feature request? pepatac

[sunta3iouxos]

Hallo all,
I was reading the pepatac publication and I read a bit their pipeline. I find it to be the most interesting and comlete pipeline for ATAC.
Since it is very tough to get the whole pipeline to work in my/our environments, especialy with those looper/refgenie etc, I was wondering if the snakepieps team could add parts of the pipeline to the DNA-mapping and ATAC-seq pipeline.
This is just a suggetion.

[katsikora]

Hi,

I don't think we would integrate a full independent pipeline, but you could ask the authors to develop a snakemake implementation of it, if that's what works better for you.

Other than that, what are the unique features of pepatac that are not already implemented in snakePipes and that you find extremely helpful? We could consider implementing those.

Best,

Katarzyna

[sunta3iouxos]

I am not looking for complete integration.
Thsi is beyond the scope of snakePipes.
I was looking mainly to take some parts that I think they are doing better in that pipeline, for example while assessing peaks from replicates:

Aggregating results from multiple samples

To summarize and incorporate data across samples, the second step in a PEPATAC analysis is to run a project-level pipeline (pepatac_collator.py) that identifies consensus peaks across a project and calculates sample coverage of those consensus peaks in a convenient table for easy downstream analysis. To establish consensus peaks, PEPATAC identifies overlapping (1 bp, a tunable parameter: --min-olap) peaks between every sample in a project and defines the consensus peak’s coordinates based on the overlapping peak with the highest score. Peaks present in at least 2 (parameter: --cutoff) samples with a minimum score per million ≥5 (parameter: --min-score) are retained. A peak count table is then provided where every sample peak set is overlapped against the consensus peak set. Individual peak counts for an overlapping peak are weighted by multiplying by the percent overlap of the sample peak with the consensus peak.
For navigating results, PEPATAC provides both sample and project level reports in a convenient, easy-to-navigate HTML report with project-level summary table and plots, job status page and individual sample pages with sample statistics and QC plots all at your fingertips. In addition, looper will produce summary plots from individual sample statistics including the number of aligned reads, percent aligned reads, TSS scores and library complexities. A user can produce the HTML report during a run or after completion, with the job status page providing information on whether a sample has failed, is still running, or has already completed.