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Kehr B, Melsted P. chopBAI: BAM index reduction solves I/O bottlenecks in the joint analysis of large sequencing cohorts. Bioinformatics. 2016;32(14):2202-4doi: 10.1093/bioinformatics/btw149.
Kehr, B., & Melsted, P. (2016). chopBAI: BAM index reduction solves I/O bottlenecks in the joint analysis of large sequencing cohorts. Bioinformatics (Oxford, England), 32(14), 2202-4. https://doi.org/10.1093/bioinformatics/btw149
Kehr, Birte, and Melsted, Páll. "chopBAI: BAM index reduction solves I/O bottlenecks in the joint analysis of large sequencing cohorts." Bioinformatics (Oxford, England) vol. 32,14 (2016): 2202-4. doi: https://doi.org/10.1093/bioinformatics/btw149
Kehr B, Melsted P. chopBAI: BAM index reduction solves I/O bottlenecks in the joint analysis of large sequencing cohorts. Bioinformatics. 2016 Jul 15;32(14):2202-4. doi: 10.1093/bioinformatics/btw149. Epub 2016 Mar 18. PMID: 27153590.
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Bioinformatics. 2016 Jul 15;32(14):2202-4. doi: 10.1093/bioinformatics/btw149. Epub 2016 Mar 18.

chopBAI: BAM index reduction solves I/O bottlenecks in the joint analysis of large sequencing cohorts.

Bioinformatics (Oxford, England)

Birte Kehr, Páll Melsted

Affiliations

  1. deCODE Genetics/Amgen, Reykjavík, Iceland.
  2. deCODE Genetics/Amgen, Reykjavík, Iceland Faculty of Industrial Engineering, Mechanical Engineering and Computer Science, University of Iceland, Reykjavík, Iceland.

PMID: 27153590 DOI: 10.1093/bioinformatics/btw149

Abstract

UNLABELLED: Advances in sequencing capacity have led to the generation of unprecedented amounts of genomic data. The processing of this data frequently leads to I/O bottlenecks, e. g. when analyzing a small genomic region across a large number of samples. The largest I/O burden is, however, often not imposed by the amount of data needed for the analysis but rather by index files that help retrieving this data. We have developed chopBAI, a program that can chop a BAM index (BAI) file into small pieces. The program outputs a list of BAI files each indexing a specified genomic interval. The output files are much smaller in size but maintain compatibility with existing software tools. We show how preprocessing BAI files with chopBAI can lead to a reduction of I/O by more than 95% during the analysis of 10 kb genomic regions, eventually enabling the joint analysis of more than 10 000 individuals.

AVAILABILITY AND IMPLEMENTATION: The software is implemented in C ++, GPL licensed and available at http://github.com/DecodeGenetics/chopBAIContact:[email protected].

© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: [email protected].

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