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Megadepth: efficient coverage quantification for BigWigs and BAMs

View ORCID ProfileChristopher Wilks, View ORCID ProfileOmar Ahmed, View ORCID ProfileDaniel N. Baker, View ORCID ProfileDavid Zhang, View ORCID ProfileLeonardo Collado-Torres, View ORCID ProfileBen Langmead
doi: https://doi.org/10.1101/2020.12.17.423317
Christopher Wilks
1Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
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  • For correspondence: langmea@cs.jhu.edu
Omar Ahmed
1Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
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Daniel N. Baker
1Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
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David Zhang
2Institute of Neurology, University College London (UCL), London, UK
3NIHR Great Ormond Street Hospital Biomedical Research Centre, University College London, London, UK
4Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London WC1E 6BT, UK
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Leonardo Collado-Torres
5Lieber Institute for Brain Development, Baltimore, MD, USA
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Ben Langmead
1Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
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  • For correspondence: langmea@cs.jhu.edu
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Abstract

Motivation A common way to summarize sequencing datasets is to quantify data lying within genes or other genomic intervals. This can be slow and can require different tools for different input file types.

Results Megadepth is a fast tool for quantifying alignments and coverage for BigWig and BAM/CRAM input files, using substantially less memory than the next-fastest competitor. Megadepth can summarize coverage within all disjoint intervals of the Gencode V35 gene annotation for more than 19,000 GTExV8 BigWig files in approximately one hour using 32 threads. Megadepth is available both as a command-line tool and as an R/Bioconductor package providing much faster quantification compared to the rtracklayer package.

Availability https://github.com/ChristopherWilks/megadepth, https://bioconductor.org/packages/megadepth.

Contact chris.wilks{at}jhu.edu

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://github.com/ChristopherWilks/megadepth

  • https://bioconductor.org/packages/megadepth

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted December 18, 2020.
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Megadepth: efficient coverage quantification for BigWigs and BAMs
Christopher Wilks, Omar Ahmed, Daniel N. Baker, David Zhang, Leonardo Collado-Torres, Ben Langmead
bioRxiv 2020.12.17.423317; doi: https://doi.org/10.1101/2020.12.17.423317
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Megadepth: efficient coverage quantification for BigWigs and BAMs
Christopher Wilks, Omar Ahmed, Daniel N. Baker, David Zhang, Leonardo Collado-Torres, Ben Langmead
bioRxiv 2020.12.17.423317; doi: https://doi.org/10.1101/2020.12.17.423317

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