  Motivation: Omics data, such as transcriptomics or phosphoproteomics, 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 signaling 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 several omics 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. Availability: FUNKI is a free and open-source
application built on R and Shiny, available in GitHub at
https://github.com/saezlab/ShinyFUNKI under GNU v3.0 license and accessible
also in https://saezlab.shinyapps.io/funki/ Contact<EMAIL_ADDRESS>Supplementary information: We provide data examples within the app, as well as
extensive information about the different variables to select, the results, and
the different plots in the help page.
