,0/0,33,78,0.4279,intergenic_variant,1.08,Benign,0.986,SNP
+3,193574967,rs3193574967,G,A,0/1,25,37,0.1956,intergenic_variant,1.72,Benign,0.2098,SNP
+3,201973568,rs3201973568,G,A,0/1,31,37,0.2658,intron_variant,2.52,Benign,0.1989,SNP
+3,205419128,rs3205419128,C,T,0/0,52,36,0.4883,intergenic_variant,1.9,Likely_benign,0.5741,SNP
+3,215413068,rs3215413068,T,A,0/0,56,36,0.0941,intron_variant,0.75,Benign,0.4985,SNP
+3,215424772,rs3215424772,T,C,0/1,57,20,0.1514,intergenic_variant,4.18,Benign,0.5809,SNP
+3,230529954,rs3230529954,A,G,0/0,29,54,0.0165,3_prime_UTR_variant,3.94,Benign,0.3774,SNP
+5,3136704,rs503136704,G,A,1/1,24,54,0.4796,intron_variant,3.44,VUS,0.094,SNP
+5,3711334,rs503711334,C,T,0/0,32,36,0.2017,synonymous_variant,1.8,Benign,0.8446,SNP
+5,7249728,rs507249728,T,A,0/0,40,40,0.0264,intron_variant,2.18,Likely_benign,0.1758,SNP
+5,12128364,rs512128364,C,T,1/1,20,45,0.4617,intergenic_variant,1.69,Likely_pathogenic,0.765,SNP
+5,12716024,rs512716024,G,A,1/1,37,17,0.4419,intergenic_variant,2.49,Likely_benign,0.3612,SNP
+5,18818685,rs518818685,T,C,0/1,40,62,0.2615,synonymous_variant,2.39,Benign,0.783,SNP
+5,27445089,rs527445089,G,T,0/1,33,21,0.2766,intergenic_variant,3.12,Likely_benign,0.2071,SNP
+5,29148483,rs529148483,G,C,0/0,53,44,0.1067,intergenic_variant,1.46,Benign,0.1875,SNP
+5,31728220,rs531728220,T,C,0/1,29,57,0.4099,missense_variant,21.44,Benign,0.4975,SNP
+5,38342384,rs538342384,T,C,0/1,25,20,0.2498,missense_variant,6.87,Likely_benign,0.0339,SNP
+5,47985579,rs547985579,C,T,0/1,41,79,0.0179,intergenic_variant,4.24,Benign,0.2261,SNP
+5,49872387,rs549872387,C,T,0/1,55,39,0.3418,intron_variant,2.44,Benign,0.7243,SNP
+5,51466379,rs551466379,A,G,0/0,35,16,0.4753,intergenic_variant,2.07,Benign,0.8375,SNP
+5,55902355,rs555902355,G,A,0/1,21,57,0.4147,intron_variant,0.0,Likely_benign,0.0817,SNP
+5,62311461,rs562311461,T,C,0/0,58,51,0.1393,intergenic_variant,0.0,Benign,0.8822,SNP
+5,64877894,rs564877894,C,T,0/0,37,56,0.0276,intergenic_variant,2.86,Benign,0.7977,SNP
+5,67834706,rs567834706,C,T,0/1,26,63,0.4702,intron_variant,2.07,Likely_benign,0.8698,SNP
+5,74268090,rs574268090,A,C,0/1,44,45,0.4686,intergenic_variant,0.0,Benign,0.6987,SNP
+5,76907506,rs576907506,C,T,0/0,32,68,0.2667,intron_variant,3.58,Benign,0.6745,SNP
+5,84187669,rs584187669,A,T,0/0,57,39,0.3215,intergenic_variant,0.18,Benign,0.5256,SNP
+5,86109853,rs586109853,T,C,0/0,31,50,0.2318,synonymous_variant,7.04,VUS,0.6531,SNP
+5,90067037,rs590067037,G,A,0/1,42,25,0.2105,intron_variant,1.32,Benign,0.9192,SNP
+5,97667795,rs597667795,A,G,0/0,41,55,0.0606,intron_variant,1.91,Benign,0.1014,SNP
+5,97938090,rs597938090,A,G,0/0,29,32,0.0493,intron_variant,3.86,Benign,0.3164,SNP
+5,99280747,rs599280747,T,C,0/0,39,60,0.1171,intergenic_variant,0.0,Likely_benign,0.0734,SNP
+5,109285379,rs5109285379,T,G,0/1,24,67,0.4185,intron_variant,0.0,Benign,0.9449,SNP
+5,117007356,rs5117007356,T,A,0/0,45,70,0.0738,intergenic_variant,0.71,Benign,0.4458,SNP
+5,125957675,rs5125957675,A,G,0/0,50,75,0.1141,intron_variant,3.15,Likely_pathogenic,0.6757,SNP
+5,131609766,rs5131609766,A,G,0/0,58,22,0.2748,intron_variant,0.0,Benign,0.8413,SNP
+5,138679196,rs5138679196,A,C,0/1,33,23,0.1084,synonymous_variant,0.0,Benign,0.991,SNP
+5,138833372,rs5138833372,T,A,0/0,31,75,0.0824,synonymous_variant,4.98,Benign,0.1626,SNP
+5,140148594,rs5140148594,T,C,0/1,41,39,0.2821,3_prime_UTR_variant,0.59,Likely_benign,0.7997,SNP
+5,142505772,rs5142505772,T,C,0/0,47,16,0.1847,intergenic_variant,0.41,Benign,0.8875,SNP
+5,147823136,rs5147823136,A,G,1/1,59,33,0.3135,missense_variant,0.0,Benign,0.0498,SNP
+5,148581022,rs5148581022,A,T,1/1,21,69,0.4562,intron_variant,0.14,Benign,0.7543,SNP
+5,148892392,rs5148892392,T,A,0/0,29,38,0.0763,intergenic_variant,0.99,Likely_benign,0.3554,SNP
+5,152710843,rs5152710843,T,C,0/1,30,19,0.4568,intron_variant,3.36,Likely_benign,0.6489,SNP
+5,172523593,rs5172523593,G,A,0/0,30,61,0.4513,intergenic_variant,0.0,Benign,0.5145,SNP
+5,186488998,rs5186488998,A,G,0/1,38,27,0.4147,intergenic_variant,3.49,Benign,0.2605,SNP
+5,187729354,rs5187729354,A,G,0/1,54,37,0.316,intergenic_variant,0.0,Likely_benign,0.1361,SNP
+5,188473721,rs5188473721,A,G,0/0,21,15,0.3105,intergenic_variant,0.0,Benign,0.1178,SNP
+5,190005116,rs5190005116,G,T,0/0,52,54,0.32,intron_variant,4.57,Benign,0.1042,SNP
+5,197448642,rs5197448642,T,C,0/1,44,43,0.3456,synonymous_variant,2.84,Benign,0.6382,SNP
+5,200796515,rs5200796515,G,A,0/0,44,71,0.0092,intron_variant,0.4,Benign,0.3521,SNP
+5,210355908,rs5210355908,C,T,0/1,47,36,0.4791,intron_variant,1.19,Benign,0.2174,SNP
+5,211600225,rs5211600225,T,C,0/1,24,28,0.2932,intergenic_variant,3.03,Benign,0.6922,SNP
+5,222311395,rs5222311395,A,T,0/1,49,25,0.391,intergenic_variant,3.2,Benign,0.6872,SNP
+5,241801144,rs5241801144,T,A,0/0,29,28,0.1893,intergenic_variant,0.0,Benign,0.5396,SNP
+5,245779190,rs5245779190,T,G,0/0,40,44,0.0072,intron_variant,1.42,Benign,0.935,SNP
+5,246785471,rs5246785471,G,A,0/0,47,20,0.2554,intergenic_variant,1.14,Benign,0.386,SNP
+7,2641618,rs702641618,T,C,0/1,55,35,0.0776,synonymous_variant,4.68,Benign,0.7617,SNP
+7,16920997,rs716920997,A,T,0/1,44,41,0.3886,intergenic_variant,0.0,Benign,0.9228,SNP
