Bam-readcount -- rapid generation of basepair-resolution sequence metrics

Ajay Khanna; David E. Larson; Sridhar Nonavinkere Srivatsan; Matthew Mosior; Travis E. Abbott; Susanna Kiwala; Timothy J. Ley; Eric J. Duncavage; Matthew J. Walter; Jason R. Walker; Obi L. Griffith; Malachi Griffith; Christopher A. Miller

arXiv · 2107.12817

Bam-readcount -- rapid generation of basepair-resolution sequence metrics

Ajay Khanna·David E. Larson·Sridhar Nonavinkere Srivatsan·Matthew Mosior·Travis E. Abbott·Susanna Kiwala·Timothy J. Ley·Eric J. Duncavage·Matthew J. Walter·Jason R. Walker·Obi L. Griffith·Malachi Griffith·Christopher A. Miller

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Abstract

Bam-readcount is a utility for generating low-level information about sequencing data at specific nucleotide positions. Originally designed to help filter genomic mutation calls, the metrics it outputs are useful as input for variant detection tools and for resolving ambiguity between variant callers . In addition, it has found broad applicability in diverse fields including tumor evolution, single-cell genomics, climate change ecology, and tracking community spread of SARS-CoV-2. Here we report on the release of version 1.0 of this tool, which adds CRAM support, among other improvements. It is released under a permissive MIT license and available at https://github.com/genome/bam-readcount.

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Ajay Khanna, David E. Larson, Sridhar Nonavinkere Srivatsan, Matthew Mosior, Travis E. Abbott, Susanna Kiwala, Timothy J. Ley, Eric J. Duncavage, Matthew J. Walter, Jason R. Walker, Obi L. Griffith, Malachi Griffith, Christopher A. Miller. 2021-07-27. Bam-readcount -- rapid generation of basepair-resolution sequence metrics. https://arxiv.org/abs/2107.12817

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