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

ABSTRACT: Omics data are broadly used to get a snap-shot 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. 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 visualise the results and run post-analyses, and is mirrored as a scripted version in R. 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/. We provide data examples within the app, and extensive information about the different variables to select, the results, and the different plots in the help page. User can also check the tutorial and more information in https://saezlab.github.io/ShinyFUNKI/.

SUBMITTER: Hernansaiz-Ballesteros R 

PROVIDER: S-EPMC8963329 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature