question_id curator_name domain question_style skills_tested question internet_required gpu_preferred file_paths ensembl-grab-q1 LG Genomics Retrieval API/Web Fetching Convert all of the following to Ensembl gene IDs. Provide the ID without the Ensembl version (e.g., ENSGXXXXXXXXXXXX not ENSGXXXXXXXXXXXX.XX). Respond with semi-colon separated values, no spaces. Inputs: 1. NM_001276266.2 2. TERB2 3. ENST00000267814 4. chr15:45167214-45187966 (hg38) 5. GeneID:9153 6. NP_922946.1 7. MIM:617658 8. BEN domain containing 5, transcript variant 6. True False bam-infer-read-length-q1 SN Genomics Metadata Recovery Reasoning, Bioinformatics Tools For the given BAM file mt.sorted.bam, infer if it's paired or single ended reads and the read length. Expected output format: 1x57 False False mt.sorted.bam differential-composition-q1 SN Single-cell Synthetic/Augmented Data Bioinformatics Tools, Reasoning differential.composition.q1.1.mtx.gz and differential.composition.q1.2.mtx.gz contain raw scRNA counts matrices derived from retinal samples of two individuals (one per file, each column is a unique barcode that passes QC). differential.composition.q1.genes.txt.gz is the list of common genes. One of the cell types is severely depleted in one of the two individuals. What is this cell type? Return only the name of the depleted cell type from this list: astrocyte, microglial cell, RPE cell, cone cell, rod cell, horizontal cell, bipolar cell, RGC, T cells, macrophage, Schwann cell, Pericyte, B cell, fibroblast, endothelial cell, muller glia cell. True False differential.composition.q1.1.mtx.gz, differential.composition.q1.2.mtx.gz, differential.composition.q1.genes.txt.gz genomic-state-q1 LG Epigenomics Routine Analysis API/Web Fetching, Reasoning Consider chr11:124,738,681-124,738,772 (hg38). What is the likely purpose of this region? Choose only one. A. Active enhancer, Liver B. Active enhancer, Brain frontal lobe C. Active enhancer, ESC D. Active transcription, ubiquitous E. TSS poised or flanking, ubiquitous F. Polycomb repression, ubiquitous. Respond with a single letter. True False cryptic-exon-q1 SN Transcriptomics Synthetic/Augmented Data Coding, Reasoning, Bioinformatics Tools I have a bulk human RNA-seq fastq file cryptic.exon.q1.fq.gz. There is exactly one highly expressed coding gene that has a cryptic exon in it formed by two novel junctions. Report the HGNC gene symbol (uppercase) for that gene. True False cryptic.exon.q1.fq.gz read-paper-download-file-parse-q1 SN Epigenomics Retrieval API/Web Fetching Take a look at the pdf here: https://www.biorxiv.org/content/10.1101/2023.10.04.560808v2.full.pdf, can you find the exact number of peaks in the COC/L1 cluster? Follow any external links in the paper if additional data is required to answer this question. Respond with only the number. True False huggingface-entropy-q1 SN Machine Learning Tooling API/Web Fetching, Coding, Reasoning, ML Frameworks, Tooling Run the DNA language model here: https://huggingface.co/kuleshov-group/caduceus-ph_seqlen-131k_d_model-256_n_layer-16 on the 1000 bp long DNA sequence at hg38 chr12:7792299-7793299. Specifically, mask each base one at a time, keeping all others unmasked, and compute the per position base 2 entropy of the predictions. Return the substring corresponding to the longest run with <0.5 entropy. True True ml-model-track-overlap-q1 GE; SN Epigenomics Retrieval API/Web Fetching, Reasoning, Data Wrangling Borzoi (Linder et al., doi:10.1038/s41588-024-02053-6) and Sei (Chen et al., doi:10.1038/s41588-022-01102-2) are both DNA sequence models trained to predict genomic assay outputs. Out of the Sei tracks that are linked to a specific Cistrome ID, how many tracks share provenance with any of the tracks in Borzoi? Round your answer to the nearest 100. True False compute-gc-content-interval-q1 AL Genomics Routine Analysis API/Web Fetching, Coding "Using the GRCh38.p13 human reference genome, retrieve the reference DNA sequence for chromosome 1 from positions 1,000,000 to 1,000,100 (1-based, inclusive) on the '+' strand, and calculate: (1) gc_percent (rounded to 2 