| --- |
| license: mit |
| task_categories: |
| - tabular-regression |
| tags: |
| - biology |
| - genomics |
| pretty_name: "gReLU tutorial 3 dataset (Microglia scATAC-seq)" |
| size_categories: |
| - 10K<n<100K |
| configs: |
| - config_name: peaks |
| data_files: |
| - split: train |
| path: "peak_file.narrowPeak" |
| - config_name: fragments |
| data_files: |
| - split: train |
| path: "fragment_file.bed" |
| --- |
| |
| # tutorial-3-data (Microglia scATAC pseudobulk) |
|
|
| ## Dataset Summary |
| This dataset contains pseudobulk scATAC-seq data for human microglia, derived from the study by Corces et al. (2020) (https://www.nature.com/articles/s41588-020-00721-x). Genome coordinates correspond to the hg38 reference genome. This data is used in tutorial 3 of gReLU (https://github.com/Genentech/gReLU/blob/main/docs/tutorials/3_train.ipynb). |
| |
| ## Dataset Structure |
| |
| The dataset is divided into two configurations: `peaks` and `fragments`. |
| |
| ### 1. Peaks Configuration (`peak_file.narrowPeak`) |
| Standard ENCODE narrowPeak format (tab-separated). |
| - `chrom`: Chromosome / Contig name. |
| - `start`: 0-based start position. |
| - `end`: End position. |
| - `name`: Peak identifier. |
| - `score`: Integer score for display. |
| - `strand`: Orientation. |
| - `signalValue`: Measurement of overall enrichment. |
| - `pValue`: Statistical significance (-log10). |
| - `qValue`: False discovery rate (-log10). |
| - `peak`: Point-source (summit) relative to start. |
|
|
| ### 2. Fragments Configuration (`fragment_file.bed`) |
| Standard BED6 format representing individual ATAC-seq fragments. |
| - `chrom`: Chromosome. |
| - `start`: Start position. |
| - `end`: End position. |
| - `source`: Sequencing run identifier (e.g., `SRR11442505`). |
| - `score`: Placeholder (0). |
| - `strand`: Orientation. |
| |
| ## Usage |
| |
| ### Loading Peaks |
| ```python |
| from datasets import load_dataset |
|
|
| dataset = load_dataset("Genentech/tutorial-3-data", "peaks", split="train", delimiter="\t") |
| dataset = load_dataset("Genentech/tutorial-3-data", "fragments", split="train", delimiter="\t") |
| ``` |
