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

Cole, J. J., Faydaci, B. A., Mcguinness, D. , Shaw, R., Maciewicz, R. A., Robertson, N. A. and Goodyear, C. S. (2021) Searchlight: automated bulk RNA-seq exploration and visualisation using dynamically generated R scripts. BMC Bioinformatics, 22(1), 411. (doi: 10.1186/s12859-021-04321-2)

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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.

Item Type:Articles
Additional Information:This project was funded by the GLAZgo Discovery Centre.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Cole, Mr John and Robertson, Mr Neil and Mcguinness, Dr David and Faydaci, Mr Bekir and Goodyear, Professor Carl and Maciewicz, Dr Rose
Authors: Cole, J. J., Faydaci, B. A., Mcguinness, D., Shaw, R., Maciewicz, R. A., Robertson, N. A., and Goodyear, C. S.
College/School:College of Medical Veterinary and Life Sciences
College of Medical Veterinary and Life Sciences > Institute of Health and Wellbeing > Mental Health and Wellbeing
College of Medical Veterinary and Life Sciences > Institute of Infection Immunity and Inflammation
Journal Name:BMC Bioinformatics
Publisher:Biomed Central
ISSN:1471-2105
ISSN (Online):1471-2105
Copyright Holders:Copyright © 2021 The Authors
First Published:First published in BMC Bioinformatics 22(1):411
Publisher Policy:Reproduced under a Creative Commons License

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