decimals), (2) length, (3) n_count (the number of Ns in the sequence), and (4) sequence_md5 (MD5 of the uppercase interval sequence). Return the results as a comma-separated string in the format: gc_percent,length,n_count,sequence_md5. For example: ""31.86,10,50,v24a827t740a77764d0d8e35ba56f612"" " True False reverse-search-gwas-q1 JR Population Genetics Metadata Recovery API/Web Fetching, Reasoning, Data Wrangling Identify the PubMed ID of the study from which this summary statistics in reverse.search.gwas.q1.tsv.gz are derived. Print only the PMID, e.g. 31510655. True False reverse.search.gwas.q1.tsv.gz pathogenic-variant-lookup-q1 SN Genomics Retrieval API/Web Fetching Using the human SHH MANE Select transcript on hg38, consider the coding sequence within exon 1. Within this interval, identify all OMIM allelic variants with phenotypes that map to single-nucleotide missense substitutions in SHH. Retrieve the AlphaMissense pathogenicity scores for those amino-acid substitutions. Return the single variant with the highest AlphaMissense score, in chr:pos (1-based) format. True False identify-donor-q1 SN Population Genetics Metadata Recovery API/Web Fetching, Reasoning, Bioinformatics Tools The pair end fastqs (identify.donor.R1.fq.gz, identify.donor.R2.fq.gz) correspond to reads from one of the 1000G donors (2504 high coverage set) from a 5Mb region of the genome. Identify the donor and report the 1000G sample ID, e.g. HG03884 True False identify.donor.R1.fq.gz, identify.donor.R2.fq.gz contaminated-rna-q3 SN Transcriptomics Synthetic/Augmented Data Bioinformatics Tools, Reasoning "You are given a single-end RNA-seq FASTQ file (contaminated.rna.q3.fq.gz). The sample is expected to be human, but it may contain reads from another organism. Determine the genus of the most likely non-human organism present, if any. Report your answer as the exact scientific genus name in all lowercase letters (for example, mus), else respond with ""none""." True False contaminated.rna.q3.fq.gz hic-differential-loop-q1 SN Epigenomics Retrieval API/Web Fetching, Visual Reasoning, Data Wrangling Consider the MicroC data for H1 and HFF cells from the following paper: https://doi.org/10.1016/j.molcel.2020.03.003. In the sub-compartment containing the NANOG gene (chr12:7629950-7809597), there is a differential loop between the two samples. Report the position of the loop (on chr12) in the following format start;end, with startT, CA548798891, VCV000587372.6, OMIM 616787.0001 on the GRCh38 reference assembly. Report in semi-colon separated chr#:position format (1-based, inclusive), no spaces (e.g. chr1:2;chr2:34). True False histone-chip-q1 SN Epigenomics Metadata Recovery Reasoning, Bioinformatics Tools I have a histone ChIP-seq ENCODE-style filtered tagAlign file (histone.chip.q1.signal.tagalign.gz) along with its control (histone.chip.q1.control.tagalign.gz), both hg38. I lost the metadata. Can you figure out the histone mark? Output exactly one label from this set: H3K4me3, H3K27ac, H3K4me1, H3K36me3, H3K27me3, H3K9me3. True False histone.chip.q1.signal.tagalign.gz, histone.chip.q1.control.tagalign.gz cell-proportions-q1 BO Single-cell Synthetic/Augmented Data Reasoning, Bioinformatics Tools I have a counts matrix of single cell transcriptomic data, cell.proportions.q1.mtx.gz. The data contains measurements from 5350 cells, each with 1000 measured genes. That data was generated by measuring data from a co-culture of a few unique cell types. Can you tell me the proportions of those cells in descending order to the nearest 5 percent? Drop any cells with questionable QC. Expected output: 35;35;20;10 if there are 4 cell types. True False cell.proportions.q1.mtx.gz three-way-barnyard-q2 SN Single-cell Synthetic/Augmented Data Bioinformatics Tools, Coding, Reasoning Given paired-end 10x scRNA-seq FASTQs (three.way.barnyard.q2.R1.fq.gz, three.way.barnyard.q2.R2.fq.gz) from a 3-species barnyard (human, mouse, pig)—R1=28-bp cell barcode+UMI, R2≈91-bp cDNA. The barcodes are pre-thresholded for minimum read depth. Report the percentages among confidently assigned single-cell barcodes for human, mouse, pig (rounded to the nearest 10%, comma-separated, summing to 100) and also assign a tissue of origin for human, mouse, pig, respectively, chosen from: liver, heart, testis, kidney, bone_marrow, spleen, cortex, retina, lung, skin. Expected output format: 40;40;20;kidney;heart;heart. True False three.way.barnyard.q2.R1.fq.gz, three.way.barnyard.q2.R2.fq.gz chip-pioneer-q1 SN Epigenomics Metadata Recovery API/Web Fetching, Reasoning, Bioinformatics Tools chip.pioneer.q1.tar contains fragment bed files obtained by aligning paired-end reads from multiple ChIP-seq experiments and their input controls using the Chromap aligner (v0.2.6, --preset chip, hg38). 6 TFs (TF1-TF6) were each separately overexpressed in BJ fibroblasts for 48 hours at comparable protein levels, and ChIP-seq was then performed. Obtain the BJ fibroblasts DNase-seq data corresponding to ENCODE accession ENCSR000EME. Using these, determine which TF showcases the most pioneering ability- which can be assumed to be reflected in the ChIP-seq signal at 48 hours. Respond with one of TF1, TF2, TF3, TF4, TF5, TF6. True False chip.pioneer.q1.tar deleterious-mutation-q2 SN Genomics Synthetic/Augmented Data Bioinformatics Tools, Data Wrangling In deleterious.mutation.q2.R1.fq.gz (exome 1×150 bp, reads from human 50Mb chunk of chr9 only), there is one gene that harbors a high-confidence nonsense SNV consistent with somatic mosaicism. The gene is highly LoF-intolerant. Report the HGNC gene symbol (uppercase) for the affected gene, and the approximate alternate allele frequency, rounded to the nearest 10%. Expected output format: POU5F1,10 True False deleterious.mutation.q2.R1.fq.gz bam-ops-q1 SN Genomics Routine Analysis Bioinformatics Tools For the given BAM file mt.sorted.bam, how many reads pass quality threshold of 30 and are properly paired? False False mt.sorted.bam perturb-seq-effect-q1 BO Single-cell Synthetic/Augmented Data Coding, Reasoning You are given the cellranger output of a CRISPR perturb-seq experiment in perturb.seq.effect.q1.tar.gz where cell features are at filtered_feature_bc_matrix/features.tsv.gz, counts are at filtered_feature_bc_matrix/matrix.mtx.gz, barcodes are at filtered_feature_bc_matrix/barcodes.tsv.gz, guide assignment per cell is at perturb_protospacer_calls_per_cell.csv, and guide reference at feature_reference.csv. I am interested in finding guides which robustly knockdown the interferon gamma pathway. We need to decide which target gene from this screen to explore in a follow up screen - which gene target should be selected? Respond with a single gene target name (i.e. CCL6). True False perturb.seq.effect.q1.tar.gz exogenous-mix-reads-q2 SN Transcriptomics Synthetic/Augmented Data Bioinformatics Tools, Reasoning I have FASTQ data from a perturbation experiment involving KLF4 exogenous overexpression using a Sendai virus. I want to estimate the fraction of exogenous-origin reads in exogenous.mix.reads.q2.mix.fq, given exogenous.mix.reads.q2.exo.fq (early timepoint, assumed purely exogenous) and exogenous.mix.reads.q2.endo.fq (later timepoint, predominantly endogenous). All files contain reads mapping to KLF4. I don't have details on the Sendai construct. If possible, estimate the percent of exogenous reads in exogenous.mix.reads.q2.mix.fq (by read count) to the nearest 10 and return only the integer (e.g. 50); if not possible, return NA. True False exogenous.mix.reads.q2.mix.fq, exogenous.mix.reads.q2.endo.fq, exogenous.mix.reads.q2.exo.fq align-one-sequence-to-reference-q1 SN Genomics Routine Analysis Bioinformatics Tools Where does CACACACAGGAGAT align to in the given GCF_000001215.4_Release_6_plus_ISO1_MT_genomic.fna? Report as 0-based coordinates in contig:start-end format (no commas). False False GCF_000001215.4_Release_6_plus_ISO1_MT_genomic.fna promoter-sequence-retrieval-q1 GE Genomics Routine Analysis API/Web Fetching, Coding Using the Ensembl GRCz11 genome assembly and Ensembl gene annotation, what is the DNA sequence of the promoter region of the zebrafish gene shha? Define the promoter as the region spanning positions −500 to +100 relative to the