prepareDataObjects: Prepare the data object required for downstream analysis

In cbg-ethz/slidr: Discovery of mutation-specific synthetic lethal partners from large pan-cancer perturbation screens

Prepare the data object required for downstream analysis

Description

The function processes the pan-cancer data and returns an object with viabilities matrix, mutation matrix, mutation annotations and primary site for different types of cancers.

Usage

prepareDataObjects(
  data,
  x,
  fdr = 0.05,
  min_Nmut = 2,
  all_cancers_mut_df,
  CN_df,
  gistic = FALSE,
  top_drivers = NULL,
  CN_Thr = 2,
  minNrcelllines = 5,
  celllines,
  meta_data,
  essential_genes = NULL
)

Arguments

data	input data frame of cell line viabilities for different gene knockdowns
x	primary site
fdr	fdr cut-off for choosing the top drivers from mutSig2 list of drivers. Default = 0.05
min_Nmut	lower bound of number of cell lines with mutations. Default = 2
all_cancers_mut_df	MAF file from CCLE
CN_df	copy number dataframe from CCLE
gistic	Logical variable checking if copy number is based on Gistic. Default = FALSE
top_drivers	vector of driver genes of interest. Default = NULL
CN_Thr	threshold for using CN data. Values: 0 = Homozygous and heterozygous deletions ; 1 = Homozygous deletions only; 2 = No copy number used (default)
minNrcelllines	lower bound of number of cell lines. Default = 5
celllines	vector of interested celllines
meta_data	information on different sub types for each primary site
essential_genes	vector of essential genes

Value

An object for each cancer type

viabilities

dataframe of viabilities for each cancer type

mutations

matrix of mutations in drivers for each cancer type

CNalterations

matrix of non-negative copy number alterations of drivers for each cancer type

mutation_annot

annotations of the mutations

primary_site

cancer type

cbg-ethz/slidr documentation built on Feb. 8, 2023, 11:15 p.m.