CoRe.panessprofile: Profile of number of fitness genes across fixed numbers of...

In DepMap-Analytics/CoRe: CoRe R package

Profile of number of fitness genes across fixed numbers of cell lines and its cumulative sums

Description

This function calculates the numbers (and cumulative numbers) of genes whose inactivation exerts a fitness effect in n cell lines, varying n from 1 to the number of cell lines in the dependency map given in input.

Usage

CoRe.panessprofile(depMat,
                   display=TRUE,
                   main_suffix='fitness genes in at least 1 cell line',
                   xlab='n. dependent cell lines')

Arguments

depMat	A binary dependency matrix, i.e. a binary matrix with genes on rows and cell-lines/samples on columns. A 1 in position [i,j] indicates that inactivation of the i-th gene exerts a significant loss of fitness in the j-th sample, 0 otherwise.
display	Boolean, default is TRUE. Should bar plots of the dependency profiles be plotted
main_suffix	If display=TRUE, title suffix to give to plot showing number of genes depleted across fixed number of cell lines, default is 'genes depleted in at least 1 cell line'
xlab	If display=TRUE, label to be given to the x-axis of the plots, default is 'n. cell lines'

Value

A list with the following two named vectors:

panessprof	Number of genes that are depleted across fixed number of cell lines in the inputted dependency matrix
CUMsums	Cumulative number of genes depleted in at least n cell lines in the inputted dependency matrix

Author(s)

C. Pacini, E. Karakoc, A. Vinceti & F. Iorio

References

[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.

[2] Dwane L, Behan FM, Gonçalves E, Lightfoot H, Yang W, van der Meer D, Shepherd R, Pignatelli M, Iorio F, Garnett MJ. Project Score database: a resource for investigating cancer cell dependencies and prioritizing therapeutic targets. Nucleic Acids Res. 2021 Jan 8;49(D1):D1365-D1372.

Examples

## Downloading dependency matrix
## for > 300 cancer cell lines from [1,2]
BinDepMat<-CoRe.download_BinaryDepMatrix()

## Extracting dependency submatrix for
## Non-Small Cell Lung Carcinoma cell lines only
LungDepMat<-CoRe.extract_tissueType_SubMatrix(BinDepMat, tissue_type="Non-Small Cell Lung Carcinoma")

## Computing number of fitness genes across fixed numbers
## of cell lines and its cumulative sums
pprofile <- CoRe.panessprofile(depMat = LungDepMat)
head(pprofile)

DepMap-Analytics/CoRe documentation built on July 6, 2022, 8:01 a.m.