+7,19702476,rs719702476,T,C,0/0,53,24,0.0748,intron_variant,0.0,Benign,0.9168,SNP
+7,26849510,rs726849510,C,G,0/1,45,40,0.4568,intron_variant,2.05,Benign,0.6497,SNP
+7,48152991,rs748152991,G,A,0/0,43,32,0.2594,intron_variant,1.3,Benign,0.9283,SNP
+7,50546515,rs750546515,G,C,0/1,38,70,0.1689,intron_variant,2.64,Benign,0.4173,SNP
+7,52928839,rs752928839,C,T,0/0,29,70,0.0794,intron_variant,0.0,Benign,0.0046,SNP
+7,54231099,rs754231099,T,C,0/0,31,15,0.0069,intergenic_variant,1.54,Benign,0.0635,SNP
+7,58663013,rs758663013,A,G,0/0,49,54,0.1247,intergenic_variant,2.64,VUS,0.1104,SNP
+7,61837661,rs761837661,A,C,0/0,22,56,0.4571,intergenic_variant,1.73,Benign,0.0963,SNP
+7,68857181,rs768857181,T,C,0/0,23,39,0.3988,intron_variant,1.78,Likely_pathogenic,0.3524,SNP
+7,69744797,rs769744797,G,C,0/1,35,45,0.4849,intergenic_variant,0.86,VUS,0.7016,SNP
+7,78327313,rs778327313,T,C,0/0,50,66,0.0513,intergenic_variant,0.0,Benign,0.7909,SNP
+7,79781293,rs779781293,C,A,0/0,46,39,0.2965,synonymous_variant,1.85,Benign,0.5906,SNP
+7,80553568,rs780553568,A,G,0/0,43,19,0.1293,intergenic_variant,2.89,Benign,0.1473,SNP
+7,92891642,rs792891642,A,C,0/0,41,39,0.2719,intergenic_variant,0.82,Benign,0.7482,SNP
+7,94348013,rs794348013,C,G,0/0,24,31,0.1609,intergenic_variant,0.0,Benign,0.3554,SNP
+7,95281854,rs795281854,A,G,0/1,33,39,0.1424,intergenic_variant,0.26,Benign,0.014,SNP
+7,95402449,rs795402449,T,C,1/1,23,29,0.2873,intron_variant,1.9,Benign,0.2813,SNP
+7,100770444,rs7100770444,A,C,0/0,50,24,0.0925,intergenic_variant,0.44,Benign,0.3313,SNP
+7,103076226,rs7103076226,T,C,1/1,50,79,0.2351,intergenic_variant,1.73,Likely_pathogenic,0.275,SNP
+7,103759903,rs7103759903,A,G,0/1,30,23,0.3258,3_prime_UTR_variant,5.09,Benign,0.8121,SNP
+7,103865218,rs7103865218,A,C,0/0,31,60,0.065,intron_variant,3.28,Benign,0.7602,SNP
+7,103874935,rs7103874935,C,T,0/1,32,61,0.4654,intron_variant,4.35,Likely_pathogenic,0.6959,SNP
+7,107948137,rs7107948137,A,T,0/1,55,55,0.2534,intron_variant,3.49,Benign,0.1399,SNP
+7,108038096,rs7108038096,C,T,0/1,39,74,0.4099,synonymous_variant,0.0,Benign,0.808,SNP
+7,108364688,rs7108364688,C,T,0/1,50,15,0.3273,intergenic_variant,0.0,Likely_benign,0.6775,SNP
+7,109664014,rs7109664014,G,T,0/1,37,34,0.3553,intron_variant,1.35,Benign,0.1956,SNP
+7,114538593,rs7114538593,G,A,0/0,47,26,0.3583,intron_variant,0.6,Benign,0.6484,SNP
+7,115936314,rs7115936314,A,G,0/0,41,52,0.4377,intergenic_variant,0.0,Benign,0.484,SNP
+7,130813175,rs7130813175,A,C,0/1,31,56,0.3072,intergenic_variant,0.34,VUS,0.4399,SNP
+7,131247333,rs7131247333,A,G,0/0,55,73,0.1398,intergenic_variant,0.29,Benign,0.113,SNP
+7,133942651,rs7133942651,A,T,0/0,48,39,0.0507,intron_variant,0.16,Benign,0.5188,SNP
+7,135863142,rs7135863142,A,G,0/0,50,30,0.3035,intron_variant,0.87,Benign,0.1008,SNP
+7,146646637,rs7146646637,C,T,0/0,57,75,0.0341,intron_variant,3.86,Benign,0.1651,SNP
+7,146754222,rs7146754222,G,A,0/0,29,58,0.1214,intergenic_variant,1.3,Benign,0.1334,SNP
+7,155471202,rs7155471202,C,G,0/0,23,64,0.0313,intergenic_variant,4.71,Likely_benign,0.9542,SNP
+7,164866513,rs7164866513,C,T,0/0,43,43,0.2749,intergenic_variant,1.26,Likely_benign,0.2856,SNP
+7,170625331,rs7170625331,C,T,0/0,33,44,0.081,intron_variant,0.92,Benign,0.3558,SNP
+7,179270497,rs7179270497,G,A,0/0,37,40,0.3056,missense_variant,15.24,Benign,0.3228,SNP
+7,186419264,rs7186419264,C,T,0/0,29,63,0.3956,synonymous_variant,3.0,Benign,0.8984,SNP
+7,188959946,rs7188959946,A,G,0/1,35,28,0.4111,synonymous_variant,3.62,Benign,0.5634,SNP
+7,189058671,rs7189058671,C,G,0/0,35,78,0.1555,intron_variant,5.65,Benign,0.9192,SNP
+7,189109266,rs7189109266,A,G,0/0,34,26,0.2749,3_prime_UTR_variant,0.0,Benign,0.3006,SNP
+7,191308392,rs7191308392,C,G,0/0,49,44,0.2819,intergenic_variant,2.29,Benign,0.1157,SNP
+7,196127108,rs7196127108,T,C,1/1,43,35,0.237,intergenic_variant,1.31,Benign,0.5567,SNP
+7,203095598,rs7203095598,C,T,0/1,38,56,0.3279,intergenic_variant,0.0,Benign,0.3462,SNP
+7,220684024,rs7220684024,A,G,0/0,24,59,0.1058,intergenic_variant,2.16,Benign,0.8021,SNP
+7,238354376,rs7238354376,G,C,0/1,42,74,0.4896,intergenic_variant,2.9,Benign,0.8795,SNP
+7,243995031,rs7243995031,A,T,0/0,27,66,0.0499,intergenic_variant,0.0,VUS,0.4731,SNP
+11,4090940,rs1104090940,A,G,0/0,52,51,0.0513,intergenic_variant,0.67,Benign,0.9084,SNP
+11,7323276,rs1107323276,T,C,1/1,23,50,0.3298,3_prime_UTR_variant,7.55,Benign,0.8901,SNP
+11,12744151,rs1112744151,T,C,0/0,51,60,0.0679,intron_variant,1.54,Likely_benign,0.6798,SNP
+11,16344901,rs1116344901,C,T,0/1,30,27,0.2561,5_prime_UTR_variant,1.51,Benign,0.2412,SNP
+11,16862402,rs1116862402,A,G,0/0,38,63,0.0281,3_prime_UTR_variant,6.56,Benign,0.4204,SNP
+11,18744877,rs1118744877,T,C,0/1,38,29,0.1505,missense_variant,24.95,Benign,0.212,SNP
+11,22055490,rs1122055490,T,C,0/1,51,58,0.1168,intron_variant,4.12,Benign,0.1295,SNP
+11,22214566,rs1122214566,G,A,1/1,33,34,0.3104,intron_variant,3.25,Benign,0.3806,SNP
+11,25028678,rs1125028678,G,C,0/1,20,63,0.3936,intergenic_variant,2.62,VUS,0.5762,SNP
+11,26238489,rs1126238489,A,G,0/0,35,66,0.0296,intron_variant,2.97,Benign,0.3606,SNP
+11,29801395,rs1129801395,A,G,0/1,31,28,0.4253,intron_variant,2.03,Benign,0.6112,SNP
+11,34628459,rs1134628459,T,C,1/1,49,55,0.4305,intron_variant,1.68,Benign,0.297,SNP
+11,36154050,rs1136154050,C,T,0/0,50,47,0.1718,intron_variant,1.03,Likely_benign,0.3465,SNP
+11,48718801,rs1148718801,C,T,0/1,23,34,0.3298,intergenic_variant,0.0,Benign,0.7909,SNP
+11,52054833,rs1152054833,G,A,0/1,51,53,0.2019,intergenic_variant,0.0,Benign,0.8784,SNP
+11,62660479,rs1162660479,A,T,0/1,22,79,0.0779,intron_variant,0.94,Likely_benign,0.3227,SNP
+11,64461738,rs1164461738,A,G,0/0,44,15,0.2648,intergenic_variant,1.36,Benign,0.5719,SNP
+11,73377091,rs1173377091,A,G,0/0,35,77,0.0441,intergenic_variant,3.16,Benign,0.2789,SNP
+11,78169768,rs1178169768,C,T,0/1,32,70,0.4394,intergenic_variant,0.94,Benign,0.0543,SNP
+11,80512951,rs1180512951,C,G,1/1,39,49,0.4622,intron_variant,3.51,Benign,0.7381,SNP
+11,82023301,rs1182023301,A,C,1/1,32,54,0.411,intergenic_variant,2.62,VUS,0.1718,SNP
+11,84214217,rs1184214217,C,T,0/1,51,38,0.2817,intergenic_variant,0.65,Benign,0.4263,SNP
+11,108621918,rs11108621918,C,T,0/1,58,23,0.2792,intergenic_variant,1.89,Benign,0.4876,SNP
+11,109218288,rs11109218288,G,A,0/0,52,52,0.4923,intergenic_variant,0.63,Benign,0.1853,SNP
+11,111603684,rs11111603684,G,A,0/1,37,68,0.1247,intergenic_variant,2.98,Benign,0.0955,SNP
+11,117857676,rs11117857676,T,G,0/0,40,30,0.0389,intron_variant,2.77,Likely_benign,0.3487,SNP
+11,118806168,rs11118806168,T,A,0/1,37,61,0.2814,intron_variant,0.0,Benign,0.9523,SNP
+11,121384679,rs11121384679,C,T,0/1,51,63,0.1651,intergenic_variant,1.24,Likely_benign,0.6155,SNP
+11,132616217,rs11132616217,T,A,0/0,42,64,0.1618,intron_variant,4.8,Benign,0.382,SNP
+11,136397612,rs11136397612,G,A,0/0,38,37,0.0045,intergenic_variant,0.73,Benign,0.0399,SNP
+11,137451358,rs11137451358,A,G,0/0,36,40,0.2985,intergenic_variant,1.67,Benign,0.6007,SNP
+11,149679356,rs11149679356,C,G,0/1,35,42,0.1328,synonymous_variant,4.01,Likely_benign,0.0932,SNP
+11,150841876,rs11150841876,G,A,0/0,42,70,0.0947,intron_variant,0.0,Benign,0.543,SNP
+11,153899583,rs11153899583,T,G,0/0,47,73,0.0212,synonymous_variant,3.89,Benign,0.7522,SNP
+11,176474026,rs11176474026,C,T,0/1,37,41,0.1828,intergenic_variant,0.0,Likely_benign,0.4242,SNP
+11,179203719,rs11179203719,A,G,0/0,52,78,0.4396,intergenic_variant,0.06,Benign,0.3001,SNP
+11,183858053,rs11183858053,A,C,0/1,53,52,0.169,intergenic_variant,2.61,Benign,0.0483,SNP
+11,195892957,rs11195892957,A,T,0/0,37,40,0.3399,intergenic_variant,1.54,Benign,0.0258,SNP
+11,197276892,rs11197276892,G,C,0/0,56,15,0.3785,stop_gained,33.88,Likely_benign,0.4306,SNP
+11,198732008,rs11198732008,G,T,0/0,26,54,0.1647,intergenic_variant,1.67,Benign,0.8835,SNP
+11,199699613,rs11199699613,C,T,0/1,57,56,0.411,intron_variant,1.38,Benign,0.2448,SNP
+11,200832260,rs11200832260,G,C,0/1,31,77,0.3462,intron_variant,1.53,Benign,0.5745,SNP
+11,216239548,rs11216239548,T,C,0/1,42,61,0.2801,intron_variant,2.81,Benign,0.6846,SNP
+11,216859199,rs11216859199,T,C,0/0,31,16,0.0015,intergenic_variant,0.0,Benign,0.0618,SNP
+11,229667974,rs11229667974,A,C,0/0,37,51,0.0185,intron_variant,1.58,Benign,0.1539,SNP
+11,232439637,rs11232439637,G,T,0/1,33,63,0.4954,intergenic_variant,0.53,Benign,0.3319,SNP
+11,233311993,rs11233311993,T,G,0/0,48,47,0.3914,intron_variant,0.0,Benign,0.6704,SNP
+11,234701224,rs11234701224,T,C,1/1,23,42,0.4688,intron_variant,0.0,Likely_benign,0.4396,SNP
+11,242162355,rs11242162355,C,T,0/0,53,67,0.4512,missense_variant,30.88,Benign,0.7345,SNP
+11,248809861,rs11248809861,C,T,0/1,56,54,0.0112,intron_variant,2.27,Benign,0.8677,SNP
+17,15484220,rs1715484220,A,G,1/1,32,27,0.3104,intergenic_variant,2.19,Benign,0.9511,SNP
+17,20404823,rs1720404823,T,C,0/1,35,36,0.2341,intergenic_variant,0.0,Benign,0.7984,SNP
+17,22070035,rs1722070035,G,A,1/1,46,54,0.1859,missense_variant,0.86,Benign,0.8872,SNP
+17,22916926,rs1722916926,A,G,0/0,50,69,0.1026,intergenic_variant,0.0,Benign,0.3859,SNP
+17,26924376,rs1726924376,T,C,0/0,37,26,0.0566,intron_variant,0.0,Benign,0.9965,SNP
+17,56118518,rs1756118518,C,T,0/0,39,28,0.0608,intergenic_variant,2.13,Benign,0.1534,SNP
+17,56176993,rs1756176993,G,A,0/1,28,72,0.4995,intergenic_variant,1.53,Benign,0.5193,SNP
+17,57084987,rs1757084987,G,T,1/1,54,35,0.2067,intergenic_variant,2.65,Benign,0.4798,SNP
+17,62664376,rs1762664376,A,T,0/0,54,28,0.002,intergenic_variant,1.59,Benign,0.7986,SNP
+17,70385338,rs1770385338,A,G,1/1,26,63,0.4765,intergenic_variant,1.31,Benign,0.9087,SNP
+17,73562181,rs1773562181,G,A,0/0,33,20,0.011,intron_variant,3.9,Benign,0.7314,SNP
+17,78775720,rs1778775720,C,T,0/0,30,71,0.2099,intron_variant,2.44,Benign,0.6272,SNP
+17,82061778,rs1782061778,A,C,0/1,56,71,0.359,intergenic_variant,1.1,Likely_benign,0.428,SNP
+17,84557996,rs1784557996,A,G,0/1,22,70,0.4574,intergenic_variant,3.22,Benign,0.5108,SNP
+17,89107992,rs1789107992,T,C,1/1,28,34,0.3567,intron_variant,1.73,Benign,0.5098,SNP
+17,89384221,rs1789384221,A,T,0/1,32,22,0.2323,intergenic_variant,0.54,VUS,0.0213,SNP
+17,92830890,rs1792830890,A,G,0/0,42,42,0.4872,intergenic_variant,0.0,Benign,0.5035,SNP
+17,100360241,rs17100360241,G,A,0/0,29,36,0.0206,intergenic_variant,2.05,Benign,0.8561,SNP
+17,101147786,rs17101147786,A,G,0/0,41,77,0.4935,intergenic_variant,2.86,Benign,0.7096,SNP
