DRAGoN: a robust pipeline for analyzing DRUG-seq datasets.

Motivation: Existing bioinformatics pipelines to process DRUG-seq datasets have limited flexibility and can have difficulty analyzing current datasets without requiring excessive computational time or memory.

Results: Here, we describe an alternative, DRAGoN, which is fast, robust, and performs as well as or better than competing pipelines on key benchmarks without sacrificing accuracy. This is accomplished primarily via a preliminary demultiplexing step that facilitates the parallelization of the pipeline as well as the collection of per-well statistics that assist with quality control. DRAGoN provides the user maximum flexibility with respect to filtering, alignment, counting, and downsampling, and it efficiently collapses UMIs.

Availability and implementation: DRAGoN is a Nextflow pipeline that utilizes open-source software alongside custom C++ programs and Python scripts. It is freely available at https://github.com/MSDLLCPapers/DRAGoN.