Installation 

# install.packages("devtools")
devtools::install_github("CogDisResLab/KRSA")

The KRSA Vignette is now available in R (using browseVignettes(“KRSA”)). To have the KRSA Vignette locally accessible, the build_vignettes argument must be set as TRUE when installing the package:

devtools::install_github(build_vignettes = T)

Installation Requirements

R (>= 3.5.0) version

For Windows users:
installment of Rtools (https://cran.r-project.org/bin/windows/Rtools/).

KRSA

Kinome Random Sampling Analyzer, or KRSA, is an R Shiny application that automates many of the steps required to analyze PamChip datasets, including peptide filtering, random sampling, heatmap generation, and kinase network generation. This new software makes analyzing kinome array datasets accessible and eliminates much of the human workload that the previous method required. More importantly, KRSA represents the results in a bigger biological context by visualizing altered kinome signaling networks instead of individual kinases.

More info on the PamStation12 platform can be found here: PamGene

Package Website

https://CogDisResLab.github.io/KRSA/

Access

KRSA Shiny App GitHub Repository: Link

KRSA manuscript is available here: PubMed

Workflow

KRSA Workflow

Random Sampling Approach

Running Random Sampling



Calculating Mean, Standard Deviations, and Z Scores



Input Files

The user-supplied kinase-peptide association file and the raw kinome array data file are selected as input. The kinase-peptide associations should be based on the known/predicted interactions found in databases like GPS 3.0 and Kinexus Phosphonet. Expected inputs should be formatted as shown in the example files: vignettes/data_files/example_Median_SigmBg.txt

Contact

For technical issues, please start a new issue on this repo: Link

For biological interpretation questions please email: