RT Journal Article
SR Electronic
T1 SPOT: a web-tool enabling Swift Profiling Of Transcriptomes
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2021.03.03.433767
DO 10.1101/2021.03.03.433767
A1 Farr, Elias
A1 Sattler, Julia M.
A1 Frischknecht, Friedrich
YR 2021
UL http://biorxiv.org/content/early/2021/03/04/2021.03.03.433767.abstract
AB The increasing number of single cell and bulk RNAseq data sets describing complex gene expression profiles in different organisms, organs or cell types calls for an intuitive tool allowing rapid comparative analysis. Here we present Swift Profiling Of Transcriptomes (SPOT) as a web tool that allows not only differential expression analysis but also fast ranking of genes fitting transcription profiles of interest. Based on a heuristic approach the spot algorithm ranks the genes according to their proximity to the user-defined gene expression profile of interest. The best hits are visualized as a table, bar chart or dot plot and can be exported as an Excel file. While the tool is generally applicable, we tested it on RNAseq data from malaria parasites that undergo multiple stage transformations during their complex life cycle as well as on data from multiple human organs during development and cell lines infected by the SARS-CoV-2 virus. SPOT should enable non-bioinformaticians to easily analyse their own and any available dataset.Competing Interest StatementThe authors have declared no competing interest.