Document Type

Article

Publication Date

5-1-2020

Keywords

JGM

JAX Source

Bioinformatics 2020 May 1; 36(10):3234-3235

Volume

36

Issue

10

First Page

3234

Last Page

3235

ISSN

1367-4811

PMID

32044918

DOI

https://doi.org/10.1093/bioinformatics/btaa061

Grant

Jackson Laboratory Director's Innovation Fund, HG009409,DK107967

Abstract

MOTIVATION: Modern genomic research is driven by next-generation sequencing experiments such as ChIP-seq and ChIA-PET that generate coverage files for transcription factor binding, as well as DHS and ATAC-seq that yield coverage files for chromatin accessibility. Such files are in a bedGraph text format or a bigWig binary format. Obtaining summary statistics in a given region is a fundamental task in analyzing protein binding intensity or chromatin accessibility. However, the existing Python package for operating on coverage files is not optimized for speed.

RESULTS: We developed pyBedGraph, a Python package to quickly obtain summary statistics for a given interval in a bedGraph or a bigWig file. When tested on 12 ChIP-seq, ATAC-seq, RNA-seq and ChIA-PET datasets, pyBedGraph is on average 260 times faster than the existing program pyBigWig. On average, pyBedGraph can look up the exact mean signal of 1 million regions in ∼0.26 s and can compute their approximate means in

AVAILABILITY AND IMPLEMENTATION: pyBedGraph is publicly available at https://github.com/TheJacksonLaboratory/pyBedGraph under the MIT license.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Comments

This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License.

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