+17,104746148,rs17104746148,G,A,0/1,49,56,0.4248,intergenic_variant,0.92,Benign,0.7959,SNP
+17,106492575,rs17106492575,G,A,0/0,53,76,0.4645,splice_region_variant,28.46,Benign,0.3911,SNP
+17,117319052,rs17117319052,G,A,0/0,23,63,0.1281,stop_gained,25.55,Likely_benign,0.5294,SNP
+17,119211481,rs17119211481,C,T,0/0,25,61,0.0721,5_prime_UTR_variant,3.72,Likely_benign,0.0345,SNP
+17,122821866,rs17122821866,T,G,0/1,23,22,0.332,intergenic_variant,0.94,Benign,0.3836,SNP
+17,122844791,rs17122844791,G,C,0/0,56,19,0.2584,intergenic_variant,0.0,Benign,0.4749,SNP
+17,124897438,rs17124897438,C,T,0/0,46,18,0.2621,intergenic_variant,4.58,Benign,0.256,SNP
+17,128090786,rs17128090786,A,T,0/0,41,53,0.4624,intergenic_variant,0.9,Benign,0.0322,SNP
+17,131130304,rs17131130304,C,T,0/1,51,28,0.3104,intergenic_variant,0.39,Benign,0.6907,SNP
+17,154323096,rs17154323096,A,G,0/0,43,79,0.1562,intergenic_variant,1.04,Benign,0.4357,SNP
+17,157372856,rs17157372856,A,T,0/0,29,23,0.2006,intergenic_variant,0.0,VUS,0.4163,SNP
+17,163583556,rs17163583556,C,T,0/0,40,76,0.0676,intergenic_variant,0.0,Benign,0.2507,SNP
+17,164829878,rs17164829878,A,T,0/0,48,58,0.097,intergenic_variant,2.47,Benign,0.5383,SNP
+17,165052841,rs17165052841,A,G,0/0,21,21,0.0725,intron_variant,0.24,Benign,0.4386,SNP
+17,165159451,rs17165159451,C,T,0/1,44,18,0.4053,intergenic_variant,0.0,Benign,0.4745,SNP
+17,169779913,rs17169779913,G,A,0/1,39,40,0.3527,intron_variant,4.12,VUS,0.5813,SNP
+17,169950740,rs17169950740,A,G,0/1,22,37,0.2656,intergenic_variant,3.01,Benign,0.0073,SNP
+17,175674956,rs17175674956,C,T,0/0,30,35,0.1878,intron_variant,2.53,Benign,0.9078,SNP
+17,188956195,rs17188956195,A,G,0/0,37,49,0.3346,intergenic_variant,0.32,Likely_benign,0.072,SNP
+17,196892954,rs17196892954,A,G,0/1,33,23,0.4066,intron_variant,1.02,VUS,0.4515,SNP
+17,197486892,rs17197486892,A,G,0/0,31,23,0.4407,intergenic_variant,0.0,Benign,0.2082,SNP
+17,200163157,rs17200163157,C,G,0/1,45,60,0.274,intergenic_variant,0.0,Benign,0.5243,SNP
+17,201612908,rs17201612908,G,A,0/1,36,79,0.4101,intron_variant,0.0,Likely_benign,0.2809,SNP
+17,203782711,rs17203782711,T,A,0/0,39,32,0.2561,intergenic_variant,0.07,Likely_benign,0.8601,SNP
+17,207695628,rs17207695628,G,A,0/0,51,75,0.2378,intergenic_variant,0.0,Benign,0.397,SNP
+17,208320278,rs17208320278,G,A,0/1,23,37,0.4329,missense_variant,0.0,Likely_benign,0.6391,SNP
+17,231068405,rs17231068405,T,A,0/0,34,36,0.1938,intergenic_variant,1.33,Benign,0.2496,SNP
+17,232338389,rs17232338389,C,T,0/1,22,20,0.1986,intron_variant,1.97,Benign,0.0204,SNP
+17,234047320,rs17234047320,T,G,0/0,57,42,0.1532,intron_variant,4.9,Likely_benign,0.4048,SNP
+17,239350718,rs17239350718,T,C,1/1,27,47,0.2598,intergenic_variant,0.0,Benign,0.537,SNP
+17,239492671,rs17239492671,G,A,0/1,52,58,0.2729,intergenic_variant,1.44,Benign,0.4601,SNP
+19,4494857,rs1904494857,G,T,0/0,49,53,0.4202,intergenic_variant,2.31,Benign,0.4897,SNP
+19,9122365,rs1909122365,C,T,0/0,55,32,0.4603,intergenic_variant,0.0,Benign,0.0763,SNP
+19,17653438,rs1917653438,C,G,0/0,29,65,0.0518,intergenic_variant,0.0,Likely_benign,0.6782,SNP
+19,34403082,rs1934403082,C,T,0/1,21,45,0.4699,synonymous_variant,1.64,Benign,0.7908,SNP
+19,38891030,rs1938891030,T,C,0/0,58,73,0.0347,intron_variant,0.56,Benign,0.85,SNP
+19,40218737,rs1940218737,C,T,0/0,40,53,0.2376,intergenic_variant,0.0,Benign,0.9813,SNP
+19,43616112,rs1943616112,A,T,0/1,51,50,0.4203,intron_variant,5.39,Benign,0.6723,SNP
+19,44753808,rs1944753808,T,C,0/0,32,74,0.0361,intron_variant,2.13,Benign,0.7693,SNP
+19,46061013,rs1946061013,A,T,0/0,31,45,0.0101,intron_variant,2.45,Benign,0.5063,SNP
+19,55156492,rs1955156492,G,A,0/0,29,39,0.0134,intergenic_variant,0.0,Likely_benign,0.9128,SNP
+19,64422455,rs1964422455,T,C,0/0,28,39,0.2561,intergenic_variant,2.08,Benign,0.6441,SNP
+19,77218300,rs1977218300,C,T,0/0,38,71,0.406,intergenic_variant,0.43,Benign,0.8837,SNP
+19,83932221,rs1983932221,C,A,0/0,24,64,0.0646,intergenic_variant,0.57,Benign,0.2362,SNP
+19,96291304,rs1996291304,C,T,0/0,53,25,0.0632,intergenic_variant,1.92,Benign,0.4972,SNP
+19,99546817,rs1999546817,A,T,0/0,40,47,0.2847,synonymous_variant,0.0,Likely_pathogenic,0.7301,SNP
+19,102626617,rs19102626617,A,C,0/0,56,39,0.1179,synonymous_variant,7.69,Benign,0.2035,SNP
+19,115380356,rs19115380356,A,G,0/0,40,57,0.3654,intergenic_variant,1.27,Benign,0.2121,SNP
+19,115424172,rs19115424172,C,T,1/1,32,18,0.4749,intergenic_variant,2.92,Benign,0.9781,SNP
+19,117152107,rs19117152107,G,A,1/1,40,61,0.3833,intergenic_variant,0.0,Likely_pathogenic,0.4352,SNP
+19,117313202,rs19117313202,A,G,0/0,26,63,0.4387,intergenic_variant,0.0,Benign,0.1826,SNP
+19,119097811,rs19119097811,T,C,0/0,52,29,0.2603,intron_variant,0.0,Likely_benign,0.3321,SNP
+19,121635442,rs19121635442,G,C,0/1,48,24,0.4163,intergenic_variant,1.38,Benign,0.398,SNP
+19,124790593,rs19124790593,A,G,0/1,25,55,0.0923,intron_variant,1.63,Benign,0.6235,SNP
+19,127158526,rs19127158526,T,C,0/0,43,31,0.0351,3_prime_UTR_variant,1.14,Benign,0.9231,SNP
+19,132035691,rs19132035691,A,G,0/0,41,76,0.3283,intron_variant,0.0,Benign,0.9866,SNP
+19,134152583,rs19134152583,G,C,0/0,28,65,0.0269,intron_variant,0.0,Benign,0.652,SNP
+19,139027273,rs19139027273,C,T,0/1,24,77,0.4463,intron_variant,1.4,Benign,0.7002,SNP
+19,139351607,rs19139351607,G,C,0/1,50,49,0.3461,intergenic_variant,0.3,Likely_benign,0.3225,SNP
+19,141413639,rs19141413639,T,C,1/1,30,76,0.4761,intergenic_variant,0.0,Likely_benign,0.8573,SNP
+19,150568469,rs19150568469,T,C,0/0,40,15,0.1576,intron_variant,4.59,Likely_benign,0.2186,SNP
+19,156243082,rs19156243082,C,T,0/1,29,33,0.2436,intergenic_variant,0.88,Benign,0.1073,SNP
+19,158543712,rs19158543712,G,A,0/0,46,15,0.3711,intron_variant,4.04,Benign,0.9733,SNP
+19,163487541,rs19163487541,T,C,0/0,21,59,0.1221,intergenic_variant,0.2,Likely_pathogenic,0.8643,SNP
+19,172117905,rs19172117905,G,T,0/1,34,48,0.2714,intergenic_variant,1.37,Benign,0.3043,SNP
+19,176377165,rs19176377165,T,C,0/1,41,33,0.3301,intergenic_variant,0.92,Benign,0.6755,SNP
+19,177841661,rs19177841661,C,T,0/0,37,34,0.4894,3_prime_UTR_variant,0.0,Likely_benign,0.4676,SNP
+19,182583055,rs19182583055,C,A,0/1,44,56,0.3726,intergenic_variant,3.14,Benign,0.3238,SNP
+19,185709051,rs19185709051,G,C,0/0,27,26,0.0599,intergenic_variant,0.8,Benign,0.2875,SNP
+19,186220434,rs19186220434,T,C,0/1,37,48,0.2382,intergenic_variant,2.12,Likely_benign,0.1369,SNP
+19,192669576,rs19192669576,T,C,0/0,50,54,0.2948,intron_variant,0.0,Benign,0.5498,SNP
+19,195153061,rs19195153061,G,T,0/1,33,30,0.0742,splice_region_variant,16.68,Benign,0.4472,SNP
+19,201075939,rs19201075939,G,T,0/0,26,29,0.2166,intergenic_variant,0.0,Benign,0.5127,SNP
+19,205368662,rs19205368662,G,A,0/0,53,38,0.1427,synonymous_variant,6.43,Benign,0.2161,SNP
+19,206338363,rs19206338363,C,G,0/0,51,53,0.0603,intergenic_variant,1.47,Likely_benign,0.9387,SNP
+19,216264564,rs19216264564,C,T,0/0,47,31,0.2565,intron_variant,2.23,Benign,0.639,SNP
+19,217404031,rs19217404031,C,T,0/0,51,39,0.0837,intergenic_variant,3.04,Benign,0.8997,SNP
+19,221194936,rs19221194936,T,C,0/1,51,50,0.2957,intron_variant,3.81,Likely_benign,0.1102,SNP
+19,239919084,rs19239919084,G,A,0/0,49,27,0.0857,intron_variant,3.03,Benign,0.6232,SNP
+19,243055273,rs19243055273,T,C,0/0,40,51,0.3621,intron_variant,0.0,Likely_benign,0.8496,SNP
+19,244487867,rs19244487867,A,T,0/0,20,23,0.0984,intergenic_variant,0.0,Benign,0.3316,SNP
+22,2292532,rs2202292532,T,C,1/1,56,16,0.4835,intron_variant,1.42,Benign,0.6154,SNP
+22,7018836,rs2207018836,C,T,0/1,27,50,0.4341,intron_variant,1.85,Benign,0.199,SNP
+22,12545136,rs2212545136,C,T,0/1,33,33,0.1601,intergenic_variant,0.0,Benign,0.8958,SNP
+22,20229435,rs2220229435,A,C,0/1,47,67,0.375,intron_variant,5.26,Benign,0.1909,SNP
+22,42725287,rs2242725287,T,C,0/1,53,47,0.0693,intergenic_variant,0.78,VUS,0.8846,SNP
+22,59837193,rs2259837193,C,A,0/0,55,23,0.3426,splice_acceptor_variant,36.48,Benign,0.7632,SNP
+22,61640927,rs2261640927,T,G,0/0,22,72,0.246,intergenic_variant,0.0,Benign,0.2415,SNP
+22,70559032,rs2270559032,A,G,0/0,36,33,0.0094,intergenic_variant,0.29,Likely_benign,0.1516,SNP
+22,71793788,rs2271793788,G,A,0/0,20,32,0.1378,intergenic_variant,0.0,Benign,0.3169,SNP
+22,82792695,rs2282792695,C,T,0/1,52,75,0.4777,intergenic_variant,3.2,Benign,0.3986,SNP
+22,85215845,rs2285215845,C,T,1/1,24,65,0.1586,intron_variant,0.33,Benign,0.2465,SNP
+22,85791688,rs2285791688,A,G,0/0,52,70,0.0915,intergenic_variant,2.14,Benign,0.9989,SNP
+22,85879204,rs2285879204,A,T,0/0,26,58,0.0946,intergenic_variant,0.02,Benign,0.2304,SNP
+22,87256764,rs2287256764,C,T,0/1,20,74,0.2401,intron_variant,0.59,Benign,0.8308,SNP
+22,95894700,rs2295894700,C,T,1/1,55,22,0.4215,synonymous_variant,1.24,Benign,0.16,SNP
+22,100170476,rs22100170476,T,C,1/1,37,53,0.3792,intron_variant,4.07,Benign,0.9803,SNP
+22,100235140,rs22100235140,C,T,0/0,36,34,0.219,intron_variant,0.0,Benign,0.2263,SNP
+22,105029778,rs22105029778,A,G,0/0,45,40,0.1052,intergenic_variant,0.0,Benign,0.4223,SNP
+22,105434292,rs22105434292,C,G,0/0,30,30,0.024,intergenic_variant,0.0,Likely_benign,0.559,SNP
+22,106344682,rs22106344682,G,A,0/1,47,28,0.2319,synonymous_variant,0.0,Benign,0.1212,SNP
+22,107574806,rs22107574806,C,T,0/1,37,43,0.4076,intron_variant,0.0,Benign,0.817,SNP
+22,111183443,rs22111183443,T,C,0/1,30,74,0.3651,intron_variant,0.0,Benign,0.2754,SNP
+22,113344621,rs22113344621,C,T,0/0,35,56,0.2049,synonymous_variant,0.0,Likely_benign,0.5497,SNP
+22,117942153,rs22117942153,G,C,0/0,20,37,0.2978,intergenic_variant,0.0,Benign,0.5501,SNP
+22,119536630,rs22119536630,A,G,0/0,32,43,0.2187,intron_variant,0.0,Benign,0.603,SNP
+22,119645520,rs22119645520,A,G,0/1,43,49,0.2899,intergenic_variant,2.8,Benign,0.0564,SNP
+22,131154899,rs22131154899,T,A,0/0,25,30,0.2592,intergenic_variant,1.61,Benign,0.1695,SNP
+22,166780054,rs22166780054,C,A,0/1,24,48,0.3408,intergenic_variant,1.28,Benign,0.162,SNP
+22,175324055,rs22175324055,C,T,0/1,46,60,0.2543,intergenic_variant,0.0,Benign,0.3027,SNP
+22,178747890,rs22178747890,G,A,1/1,37,30,0.4704,missense_variant,0.0,Likely_benign,0.1458,SNP
+22,181268221,rs22181268221,A,T,0/0,25,52,0.2146,intergenic_variant,0.0,Benign,0.922,SNP
+22,181659472,rs22181659472,G,A,0/0,49,61,0.0089,intron_variant,1.41,Benign,0.5134,SNP
+22,181908696,rs22181908696,C,T,0/0,51,48,0.119,intron_variant,3.24,Benign,0.624,SNP
+22,183781509,rs22183781509,A,G,0/1,21,33,0.2508,intron_variant,3.3,Benign,0.3581,SNP