transcription start site (TSS) of the canonical transcript, where the TSS is position 0, negative positions are upstream, and positive positions are downstream, yielding a 601 bp sequence. Return the sequence in 5′ to 3′ orientation on the sense strand (reverse complement the genomic sequence if the gene is on the − strand). True False bedtools-chromhmm-q1 SN Epigenomics Routine Analysis Bioinformatics Tools "We wish to find the chromatin states overlapping the peaks in the given ENCODE narrowpeak bed file ENCFF333TAT.bed.gz. We have a ChromHMM annotation bed file E055_15_coreMarks_dense.bed.gz. What percentage of all bases in the peaks overlap with the 14_ReprPCWk annotation? Ignore bases in the peak file that don't have any corresponding annotation in the annotation file. Round to the nearest integer. Output format: ""42""." False False ENCFF333TAT.bed.gz, E055_15_coreMarks_dense.bed.gz lung-cancer-sc-q1 BO Single-cell Routine Analysis Coding, Reasoning, Data Wrangling You are given a single cell transcriptomic counts data generated from primary human tumor samples from patients with lung cancer (lung.cancer.sc.h5ad). This file has been cleaned for doublets and low quality cells already. Each sample is from a patient with lung adenocarcinoma (LUAD) or lung squamous cell carcinoma (LUSC). Out of samples Patient_005, Patient_006, Patient_007, Patient_018, and Patient_040, identify the LUSC sample with the highest proportion of dendritic cells out of all cells in that sample? Secondly, what percentage, to the nearest 20 percent, of all non-immune cells across all samples are malignant basal cells from LUSC patients? Expected answer format: Patient_006;20. True False lung.cancer.sc.h5ad tissue-fibroblast-q1 BO Single-cell Routine Analysis Reasoning, Coding "I have a counts matrix of transcriptomic reads from a murine multi-tissue fibroblast atlas, tissue.fibroblast.q1.rds. I want to know what tissue the fibroblast corresponding to barcode Cell_11249_MCI is from, and what tissue the fibroblast corresponding to the barcode Cell_10369_WXV is. Please provide an answer in a string format with each answer separated by a comma, and select each answer from ""Lymph node"", ""Pancreas"", ""Muscle"", ""Tendon"", ""Mesentery"", ""Omentum"" , 'Adipose"", ""Artery"", ""Bone"", ""Heart"", ""Intestine"", ""Skin"", ""Lung"", ""Liver"", or ""Spleen"". Expected output format example: Pancreas,Omentum. " True False tissue.fibroblast.q1.rds characterize-response-q1 SN Transcriptomics Metadata Recovery API/Web Fetching, Reasoning characterize.response.q1.txt contains an ordered list of differentially regulated genes in one direction (decreasing abs log-fold change, all sharing the same sign) in a specific immune cell type in response to a specific condition. Which condition, cell type pair from the following options most specifically describes this gene set. Conditions: a. stimulation by lipopolysaccharide (LPS), b. exhaustion, c. stimulation by cytokine LIF, d. stimulation by cytokine IL-39, e. COVID-19, f. sepsis, g. Med12 knockout, h. systemic lupus erythematosus, i. treatment with BMS-34554, j. treatment with aldesleukin, k. aging, l. rheumatoid arthritis. Cell types: i. monocytes, ii. CD8 T cells, iii. CD4 T cells, iv. B cells, v. dendritic cells, vi. NK cells, vii. Neutrophils. Respond in the format d;ii. True False characterize.response.q1.txt geo-lookup-read-matrix-market-q1 SN Single-cell Retrieval API/Web Fetching, Data Wrangling From the supplementary data of the GEO accession GSE242423, for the D2 scRNA-seq matrix, retrieve the counts for SOX2 for barcode AAACCCAAGTCTTCGA-1. True False annotate-variant-gene-impact-q1 GE Genomics Retrieval API/Web Fetching What is the clinical significance reported in the ClinVar database for the SPI1 variant represented by the HGVS notation NM_003120.3(SPI1):c.143-2A>C? Respond with only the correct cateogry. Answer in all lowercase. True False vcf-infer-build-q1 SN Population Genetics Metadata Recovery API/Web Fetching, Reasoning, Bioinformatics Tools You are given vcf.infer.build.q1.vcf.gz, a bgzipped VCF containing biallelic SNPs on