Dataset Information

Megadepth: efficient coverage quantification for BigWigs and BAMs.

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 one hour 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

https://github.com/ChristopherWilks/megadepth,https://bioconductor.org/packages/megadepth.

SUBMITTER: Wilks C

PROVIDER: S-EPMC8528031 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Megadepth: efficient coverage quantification for BigWigs and BAMs.

Wilks Christopher C Ahmed Omar O Baker Daniel N DN Zhang David D Collado-Torres Leonardo L Langmead Ben B

Bioinformatics (Oxford, England) 20210901 18

<h4>Motivation</h4>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.<h4>Results</h4>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 mo ...[more]

PMID: 33693500

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Project description:BackgroundNext-generation sequencing allows genome-wide analysis of changes in chromatin states and gene expression. Data analysis of these increasingly used methods either requires multiple analysis steps, or extensive computational time. We sought to develop a tool for rapid quantification of sequencing peaks from diverse experimental sources and an efficient method to produce coverage tracks for accurate visualization that can be intuitively displayed and interpreted by experimentalists with minimal bioinformatics background. We demonstrate its strength and usability by integrating data from several types of sequencing approaches.ResultsWe have developed BAMscale, a one-step tool that processes a wide set of sequencing datasets. To demonstrate the usefulness of BAMscale, we analyzed multiple sequencing datasets from chromatin immunoprecipitation sequencing data (ChIP-seq), chromatin state change data (assay for transposase-accessible chromatin using sequencing: ATAC-seq, DNA double-strand break mapping sequencing: END-seq), DNA replication data (Okazaki fragments sequencing: OK-seq, nascent-strand sequencing: NS-seq, single-cell replication timing sequencing: scRepli-seq) and RNA-seq data. The outputs consist of raw and normalized peak scores (multiple normalizations) in text format and scaled bigWig coverage tracks that are directly accessible to data visualization programs. BAMScale also includes a visualization module facilitating direct, on-demand quantitative peak comparisons that can be used by experimentalists. Our tool can effectively analyze large sequencing datasets (~ 100 Gb size) in minutes, outperforming currently available tools.ConclusionsBAMscale accurately quantifies and normalizes identified peaks directly from BAM files, and creates coverage tracks for visualization in genome browsers. BAMScale can be implemented for a wide set of methods for calculating coverage tracks, including ChIP-seq and ATAC-seq, as well as methods that currently require specialized, separate tools for analyses, such as splice-aware RNA-seq, END-seq and OK-seq for which no dedicated software is available. BAMscale is freely available on github (https://github.com/ncbi/BAMscale).

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Dataset Information

Megadepth: efficient coverage quantification for BigWigs and BAMs.

Motivation

Results

Availability

Publications

Megadepth: efficient coverage quantification for BigWigs and BAMs.

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