porchard/per-cluster-atac-processing

Per-cluster processing of snATAC data

This pipeline processed snATAC-data data on a per-cluster pseudobulk basis.

Dependencies

Singularity (v. 3) and NextFlow (>= v. 20.10.0). Containers with the software for each step are pulled from the Sylabs cloud library or Docker hub.

Running

To run the pipeline, you'll need to provide a config.json file like this:

{
    "libraries": {
        "Sample_3172-CV-hg19": {
            "bam": "/path/to/library.bam", # path to pruned library ATAC bam file (from snATAC pipeline)
            "clusters": "/path/to/library.clusters.txt" # two-column TSV file (no header). First column is *RNA* barcode, second column is the cluster assignment for that barcode
        }
    }
}

You'll also need to update the nextflow.config file in this directory.

Then run the pipeline:

nextflow run -resume -params-file config.json --genome hg19 --atac_barcodes /path/to/atac-barcode-whitelist.txt.gz --rna_barcodes /path/to/rna-barcode-whitelist.txt.gz --markers Myh1,Myh2,Myh4 --results /path/to/results /path/to/per-cluster-atac-processing/main.nf

Where --genome is the name of the reference genome to use, and --markers is a comma-separated list of marker genes of interest (these genes must be included in the gene_bed file).

Output

• bam/per-library-pass-qc-nuclei: Bam files subsetted to pass QC barcodes (per-library)
• bam/per-library-per-cluster: Per-library, per-cluster bam files
• bam/per-cluster: Per-cluster bam files
• bam/aggregate: Aggregate bam file (all clusters and all libraries)
• peaks/broad: MACS2 broad peak calling output
• peaks/narrow: MACS2 narrow peak calling output (including peak summits)
• peaks/summit-extension: Extended summits (default 150 bp either side; overlaps are removed, keeping the one with the highest score, as in paper: 'Epigenomic State Transitions Characterize Tumor Progression in Mouse Lung Adenocarcinoma')
• bigwig: Per-cluster bigwig files
• plot-marker-gene-signal: ATAC per-cluster marker gene plot