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Molecular Subtyping Resource: a user-friendly tool for rapid biological discovery from transcriptional data

Authors :
Baharak Ahmaderaghi
Raheleh Amirkhah
James Jackson
Tamsin R. M. Lannagan
Kathryn Gilroy
Sudhir B. Malla
Keara L. Redmond
Gerard Quinn
Simon S. McDade
ACRCelerate Consortium
Tim Maughan
Simon Leedham
Andrew S. D. Campbell
Owen J. Sansom
Mark Lawler
Philip D. Dunne
Source :
Disease Models & Mechanisms, Vol 15, Iss 3 (2022)
Publication Year :
2022
Publisher :
The Company of Biologists, 2022.

Abstract

Generation of transcriptional data has dramatically increased in the past decade, driving the development of analytical algorithms that enable interrogation of the biology underpinning the profiled samples. However, these resources require users to have expertise in data wrangling and analytics, reducing opportunities for biological discovery by ‘wet-lab’ users with a limited programming skillset. Although commercial solutions exist, costs for software access can be prohibitive for academic research groups. To address these challenges, we have developed an open source and user-friendly data analysis platform for on-the-fly bioinformatic interrogation of transcriptional data derived from human or mouse tissue, called Molecular Subtyping Resource (MouSR). This internet-accessible analytical tool, https://mousr.qub.ac.uk/, enables users to easily interrogate their data using an intuitive ‘point-and-click’ interface, which includes a suite of molecular characterisation options including quality control, differential gene expression, gene set enrichment and microenvironmental cell population analyses from RNA sequencing. The MouSR online tool provides a unique freely available option for users to perform rapid transcriptomic analyses and comprehensive interrogation of the signalling underpinning transcriptional datasets, which alleviates a major bottleneck for biological discovery. This article has an associated First Person interview with the first author of the paper.

Details

Language :
English
ISSN :
17548403 and 17548411
Volume :
15
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Disease Models & Mechanisms
Publication Type :
Academic Journal
Accession number :
edsdoj.f0348220b314b64a6a61c4ef7c86992
Document Type :
article
Full Text :
https://doi.org/10.1242/dmm.049257