SLUR(M)-py: A SLURM Powered Pythonic Pipeline for Parallel Processing of 3D (Epi)genomic Profiles

Abstract

There is increasing demand to quickly process multiple types of sequencing-based data to completely capture epigenetic alterations and associated changes in chromatin structure underlying cellular responses. Furthermore, the need for a set of bioinformatic tools that leverage high performance computing and parallelization for processing omics data from many experiments has become apparent. Here we present SLUR(M)-py: a flexible command line tool (written in Python) that leverages the Simple Linux Utility for Resource Management system (SLURM) to process, align, and analyze sequencing data from three-dimensional and epigenomic assays in a high-performance computing environment. SLUR(M)-py is designed with host-pathogen infection experiments in mind, and contains unique scripts and functions that automate calls to SLURM for processing paired-end sequenced reads from chromatin characterization experiments, including whole-genome, ChIP-seq, ATAC-seq and Hi-C. ATAC-seq and Hi-C data from viral infection experiments as well as data from the ENCODE project are utilized to demonstrate processing speed, which outpace current high-performance computing pipelines. We explore the effect of dropping duplicate sequenced reads in ATAC-seq data and demonstrate how SLUR(M)-py can be used for quality control and to detect artifacts in Hi-C experiments from viral infection experiments. Finally, we utilize SLUR(M)-py to explore the dynamics of inter-chromosomal contacts in mammalian cells exposed to vaccinia virus, the vaccine for smallpox.