PRJNA509779

This repository is an execution of the prepareChiPS workflow on the BioProject PRJNA509779. The SraRunTable was downloaded from the given link and converted to PRJNA509779.tsv using the following code. This file was then used to supply all parameters for the snakemake workflow.

library(readr)
library(dplyr)
here::here("config/SraRunTable.txt") %>%
	read_csv() %>%
	mutate(
		target = gsub("([^ ]+) .+", "\\1", ChIP_antibody),
		Treatment = gsub("\\+", "", Treatment),
		input = "SRR8315192"
	) %>%
	dplyr::filter(target != "Input") %>%
	dplyr::select(
		accession = Run, target, treatment = Treatment, input, 
		Cell_Line, `Sample Name`, Experiment, source_name
	) %>%
	write_tsv(
		here::here("config/PRJNA509779.tsv")
	)

Before running this on a slurm HPC cluster, be sure to include a suitable size request for the temporary directory (>10G) in your config file. If this is not set clearly, some clusters may limit the size of this directory and macs2 callpeak will appear to complete without throwing any errors, despite multiple Exceptions being thrown internally. These will be visible in the callpeak.log files.

Note for OSX Users

It should be noted that this workflow is currently incompatible with OSX-based systems. There are two incompatibilities.

1. fasterq-dump has a bug which is specific to conda environments. This has been updated in SRA tools v3.0.3 but this patch has not yet been made available to conda environments for OSX.
2. An intermittent glitch appears in OSX-based R sessions, namely

Error in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y,  : 
  polygon edge not found

The fix for this is currently undefined