chromosome 20 for one sample. The VCF has no rsIDs and does not specify a reference build in the header. Determine which reference genome build the VCF coordinates and REF alleles correspond to. Respond with exactly one of: hg18, hg19, hg38, T2T-CHM13. True False vcf.infer.build.q1.vcf.gz gene-pair-ordering-fraction-q1 AL Single-cell Routine Analysis Coding, Data Wrangling "From the dataset at 10x_pbmc68k_reduced.h5ad, consider only CD19+ B cells with percent_mito less than 0.04. Among these, compute the number of cells where expression of gene SRM exceeds that of gene MRPS21 by more than 1.0 (n_srm_higher), the number of cells where expression of gene MRPS21 exceeds that of gene SRM by more than 1.0 (n_mrps21_higher), and the number of cells where the difference in expression of the two genes is between 1 and -1 (inclusive) (n_within_range). Round all fractions to two decimal places. Return these numbers as a semicolon-separated string in the format n_srm_higher,n_mrps21_higher,n_within_range. An example of a correctly formatted string is: ""50;30;20""." False False 10x_pbmc68k_reduced.h5ad 1000G-retrieve-genotype-q2 SN Population Genetics Retrieval API/Web Fetching, Bioinformatics Tools, Data Wrangling "I would like to make a file with genotypes at specific loci for all individuals from the 1000G data with 3202 individuals (20201028_3202_raw_GT_with_annot). The positions should be common SNPs- snp151Common from UCSC, hg38. Select SNPs in which the observed allele column consists of exactly two distinct bases, where both alleles are strictly one of A, C, G, or T (i.e. not multi-allelic or indel). Further filter them to be within chr1 and within the 1000 genome-wide strongest peaks of the ENCODE peak file with accession ENCFF717TCQ (based on the qValue column). Create an uncompressed tsv with columns CHROM, POS, REF, ALT, and then the 3202 identifiers in lexicographic order (include header). In this tsv, the REF and ALT should come from the 1000G VCF. Keep those where both REF and ALT in 1000G are both exactly one of A,C,G,T. Convert any phased calls to unphased. Then, in the genotype cells, include only one of ""0/0"", ""0/1"", ""1/1"" or ""./."", reserving ""./."" for any that were not exactly one of the first 3. The SNPs should be sorted by coordinate. Report the total number of lines in this file along with the md5sum of this file, in the format ""201;md5sum""." True False odd-one-out-q1 SN Epigenomics Metadata Recovery Reasoning, Coding odd.one.out.q1.tar.gz contains 10 ENCODE-style tagAlign files (hg38). Each file is a different experiment performed in a unique human cell line. 9 experiments were generated using the same assay, however 1 was generated using a different assay. What is index (1-10) of this outlier? False False odd.one.out.q1.tar.gz gene-expression-query-q1 GE Transcriptomics Retrieval API/Web Fetching, Data Wrangling Retrieve the median expression level for APOE from the 'Brain_Cortex' samples in the GTEx v8 reference dataset. The value should be in Transcripts Per Million as an integer. True False afgr-1000g-intersect-atac-q1 SN Population Genetics Retrieval API/Web Fetching, Data Wrangling, Bioinformatics Tools From the 1000G Phase 3 (3202 individuals), find all individuals that also have ATAC-seq filtered BAMs in the African Functional Genomics Resource (AFGR). Using only publicly available data, collect the md5sums of the filtered BAMs for these individuals (GRCh38 aligned), write the md5sums (one per line) to a text file sorted alphabetically. Return the count of samples and the file’s md5sum as a single comma-separated line, e.g., 42,md5hash. True False borzoi-basic-q1 SN Machine Learning Tooling Tooling, Coding, API/Web Fetching, Reasoning, ML Frameworks What is the exact count of the number of parameters in any one of the replicates of the Borzoi model (https://doi.org/10.1038/s41588-024-02053-6). Specifically, report the number of trainable parameters including both the human and mouse heads. Format the number without commas. True False annotate-variant-gene-impact-q2 GE Genomics Retrieval API/Web Fetching Using the Ensembl