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 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

from huggingface_hub import hf_hub_download
import grelu.io.bed
import pandas as pd

peak_path = hf_hub_download(
    repo_id="Genentech/microglia-scatac-tutorial-data",
    repo_type="dataset",
    filename="peak_file.narrowPeak"
)
peaks = grelu.io.bed.read_narrowpeak(peak_file)

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'])