| | --- |
| | license: mit |
| | task_categories: |
| | - tabular-regression |
| | tags: |
| | - biology |
| | - genomics |
| | pretty_name: "gReLU tutorial 3 dataset (Microglia scATAC-seq)" |
| | size_categories: |
| | - 10K<n<100K |
| | --- |
| | |
| | # microglia-scatac-tutorial-data |
| |
|
| | ## 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 files: peaks and fragments. |
| | |
| | ### Statistics |
| | | File | Rows | Description | |
| | |------|------|-------------| |
| | | `peak_file.narrowPeak` | 83,320 | Called ATAC-seq peaks | |
| | | `fragment_file.bed` | 57,919,016 | Individual ATAC-seq fragments | |
| |
|
| | ### 1. Peaks file (`peak_file.narrowPeak`) |
| | Standard ENCODE narrowPeak format (tab-separated, no header). |
| | - `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 file (`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 |
| |
|
| | ```python |
| | from huggingface_hub import hf_hub_download |
| | import pandas as pd |
| | |
| | peak_path = hf_hub_download( |
| | repo_id="Genentech/microglia-scatac-tutorial-data", |
| | repo_type="dataset", |
| | filename="peak_file.narrowPeak" |
| | ) |
| | peaks = pd.read_csv(peak_path, sep='\t', header=None) |
| | |
| | frag_path = hf_hub_download( |
| | repo_id="Genentech/microglia-scatac-tutorial-data", |
| | repo_type="dataset", |
| | filename="fragment_file.bed" |
| | ) |
| | fragments = pd.read_csv(frag_path, sep='\t', header=None, |
| | names=['chrom', 'start', 'end', 'source', 'score', 'strand']) |
| | ``` |
| |
|
