WiggleTools: parallel processing of large collections of genome-wide datasets for visualization and statistical analysis.
other · Level V
Where this comes from
- Record sourced from PubMed, PMID 24363377.
- Also identified by DOI 10.1093/bioinformatics/btt737 and PMC identifier 3967112.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
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. The code is freely available under Apache 2.0 license at www.github.com/Ensembl/Wiggletools
Medical subject headings
- Genome
- Genomics
- High-Throughput Nucleotide Sequencing