VEP API, determine the consequence for the following variant rs2136714166. Respond with a single word. True False gene-fusion-q1 SN Transcriptomics Synthetic/Augmented Data Bioinformatics Tools, Reasoning, Coding You are given paired-end RNA sequencing FASTQ files (gene.fusion.q1.R1.fq.gz, gene.fusion.q1.R2.fq.gz) from human. The data contains a synthetic gene fusion event. Your task is to identify the fusion genes. Report the answer as the names of the two genes joined by a hyphen, with the 5′ partner first and the 3′ partner second, written in all uppercase letters, HGNC symbols. For example: TCF21-COL1A1 True False gene.fusion.q1.R1.fq.gz, gene.fusion.q1.R2.fq.gz compute-gccontent-promoter-q1 AL Genomics Routine Analysis API/Web Fetching, Coding Compute the GC content of the promoter window for the human transcript ENST00000269305 on assembly GRCh38. Use Ensembl release 115. Define the promoter interval as [TSS - upstream_bp, TSS + downstream_bp - 1] on the transcript’s strand, with upstream_bp=500 and downstream_bp=100. Report the results as a semicolon separated string in the format: chromosome,start,end,strand,promoter_length,gc_count,gc_fraction where chromosome, start, end and strand are the coordinates of the resolved promoter region, promoter_length is the length of the promoter, gc_count is the number of G or C bases in the promoter, and gc_fraction is the fraction of G/C bases in the promoter, rounded to two decimal places. All genome coordinates should be 1-based and closed. An example of a correctly formatted string is: 3;101;200;+;12;100;0.12 True False vcf-infer-ancestry-q1 SN Population Genetics Metadata Recovery Reasoning, API/Web Fetching, Bioinformatics Tools You are given vcf.infer.ancestry.q1.vcf.gz, a bgzipped VCF containing variants on chromosome 1 for four unrelated individuals: Sample1, Sample2, Sample3, Sample4. Infer each individual’s ancestry as one of: AFR (African), ASJ (Ashkenazi Jew), EUR (European), EAS (East Asian), MID (Middle Eastern), SAS (South Asian), OCE (Oceania). Output 4 labels in Sample1→Sample4 order, comma-separated with no spaces (e.g., AFR,EUR,SAS,OCE). True False vcf.infer.ancestry.q1.vcf.gz find-amplification-q1 SN Genomics Synthetic/Augmented Data Bioinformatics Tools, Reasoning, Coding You are given shallow paired-end whole-genome sequencing FASTQ files (find.amplification.R1.fq.gz, find.amplification.R2.fq.gz) simulated from a chromosome of the human genome (hg38) that contains a regional copy-number gain. Identify the approximate coordinates of the amplified region relative to the reference genome and the amplification factor, defined as the mean read-depth in the amplified region divided by the mean read-depth in flanking non-amplified regions. Report the chromosome, the start coordinate, and the end coordinate rounded to the nearest 100,000 bases, followed by a single comma and the amplification factor rounded to nearest multiple of 0.5. Format your answer as chr:start-end factor. For example: chr21:23000000-26000000,2.0 True False find.amplification.q1.R1.fq.gz, find.amplification.q1.R2.fq.gz sample-swap-atac-q1 SN Single-cell Metadata Recovery Coding, Reasoning, Data Wrangling "I have bulk ATAC-seq counts lying around from axolotl organs (sample.swap.atac.q1.tsv.gz). Since the genome is large, I broke down standard AmexG_v6.0-DD chromosomes into smaller chunks (sample.swap.atac.q1.chrom.sizes). I'm not sure, but I suspect there is a sample swap. Can you check if that is the case? If there isn't, respond ""None"". Else respond with the names of the two cell types that have been swapped in case-sensitive lexicographic order, e.g. ""Brain,GallBladder""." True False sample.swap.atac.q1.tsv.gz, sample.swap.atac.q1.chrom.sizes variant-status-q1 SN Transcriptomics Routine Analysis Reasoning, Coding, API/Web Fetching A collaborator sent me variant.status.q1.bam corresponding to a single-end RNA-seq experiment from an individual mapped to hg38. What is the likely variant status at position chrX:154,398,500 (1-based) for this individual? Respond in the format x/y, where x and y are one of A,C,G,T and x