Wilks, C;
Ahmed, O;
Baker, DN;
Zhang, D;
Collado-Torres, L;
Langmead, B;
(2021)
Megadepth: efficient coverage quantification for BigWigs and BAMs.
Bioinformatics
, 37
(18)
pp. 3014-3016.
10.1093/bioinformatics/btab152.
Preview |
Text
btab152.pdf - Published Version Download (440kB) | Preview |
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 1 h 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 and implementation https://github.com/ChristopherWilks/megadepth, https://bioconductor.org/packages/megadepth. Supplementary information Supplementary data are available at Bioinformatics online.
| Type: | Article |
|---|---|
| Title: | Megadepth: efficient coverage quantification for BigWigs and BAMs |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1093/bioinformatics/btab152 |
| Publisher version: | https://doi.org/10.1093/bioinformatics/btab152 |
| Language: | English |
| Additional information: | This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third-party material in this article are included in the Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
| Keywords: | Science & Technology, Life Sciences & Biomedicine, Technology, Physical Sciences, Biochemical Research Methods, Biotechnology & Applied Microbiology, Computer Science, Interdisciplinary Applications, Mathematical & Computational Biology, Statistics & Probability, Biochemistry & Molecular Biology, Computer Science, Mathematics, ALIGNMENT |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health > Genetics and Genomic Medicine Dept |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10141401 |
Loading...
Loading...Loading...Loading...Archive Staff Only
 |
View Item |
