WiggleTools: Parallel processing of large collections of genome-wide datasets for visualization and statistical analysis

99Citations
Citations of this article
148Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Motivation: Using high-throughput sequencing, researchers are now generating hundreds of whole-genome assays to measure various features such as transcription factor binding, histone marks, DNA methylation or RNA transcription. Displaying so much data generally leads to a confusing accumulation of plots. We describe here a multithreaded library that computes statistics on large numbers of datasets (Wiggle, BigWig, Bed, BigBed and BAM), generating statistical summaries within minutes with limited memory requirements, whether on the whole genome or on selected regions. © 2013 The Author 2013. Published by Oxford University Press.

Cite

CITATION STYLE

APA

Zerbino, D. R., Johnson, N., Juettemann, T., Wilder, S. P., & Flicek, P. (2014). WiggleTools: Parallel processing of large collections of genome-wide datasets for visualization and statistical analysis. Bioinformatics, 30(7), 1008–1009. https://doi.org/10.1093/bioinformatics/btt737

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free