+22,189464679,rs22189464679,C,T,0/0,28,51,0.2707,missense_variant,21.51,Benign,0.277,SNP
+22,190315517,rs22190315517,C,T,0/0,34,66,0.2766,intergenic_variant,0.0,Benign,0.5037,SNP
+22,192866259,rs22192866259,A,T,0/1,49,29,0.3576,intergenic_variant,1.04,VUS,0.295,SNP
+22,192992948,rs22192992948,G,A,0/0,22,52,0.138,intergenic_variant,0.52,Likely_benign,0.3443,SNP
+22,193346197,rs22193346197,G,A,0/0,52,59,0.3328,intergenic_variant,0.7,Likely_benign,0.4533,SNP
+22,196616950,rs22196616950,C,T,0/1,32,35,0.3523,synonymous_variant,9.23,Benign,0.5062,SNP
+22,198011280,rs22198011280,T,C,0/0,25,40,0.2062,intergenic_variant,0.0,Benign,0.9843,SNP
+22,212885424,rs22212885424,G,A,0/0,54,72,0.2017,intergenic_variant,0.65,Benign,0.2241,SNP
+22,213393316,rs22213393316,T,C,0/0,23,38,0.0903,intergenic_variant,2.82,Benign,0.4885,SNP
+22,217871467,rs22217871467,A,G,0/0,25,53,0.2076,intergenic_variant,0.0,Benign,0.1504,SNP
+22,221349427,rs22221349427,T,C,1/1,57,24,0.3936,intron_variant,0.21,Benign,0.3506,SNP
+22,233888342,rs22233888342,C,T,1/1,40,75,0.4546,intergenic_variant,0.21,Benign,0.7176,SNP
+22,235099405,rs22235099405,G,A,0/0,38,53,0.2972,intron_variant,1.05,Benign,0.1753,SNP
+22,243378886,rs22243378886,T,C,0/0,47,64,0.1504,intron_variant,0.0,Likely_benign,0.5818,SNP
+22,244053148,rs22244053148,C,G,0/0,45,54,0.3415,intron_variant,2.69,Benign,0.4173,SNP
+22,248190093,rs22248190093,C,T,0/1,44,38,0.3703,intergenic_variant,2.0,Benign,0.0525,SNP
+X,1923763,rsX01923763,A,G,0/1,49,23,0.0702,intergenic_variant,0.0,Benign,0.3133,SNP
+X,10539343,rsX10539343,C,A,0/0,33,40,0.1473,intergenic_variant,0.84,Likely_benign,0.6636,SNP
+X,10889891,rsX10889891,T,C,0/0,45,50,0.1537,intron_variant,0.0,Likely_benign,0.2379,SNP
+X,13497052,rsX13497052,T,A,0/0,37,17,0.1314,intron_variant,0.0,Likely_benign,0.3241,SNP
+X,14734817,rsX14734817,C,T,0/0,41,20,0.2309,intergenic_variant,2.11,VUS,0.8606,SNP
+X,16562557,rsX16562557,T,C,0/0,54,74,0.3269,intergenic_variant,0.0,Benign,0.2513,SNP
+X,20283656,rsX20283656,G,T,1/1,35,17,0.2552,intron_variant,3.24,Likely_benign,0.9644,SNP
+X,22811176,rsX22811176,A,C,0/0,46,41,0.1015,intron_variant,3.72,Benign,0.307,SNP
+X,26216725,rsX26216725,T,A,0/0,57,64,0.0524,intron_variant,0.26,Benign,0.0245,SNP
+X,37153965,rsX37153965,C,T,0/1,50,36,0.4111,intergenic_variant,1.89,Benign,0.2556,SNP
+X,57383045,rsX57383045,G,A,0/0,59,47,0.2402,synonymous_variant,0.0,Benign,0.172,SNP
+X,59072094,rsX59072094,G,T,0/0,43,20,0.032,intron_variant,0.0,Benign,0.5073,SNP
+X,65229612,rsX65229612,C,T,0/0,31,66,0.1298,intron_variant,1.75,Likely_benign,0.1136,SNP
+X,69635152,rsX69635152,G,A,0/0,59,56,0.4022,intron_variant,0.56,Benign,0.6264,SNP
+X,77477576,rsX77477576,G,A,0/1,45,70,0.3761,synonymous_variant,0.56,VUS,0.875,SNP
+X,80090558,rsX80090558,C,T,1/1,29,71,0.438,missense_variant,34.95,Benign,0.3632,SNP
+X,80925027,rsX80925027,C,T,0/0,32,37,0.3014,intron_variant,0.0,Benign,0.1693,SNP
+X,81524372,rsX81524372,G,A,0/0,30,17,0.212,intergenic_variant,1.57,Benign,0.4006,SNP
+X,83117772,rsX83117772,A,G,0/1,53,37,0.2139,intergenic_variant,0.0,Benign,0.7862,SNP
+X,85379729,rsX85379729,A,G,0/0,23,24,0.0978,intron_variant,3.32,Benign,0.5919,SNP
+X,85462430,rsX85462430,T,A,1/1,49,49,0.3257,intron_variant,2.1,Benign,0.102,SNP
+X,88867128,rsX88867128,C,T,0/0,42,24,0.2929,intergenic_variant,1.57,Benign,0.5376,SNP
+X,90261309,rsX90261309,G,A,0/0,22,74,0.0783,intergenic_variant,0.0,Benign,0.4686,SNP
+X,105155558,rsX105155558,G,A,0/0,44,54,0.4429,synonymous_variant,0.0,Likely_benign,0.3278,SNP
+X,113877288,rsX113877288,T,A,0/1,50,31,0.1849,synonymous_variant,5.35,Benign,0.1111,SNP
+X,118515031,rsX118515031,G,C,0/0,49,74,0.0258,missense_variant,32.91,Likely_benign,0.9811,SNP
+X,120846020,rsX120846020,G,A,0/0,41,65,0.1646,intergenic_variant,1.72,Likely_benign,0.1769,SNP
+X,124987190,rsX124987190,T,C,0/0,33,43,0.4351,intron_variant,0.0,Benign,0.1936,SNP
+X,131230943,rsX131230943,T,C,0/0,26,24,0.4586,intron_variant,2.18,Benign,0.1464,SNP
+X,131631606,rsX131631606,A,G,0/1,20,37,0.2457,intergenic_variant,4.64,Benign,0.5706,SNP
+X,140076850,rsX140076850,G,A,0/0,34,52,0.4782,intergenic_variant,1.15,Benign,0.4442,SNP
+X,140589015,rsX140589015,A,G,0/0,45,64,0.4377,stop_gained,42.71,Benign,0.2503,SNP
+X,145687650,rsX145687650,T,C,0/1,21,32,0.4128,intergenic_variant,0.0,VUS,0.43,SNP
+X,147177896,rsX147177896,A,G,1/1,59,63,0.43,intron_variant,1.42,Benign,0.6738,SNP
+X,155100095,rsX155100095,A,G,0/0,43,33,0.1916,intron_variant,2.74,Benign,0.2824,SNP
+X,162381568,rsX162381568,A,G,0/0,31,31,0.3785,intron_variant,2.29,Benign,0.9153,SNP
+X,164262796,rsX164262796,G,A,1/1,58,44,0.2891,intergenic_variant,0.0,Benign,0.307,SNP
+X,177864879,rsX177864879,A,G,0/1,27,25,0.3601,intron_variant,0.0,Benign,0.199,SNP
+X,185709754,rsX185709754,A,G,0/1,58,41,0.0897,intergenic_variant,2.48,Benign,0.9546,SNP
+X,191885990,rsX191885990,G,A,0/1,31,38,0.366,intron_variant,3.88,Pathogenic,0.8108,SNP
+X,193174910,rsX193174910,T,C,0/1,35,33,0.4788,intergenic_variant,3.27,Benign,0.3438,SNP
+X,208029829,rsX208029829,G,C,0/0,37,65,0.152,intron_variant,5.11,Benign,0.8416,SNP
+X,209970550,rsX209970550,C,A,0/1,59,36,0.4931,intron_variant,1.77,Benign,0.5193,SNP
