The whole data sets analayzed in this manuscript are published as a part of project DRIVE (https://data.mendeley.com/datasets/y3ds55n88r/5) and at the DepMap data portal (https://depmap.org/portal/download). The breast cancer data is available as an R object in this repository (R/BreastData.RData).
To find tumor suppressive effectors, use the identifyDependencies function with argument dependencyType = "tumor-suppressive-effectors:
source("apsic_common_functions.r")
load("BreastData.RData")
# The APSiC for detecting tumor suppressive effectors
identifyDependencies(breastData, dependencyType = "tumor-suppressive-effectors")
The dependencyType argument takes values from tumor-suppressive-effectors, tumor-promoting-effectors,
amplified-cancer-genes, missense-mutational-cancer-genes, non-missense-mutational-cancer-genes to find the cancer dependencies defined in the manuscript.
To plot the rank profiles, the waterfallForGene function can be used:
gene = "TP53"
waterfallForGene(breastData, gene=gene, title=paste("Breast cancer: rank profile of", gene), rank=TRUE)
The manuscript is available at: https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkab627/6329117
APSiC p-values for 26 cancers as well as pan-cancer data for identification of genetic drivers and effectors are available here.
A web portal using the Shiny framework in R has been developed to visualize rank profiles of the DRIVE shRNA screen and corresponding gene expression data from TCGA at https://apsic.scicore.unibas.ch/.
hesam.montazeri (at) ut.ac.ir
charlotte.ng (at) dbmr.unibe.ch