CoRe.coreFitnessGenes | R Documentation |
This function identifies as Core Fitness those genes that are fitness genes in at least n cell lines (defined in input), according to the binary dependency matrix defined in input. This minimal n is estimated through the ADaM method [1] by the CoRe.tradeoffEO_TPR
function.
CoRe.coreFitnessGenes(depMat, crossoverpoint)
depMat |
Binary dependency matrix where rows are genes and columns are cell-lines/samples. A 1 in position [i,j] indicates that the inactivation of the i-th gene exerts a significant loss of fitness in the j-th sample, i.e. that gene is a fitness gene for that cell line |
crossoverpoint |
The estimated minimum number of cell lines in which a gene should be a significant fitness gene in order to be called a core-fitness gene. |
A vector of string containing the predicted core fitness genes.
C. Pacini, E. Karakoc, A. Vinceti & F. Iorio
[1] Behan FM, Iorio F, Picco G, Gonçalves E, Beaver CM, Migliardi G, et al. Prioritization of cancer therapeutic targets using CRISPR-Cas9 screens. Nature. 2019;568:511–6.
CoRe.tradeoffEO_TPR
## Downloading a binary dependency matrix ## for > 300 cancer cell lines from [1] BinDepMat<-CoRe.download_BinaryDepMatrix() ## Extracting dependency submatrix for ## Non-Small Cell Lung Carcinoma cell lines only LungDepMat<-CoRe.extract_tissueType_SubMatrix(BinDepMat) ## Compute as core-fitness genes those that are fitness ## in at least 20 Non-Small Cell Lung Carcinoma cell lines cfgenes <- CoRe.coreFitnessGenes(depMat=LungDepMat,crossoverpoint=20)
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