+X,213411649,rsX213411649,G,A,0/1,30,60,0.1898,intergenic_variant,0.53,Benign,0.3474,SNP
+X,217839279,rsX217839279,G,C,0/0,58,61,0.1007,intergenic_variant,3.03,Likely_benign,0.8398,SNP
+X,222744767,rsX222744767,C,T,0/1,33,58,0.057,intron_variant,2.93,VUS,0.7524,SNP
+X,223145030,rsX223145030,G,A,0/1,31,32,0.3927,intergenic_variant,0.0,Likely_benign,0.2986,SNP
+X,231456997,rsX231456997,A,G,0/0,45,68,0.2779,intergenic_variant,0.0,Benign,0.6071,SNP
+X,242209289,rsX242209289,A,G,0/0,47,30,0.1543,intergenic_variant,1.74,Benign,0.37,SNP
+X,244566162,rsX244566162,G,A,0/1,33,33,0.3046,missense_variant,13.43,Likely_benign,0.0021,SNP
+10,106402260,rs10106402260,NNNNNNN,N,0/1,29,43,0.04577,frameshift_variant,24.48,Benign,0.4802,DEL
+X,132319137,rsX132319137,N,N,0/1,37,40,0.00297,inframe_insertion,30.93,Benign,0.712,INS
+14,12639854,rs1412639854,N,NNNN,0/1,54,25,0.02208,inframe_insertion,39.25,Benign,0.0781,INS
+15,110398481,rs15110398481,N,N,0/1,55,42,0.03677,inframe_insertion,36.91,Benign,0.3106,INS
+6,105054569,rs6105054569,N,N,0/1,36,45,0.0132,frameshift_variant,34.9,Benign,0.5671,DEL
+4,97687819,rs497687819,N,N,0/1,52,18,0.02179,frameshift_variant,16.4,Likely_benign,0.4505,DEL
+17,146921115,rs17146921115,N,N,1/1,51,50,0.00675,frameshift_variant,36.14,Benign,0.0252,DEL
+7,131506728,rs7131506728,N,N,0/1,43,55,0.03289,inframe_insertion,39.13,Benign,0.8702,INS
+16,90336114,rs1690336114,N,NN,0/1,59,41,0.03775,inframe_insertion,22.95,Likely_benign,0.3793,INS
+20,43807263,rs2043807263,NN,N,0/1,45,23,0.03849,frameshift_variant,41.22,Benign,0.1145,DEL
+6,133001481,rs6133001481,N,N,1/1,43,17,0.0412,inframe_insertion,13.4,Benign,0.761,INS
+16,133468723,rs16133468723,N,N,0/1,44,42,0.03864,inframe_insertion,29.27,Likely_pathogenic,0.6892,INS
+15,26723324,rs1526723324,N,N,0/1,58,19,0.03819,inframe_insertion,12.25,Benign,0.8899,INS
+X,198711103,rsX198711103,N,N,0/1,43,54,0.03407,frameshift_variant,41.35,Benign,0.9528,DEL
+21,152347312,rs21152347312,N,N,0/1,32,55,0.03404,inframe_insertion,12.37,Benign,0.9544,INS
+10,240256666,rs10240256666,NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN,N,0/1,33,48,0.00439,frameshift_variant,31.33,Benign,0.4983,DEL
+10,60202368,rs1060202368,N,N,0/1,33,56,0.02355,inframe_insertion,24.47,Benign,0.6201,INS
+15,87835168,rs1587835168,NNNNNNNNNNNNN,N,0/1,34,16,0.03542,frameshift_variant,29.21,Likely_benign,0.0967,DEL
+9,246894966,rs9246894966,N,NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN,0/1,23,48,0.04397,inframe_insertion,38.51,Likely_benign,0.4684,INS
+18,203537517,rs18203537517,NNNN,N,0/1,24,43,0.02602,frameshift_variant,41.75,Benign,0.4022,DEL
+21,103241156,rs21103241156,N,NN,0/1,50,52,0.00322,inframe_insertion,36.42,Benign,0.0839,INS
+15,168715476,rs15168715476,N,NNNN,0/1,36,24,0.0176,inframe_insertion,24.35,Benign,0.8471,INS
+12,179066792,rs12179066792,N,N,0/1,49,26,0.02632,frameshift_variant,37.71,Benign,0.3054,DEL
+19,83218087,rs1983218087,NNN,N,1/1,55,38,0.02372,frameshift_variant,16.95,Benign,0.3395,DEL
+15,67871713,rs1567871713,N,NN,1/1,55,24,0.0051,inframe_insertion,37.49,Pathogenic,0.865,INS
+3,6853258,rs306853258,N,N,0/1,46,38,0.02777,inframe_insertion,18.84,Benign,0.0404,INS
+7,160564895,rs7160564895,N,N,0/1,28,23,0.03189,inframe_insertion,20.13,Benign,0.1634,INS
+2,41907443,rs241907443,NN,N,0/1,59,27,0.01565,frameshift_variant,17.82,Likely_benign,0.9602,DEL
+9,122647462,rs9122647462,N,N,0/1,58,18,0.04833,frameshift_variant,30.6,Benign,0.8489,DEL
+13,7804262,rs1307804262,N,NNNNNN,0/1,58,17,0.04168,inframe_insertion,10.96,Benign,0.7998,INS
+19,115823167,rs19115823167,NNN,N,1/1,42,19,0.0265,frameshift_variant,19.54,Benign,0.5986,DEL
+15,198089726,rs15198089726,N,N,0/1,52,28,0.02812,frameshift_variant,15.93,Likely_benign,0.8191,DEL
+15,217730869,rs15217730869,N,N,0/1,43,26,0.01345,frameshift_variant,29.34,Benign,0.3998,DEL
+15,162934825,rs15162934825,N,NNN,0/1,38,26,0.00295,inframe_insertion,33.36,Benign,0.6555,INS
+21,86716646,rs2186716646,NN,N,0/1,28,43,0.02735,frameshift_variant,12.63,Benign,0.3158,DEL
+20,4565396,rs2004565396,N,N,0/1,28,25,0.03866,frameshift_variant,20.03,Benign,0.8012,DEL
+7,96232363,rs796232363,N,N,1/1,47,24,0.03781,inframe_insertion,22.07,Benign,0.6693,INS
+21,124714576,rs21124714576,N,N,0/1,36,32,0.04751,frameshift_variant,26.91,Benign,0.6909,DEL
+16,238954699,rs16238954699,N,N,1/1,34,51,0.02283,inframe_insertion,14.16,Benign,0.1649,INS
+12,16056708,rs1216056708,N,NN,0/1,23,53,0.03803,inframe_insertion,34.61,Benign,0.6298,INS
+13,30759005,rs1330759005,N,N,0/1,48,57,0.04895,inframe_insertion,41.26,Benign,0.8796,INS
+3,208143372,rs3208143372,NNNNNNNNNNNN,N,1/1,28,22,0.01849,frameshift_variant,25.96,Benign,0.0304,DEL
+22,246540345,rs22246540345,N,N,0/1,51,15,0.03898,frameshift_variant,44.88,Benign,0.3944,DEL
+20,98009717,rs2098009717,N,N,0/1,26,39,0.04247,frameshift_variant,17.88,Benign,0.0478,DEL
+22,34139694,rs2234139694,N,N,0/1,58,54,0.02439,frameshift_variant,17.92,Benign,0.1451,DEL
+8,227890605,rs8227890605,N,N,0/1,24,38,0.03133,frameshift_variant,22.52,Benign,0.8576,DEL
+2,48397885,rs248397885,N,N,0/1,47,51,0.02463,frameshift_variant,18.45,Benign,0.7319,DEL
