BamToCov: An efficient toolkit for sequence coverage calculations

Abstract

Motivation: Many genomics applications require the computation of nucleotide coverage of a reference genome or the ability to determine how many reads map to a reference region. Results: BamToCov is a toolkit for rapid and flexible coverage computation that relies on the most memory efficient algorithm and is designed for integration in pipelines, given its ability to read alignment files from streams. The tools in the suite can process sorted BAM or CRAM files, allowing the user to extract coverage information via different filtering approaches and to save the output in different formats (BED, Wig or counts). The BamToCov algorithm can also handle strand-specific and/or physical coverage analyses.