FUNKI: interactive functional footprint-based analysis of omics data.

Autor:	Hernansaiz-Ballesteros R; Institute for Computational Biomedicine, Heidelberg University, Heidelberg University Hospital, Faculty of Medicine, Bioquant, Heidelberg 69120, Germany., Holland CH; Institute for Computational Biomedicine, Heidelberg University, Heidelberg University Hospital, Faculty of Medicine, Bioquant, Heidelberg 69120, Germany.; Faculty of Biosciences, Heidelberg University, Heidelberg 69120, Germany., Dugourd A; Institute for Computational Biomedicine, Heidelberg University, Heidelberg University Hospital, Faculty of Medicine, Bioquant, Heidelberg 69120, Germany.; Faculty of Biosciences, Heidelberg University, Heidelberg 69120, Germany., Saez-Rodriguez J; Institute for Computational Biomedicine, Heidelberg University, Heidelberg University Hospital, Faculty of Medicine, Bioquant, Heidelberg 69120, Germany.
Jazyk:	angličtina
Zdroj:	Bioinformatics (Oxford, England) [Bioinformatics] 2022 Mar 28; Vol. 38 (7), pp. 2075-2076.
DOI:	10.1093/bioinformatics/btac055
Abstrakt:	Motivation: Omics data are broadly used to get a snapshot of the molecular status of cells. In particular, changes in omics can be used to estimate the activity of pathways, transcription factors and kinases based on known regulated targets, that we call footprints. Then the molecular paths driving these activities can be estimated using causal reasoning on large signalling networks. Results: We have developed FUNKI, a FUNctional toolKIt for footprint analysis. It provides a user-friendly interface for an easy and fast analysis of transcriptomics, phosphoproteomics and metabolomics data, either from bulk or single-cell experiments. FUNKI also features different options to visualize the results and run post-analyses, and is mirrored as a scripted version in R. Availability and Implementation: FUNKI is a free and open-source application built on R and Shiny, available at https://github.com/saezlab/ShinyFUNKI and https://saezlab.shinyapps.io/funki/. Supplementary Information: Supplementary data are available at Bioinformatics online. (© The Author(s) 2022. Published by Oxford University Press.)
Databáze:	MEDLINE
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