+16,17389473,rs1617389473,N,N,1/1,49,31,0.00335,inframe_insertion,28.81,Benign,0.1482,INS
+13,137556907,rs13137556907,N,N,0/1,55,58,0.04899,inframe_insertion,14.52,Benign,0.6043,INS
+15,21954938,rs1521954938,N,N,0/1,22,49,0.0194,inframe_insertion,14.61,Likely_benign,0.0104,INS
+6,14817395,rs614817395,N,N,0/1,29,29,0.01232,frameshift_variant,10.19,Benign,0.1255,DEL
+3,72011583,rs372011583,N,N,1/1,46,23,0.00924,frameshift_variant,25.58,Benign,0.1651,DEL
+18,24682245,rs1824682245,N,NNN,0/1,49,29,0.04593,inframe_insertion,35.66,Likely_benign,0.7238,INS
+5,89538544,rs589538544,N,N,0/1,40,16,0.0003,frameshift_variant,42.6,Benign,0.5662,DEL
+22,85252203,rs2285252203,NNN,N,0/1,20,46,0.04905,frameshift_variant,24.87,Benign,0.4338,DEL
+19,106109360,rs19106109360,N,N,0/1,58,38,0.04059,frameshift_variant,33.12,Benign,0.7308,DEL
+1,178706275,rs1178706275,N,N,0/1,28,21,0.00982,inframe_insertion,27.01,Benign,0.4214,INS
+11,195690103,rs11195690103,N,N,0/1,36,37,0.02798,inframe_insertion,16.51,Benign,0.6806,INS
+9,98754402,rs998754402,N,N,0/1,39,48,0.01916,inframe_insertion,30.95,Benign,0.1638,INS
+16,132746836,rs16132746836,NNNN,N,0/1,56,24,0.0283,frameshift_variant,15.11,Benign,0.1223,DEL
+20,120928974,rs20120928974,N,N,1/1,58,37,0.04094,frameshift_variant,17.9,Benign,0.0843,DEL
+15,104924705,rs15104924705,NN,N,0/1,26,50,0.00844,frameshift_variant,13.19,VUS,0.9639,DEL
+9,59924214,rs959924214,NNNNNNNNN,N,0/1,35,28,0.046,frameshift_variant,32.78,Benign,0.4874,DEL
+21,177218386,rs21177218386,NNNNNNNNNNNNNN,N,0/1,29,47,0.04193,frameshift_variant,12.61,Likely_benign,0.047,DEL
+11,42687647,rs1142687647,N,NN,0/1,21,18,0.03638,inframe_insertion,17.36,Benign,0.7524,INS
+1,105305977,rs1105305977,NNNNNN,N,0/1,22,59,0.02808,frameshift_variant,27.66,VUS,0.3412,DEL
+20,92791321,rs2092791321,N,N,0/1,55,49,0.04826,inframe_insertion,17.15,Benign,0.5263,INS
+7,150161755,rs7150161755,N,NNNN,0/1,26,18,0.0355,inframe_insertion,15.49,Likely_benign,0.9525,INS
+9,220086464,rs9220086464,NNNN,N,0/1,26,54,0.03006,frameshift_variant,18.08,Benign,0.8666,DEL
+12,69684674,rs1269684674,N,NNN,0/1,24,26,0.01257,inframe_insertion,25.29,VUS,0.5141,INS
+10,115918049,rs10115918049,NNNNN,N,0/1,38,35,0.03572,frameshift_variant,40.56,VUS,0.882,DEL
+4,83425077,rs483425077,N,N,0/1,38,37,0.03447,inframe_insertion,37.04,VUS,0.7656,INS
+12,97893930,rs1297893930,N,N,1/1,37,19,0.02366,frameshift_variant,22.19,Benign,0.5249,DEL
+12,107713251,rs12107713251,NNNNNNNNNNNN,N,0/1,25,32,0.03513,frameshift_variant,40.84,Benign,0.9736,DEL
+13,80533395,rs1380533395,N,N,1/1,48,26,0.02319,frameshift_variant,34.7,Likely_benign,0.662,DEL
+7,107748915,rs7107748915,N,N,0/1,50,56,0.01016,frameshift_variant,14.78,Benign,0.3257,DEL
+X,49859752,rsX49859752,N,NNNNNNN,0/1,25,54,0.01046,inframe_insertion,10.08,Benign,0.2027,INS
+4,30105354,rs430105354,N,NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN,0/1,48,33,0.03795,inframe_insertion,25.19,VUS,0.5389,INS
+1,230911537,rs1230911537,N,NN,0/1,26,20,0.02644,inframe_insertion,33.43,Likely_benign,0.0893,INS
+8,226603953,rs8226603953,N,N,0/1,20,56,0.02214,frameshift_variant,13.82,VUS,0.6032,DEL
+10,160004696,rs10160004696,N,NN,0/1,35,48,0.04555,inframe_insertion,39.33,Likely_benign,0.2334,INS
+12,5533692,rs1205533692,N,NNNN,0/1,26,20,0.0143,inframe_insertion,27.18,Benign,0.6706,INS
+7,244338659,rs7244338659,NN,N,0/1,49,56,0.03697,frameshift_variant,35.03,Benign,0.5604,DEL
+6,101718968,rs6101718968,N,N,1/1,54,50,0.0304,inframe_insertion,44.71,Benign,0.1239,INS
+10,2821331,rs1002821331,NNNNNNN,N,0/1,21,46,0.02332,frameshift_variant,40.4,Likely_benign,0.9743,DEL
+18,182591524,rs18182591524,N,N,1/1,55,31,0.03327,frameshift_variant,39.72,Benign,0.8494,DEL
+7,23064154,rs723064154,NN,N,0/1,20,45,0.01642,frameshift_variant,30.27,Likely_benign,0.7753,DEL
+22,50131592,rs2250131592,N,NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN,0/1,21,49,0.00751,inframe_insertion,16.28,Likely_benign,0.158,INS
+19,4331184,rs1904331184,N,N,0/1,38,31,0.01106,inframe_insertion,21.99,Pathogenic,0.3097,INS
+2,67984461,rs267984461,NN,N,1/1,21,28,0.00263,frameshift_variant,25.7,Benign,0.1317,DEL
+17,234619257,rs17234619257,N,NN,0/1,43,21,0.02595,inframe_insertion,19.06,Likely_benign,0.0452,INS
+22,13766196,rs2213766196,N,NNNN,0/1,42,18,0.00402,inframe_insertion,15.6,Benign,0.8555,INS
+20,173838191,rs20173838191,NNNNNNNNNNNNN,N,0/1,25,19,0.04722,frameshift_variant,25.34,Benign,0.5795,DEL
+3,189432862,rs3189432862,N,NNNN,0/1,40,31,0.03128,inframe_insertion,25.52,Likely_benign,0.9692,INS
+10,4445191,rs1004445191,NNNNN,N,0/1,58,40,0.04834,frameshift_variant,40.23,Benign,0.2616,DEL
+1,184878538,rs1184878538,NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN,N,0/1,47,33,0.01976,frameshift_variant,10.61,Benign,0.279,DEL
+3,94612134,rs394612134,N,NNNNN,0/1,26,39,0.0006,inframe_insertion,35.03,Benign,0.5144,INS
+3,41932523,rs341932523,NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN,N,1/1,24,57,0.01342,frameshift_variant,38.3,Benign,0.0128,DEL
+6,4462836,rs604462836,N,N,0/1,37,31,0.03503,inframe_insertion,33.7,Benign,0.882,INS
+5,161276684,rs5161276684,NNNNNNN,N,0/1,43,29,0.01936,frameshift_variant,10.83,Likely_benign,0.214,DEL