ArticleEpigenetics & chromatin2020
BAMscale: quantification of next-generation sequencing peaks and generation of scaled coverage tracks.
Article in Epigenetics & chromatin, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
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Who cites it
46 citing papers in PubMed.
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- An epigenomic investigation of atrial fibrillation in a matched left and right atrial human cohort.Clinical epigenetics · 2026Article
- Topoisomerase III-beta protects from immune dysregulation and tumorigenesis.Science advances · 2025Article
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- Metastatic organotropism in small cell lung cancer.bioRxiv : the preprint server for biology · 2025Article
- G6PC2 controls glucagon secretion by defining the set point for glucose in pancreatic α cells.Science translational medicine · 2025Article
- Disrupting the RNA polymerase II transcription cycle through CDK7 inhibition ameliorates inflammatory arthritis.Science translational medicine · 2024Article
- Targeting Ovarian Cancer Stem Cells by Dual Inhibition of the Long Noncoding RNA HOTAIR and Lysine Methyltransferase EZH2.Molecular cancer therapeutics · 2024Article
- DNA cytosine methyltransferases differentially regulate genome-wide hypermutation and interhomolog recombination in Trichoderma reesei meiosis.Nucleic acids research · 2024Article
- Genome-wide Mapping of Topoisomerase Binding Sites Suggests Topoisomerase 3α (TOP3A) as a Reader of Transcription-Replication Conflicts (TRC).bioRxiv : the preprint server for biology · 2024Article
- YY1 binding is a gene-intrinsic barrier to Xist-mediated gene silencing.EMBO reports · 2024Article
- Transcription elongation defects link oncogenic SF3B1 mutations to targetable alterations in chromatin landscape.Molecular cell · 2024Article
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Authors and funding
15 authors.
Funding
Abstract
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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