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Searchlight: automated bulk RNA-seq exploration and visualisation using dynamically generated R scripts

Authors :
John J. Cole
Bekir A. Faydaci
David McGuinness
Robin Shaw
Rose A. Maciewicz
Neil A. Robertson
Carl S. Goodyear
Source :
BMC Bioinformatics, Vol 22, Iss 1, Pp 1-21 (2021)
Publication Year :
2021
Publisher :
BMC, 2021.

Abstract

Abstract Background Once bulk RNA-seq data has been processed, i.e. aligned and then expression and differential tables generated, there remains the essential process where the biology is explored, visualized and interpreted. Without the use of a visualisation and interpretation pipeline this step can be time consuming and laborious, and is often completed using R. Though commercial visualisation and interpretation pipelines are comprehensive, freely available pipelines are currently more limited. Results Here we demonstrate Searchlight, a freely available bulk RNA-seq visualisation and interpretation pipeline. Searchlight provides: a comprehensive statistical and visual analysis, focusing on the global, pathway and single gene levels; compatibility with most differential experimental designs irrespective of organism or experimental complexity, via three workflows; reports; and support for downstream user modification of plots via user-friendly R-scripts and a Shiny app. We show that Searchlight offers greater automation than current best tools (VIPER and BioJupies). We demonstrate in a timed re-analysis study, that alongside a standard bulk RNA-seq processing pipeline, Searchlight can be used to complete bulk RNA-seq projects up to the point of manuscript quality figures, in under 3 h. Conclusions Compared to a manual R based analysis or current best freely available pipelines (VIPER and BioJupies), Searchlight can reduce the time and effort needed to complete bulk RNA-seq projects to manuscript level. Searchlight is suitable for bioinformaticians, service providers and bench scientists. https://github.com/Searchlight2/Searchlight2 .

Details

Language :
English
ISSN :
14712105
Volume :
22
Issue :
1
Database :
Directory of Open Access Journals
Journal :
BMC Bioinformatics
Publication Type :
Academic Journal
Accession number :
edsdoj.9bca106272ef4240bc9afd063a856c67
Document Type :
article
Full Text :
https://doi.org/10.1186/s12859-021-04321-2