## ---- eval=FALSE-------------------------------------------------------------- # if (!requireNamespace("BiocManager", quietly=TRUE)) # install.packages("BiocManager") # BiocManager::install("iGC") ## ----------------------------------------------------------------------------- library(iGC) ## ----------------------------------------------------------------------------- sample_desc_pth <- system.file("extdata", "sample_desc.csv", package = "iGC") sample_desc <- create_sample_desc(sample_desc_pth) ## ---- eval=FALSE-------------------------------------------------------------- # sample_desc <- create_sample_desc( # sample_names = sample_desc$Sample, # cna_filepaths = sample_desc$CNA_filepath, # ge_filepaths = sample_desc$GE_filepath # ) ## ----------------------------------------------------------------------------- head(sample_desc) ## ----------------------------------------------------------------------------- gene_exp <- create_gene_exp(sample_desc, progress = FALSE) ## ---- eval=FALSE-------------------------------------------------------------- # gene_exp <- create_gene_exp( # sample_desc, # read_fun = read.table, # progress = TRUE, progress_width = 60, # # arugments passed to the customized read_fun (here is read.table) # header = FALSE, # skip = 2, # na.strings = "null", # colClasses = c("character", "double") # ) ## ----------------------------------------------------------------------------- gene_exp[GENE %in% c('TP53', 'BRCA1', 'NFKB1'), 1:10, with=FALSE] ## ----------------------------------------------------------------------------- my_cna_reader <- function(cna_filepath) { cna <- data.table::fread(cna_filepath, sep = '\t', header = TRUE) cna[, .(Chromosome, Start, End, Segment_Mean)] } gain_loss = log2(c(2.4, 1.6)) - 1 gene_cna <- create_gene_cna( sample_desc, gain_threshold = gain_loss[1], loss_threshold = gain_loss[2], read_fun = my_cna_reader, progress = FALSE ) gene_cna[GENE %in% c('TP53', 'BRCA1', 'NFKB1'), 1:10, with=FALSE] ## ---- eval=FALSE-------------------------------------------------------------- # # Change 4 to match one's total CPU cores # doMC::registerDoMC(cores = 4) # gene_cna <- faster_gene_cna( # sample_desc, gain_loss[[1]], gain_loss[[2]], parallel = TRUE # ) ## ----------------------------------------------------------------------------- cna_driven_genes <- find_cna_driven_gene( gene_cna, gene_exp, gain_prop = 0.15, loss_prop = 0.15, progress = FALSE, parallel = FALSE ) head(cna_driven_genes$gain_driven) head(cna_driven_genes$loss_driven) head(cna_driven_genes$both) ## ----------------------------------------------------------------------------- cna_driven_genes$loss_driven[GENE %in% c('BRCA1')]