Hi-C Sequencing of the A549, Human Cancer Cell Line
Epigenomics experiments have become multi-faceted, with researchers exploring chromatin structure and nucleosome states along with traditional epigenetic modifications, thereby producing large, complex multi-omic data sets. Given this shift, there is increasing demand to quickly process multiple types of sequencing data to effectively capture epigenetic alterations and associated changes in chromatin structure underlying cellular responses. Furthermore, this demand is coupled with the apparent need for a suite of bioinformatic tools that leverages high performance computing and parallelization for processing omics data from many experiments. To address these challenges, we developed and 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 structure and epigenomic assays in a high-performance computing environment. To test the completeness and compare the performance of our pipeline to other published pipelines, we generated a new Hi-C sample via the Arima Hi-C kit in the A549 human, cancer lung cell line. These cells were grown and maintained in lab conditions with no cellular perturbation. Across four fastq files, this sample was sequenced to a total of 727,353,489 pairs of reads using an Illumina paired-end library. This data has been approved for public release and assigned the LA-UR number LA-UR-25-23575. This material is based upon work supported by the U.S. Department of Energy, Office of Science, through the Biological and Environmental Research (BER) and the Advanced Scientific Computing Research (ASCR) programs under contract number 89233218CNA000001 to Los Alamos National Laboratory (Triad National Security, LLC) awarded to Christina R. Steadman and Shawn R. Starkenburg and supported by the Los Alamos National Laboratory Directed Research Grant (20210082DR) awarded to Shawn R. Starkenburg.