ADAM2.PercentileCF: Calculate the Core Fitness genes using the 90th-percentile...

In DepMap-Analytics/ADAM2: Adaptive Daisy Model

Description

This function identifies the Core Fitness genes from a given Quantative knockout screen dependency matrix where each row is gene and each column the cell line. The function uses all the cell lines and identifies the genes that are essential in majority of the cell lines.

Usage

ADAM2.PercentileCF(depMat,
             display=TRUE,
             percentile=0.9,
             prefix='PercentileMethod')

Arguments

depMat	Quantative knockout screen dependency matrix where rows are genes and columns are samples. A real number in position [i,j] represents the strength of dependency which indicates the amaount of loss of fitness in the j-th sample in case of the inactivation of the i-th gene. Higher strength of dependency indicates higher probability of beign a core fitness gene. These values are used for ranking the genes in terms of their dependecy strength.
display	Boolean, default is TRUE. Should bar plots of the dependency profiles be plotted
percentile	percentage of the cell lines where the given gene should show depletion. The default value is 0.9 indicating 90-th percentile least dependent cell line.
prefix	if the display is false the plots are generated in the working directory using the prefix.

Details

This function implements the idea that if a gene is essential then it should fall in the top Z most depleted genes in at least 90 For a given gene, we can rank its gene effect score in each cell line, then arrange cell lines in order of increasing gene effect score for that gene. This creates a bimodal distribution of gene ranks in their 90th-percentile least depleted lines. Z is choosen as the minimum density between the two normal distributions that are estimated from these ranks. All genes with rank less than this threshold in their 90th percentile cell lines are reported

Value

A list of the following vectors:

cfgenes	Vector of number of genes that are core fitness genes
LeastDependent	A dataframe where each row corresponds to a gene.There are two columns: Value stores the rank of the gene at the N-th percentile least dependent cell line and the Gene stores the gene name
threshold	The rank threshold for core fitness genes

Author(s)

C. Pacini, E. Karakoc & F. Iorio

Examples

data(exampleSBFData)
results <- ADAM2.PercentileCF(depMat=exampleSBFData,display=TRUE)
cfgenes <- results$cfgenes

DepMap-Analytics/ADAM2 documentation built on Dec. 1, 2019, 12:27 a.m.