Literature DB >> 33407065

recoup: flexible and versatile signal visualization from next generation sequencing.

Panagiotis Moulos1.   

Abstract

BACKGROUND: The relentless continuing emergence of new genomic sequencing protocols and the resulting generation of ever larger datasets continue to challenge the meaningful summarization and visualization of the underlying signal generated to answer important qualitative and quantitative biological questions. As a result, the need for novel software able to reliably produce quick, comprehensive, and easily repeatable genomic signal visualizations in a user-friendly manner is rapidly re-emerging.
RESULTS: recoup is a Bioconductor package for quick, flexible, versatile, and accurate visualization of genomic coverage profiles generated from Next Generation Sequencing data. Coupled with a database of precalculated genomic regions for multiple organisms, recoup offers processing mechanisms for quick, efficient, and multi-level data interrogation with minimal effort, while at the same time creating publication-quality visualizations. Special focus is given on plot reusability, reproducibility, and real-time exploration and formatting options, operations rarely supported in similar visualization tools in a profound way. recoup was assessed using several qualitative user metrics and found to balance the tradeoff between important package features, including speed, visualization quality, overall friendliness, and the reusability of the results with minimal additional calculations.
CONCLUSION: While some existing solutions for the comprehensive visualization of NGS data signal offer satisfying results, they are often compromised regarding issues such as effortless tracking of processing and preparation steps under a common computational environment, visualization quality and user friendliness. recoup is a unique package presenting a balanced tradeoff for a combination of assessment criteria while remaining fast and friendly.

Entities:  

Keywords:  ATAC-Seq; ChIP-Seq; Genomic profiles; Next generation sequencing; RNA-Seq; Signal visualization; Transcription factors

Year:  2021        PMID: 33407065     DOI: 10.1186/s12859-020-03902-x

Source DB:  PubMed          Journal:  BMC Bioinformatics        ISSN: 1471-2105            Impact factor:   3.169


  2 in total

1.  Interactive Analysis, Exploration, and Visualization of RNA-Seq Data with SeqCVIBE.

Authors:  Efthimios Bothos; Pantelis Hatzis; Panagiotis Moulos
Journal:  Methods Protoc       Date:  2022-03-18

Review 2.  Bibliometric review of ATAC-Seq and its application in gene expression.

Authors:  Liheng Luo; Michael Gribskov; Sufang Wang
Journal:  Brief Bioinform       Date:  2022-05-13       Impact factor: 13.994

  2 in total

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