require(tumorcomparer)
run_tc_qn_for_cancers_list <- function(cancers_list,gene_set_mut,gene_set_cna,gene_set_exp)
{
# NECESSARY VARIABLES FROM Read_in_and_prepare.R ----
# MUT:
mut_mat_TCGA_after_Annovar <- mut_mat_TCGA_after_Annovar
mut_mat_CCLP_after_Annovar <- mut_mat_CCLP_after_Annovar
## CNA:
TCGA_Pancan_all_thresholded_by_genes_whitelisted <- TCGA_Pancan_all_thresholded_by_genes_whitelisted
CCLP_GISTIC_thresholded <- CCLP_GISTIC_thresholded
## EXP for both CCLP and TCGA
CCLP_Microarray_TCGA_Tumors_RPKMs_quantile_normalized <- CCLP_Microarray_TCGA_Tumors_RPKMs_quantile_normalized
## Two columns from table (TBA)
TCGA_id_and_tumor_type <- TCGA_id_and_tumor_type
## RNASeq weights
TCGA_PanCan_RNASeq_RPKMs_Weights <- TCGA_PanCan_RNASeq_RPKMs_Weights
## Assignment of cell line/tumor and cancer type
GDSC_1000_Binary_Event_Matrix <- GDSC_1000_Binary_Event_Matrix
# SET BASIC PARAMETERS ----
num_cancers <- length(cancers_list)
#comparison_results_list <- vector('list', num_cancers)
#categorization_results_list <- vector('list', num_cancers)
comparison_results_list <- list()
categorization_results_list <- list()
# RUN ACROSS CANCER TYPES ----
for(i in 1:num_cancers)
{
cancer_type <- cancers_list[i]
# Create tumor mut, cna and exp files
write.table(mut_mat_TCGA_after_Annovar[intersect(rownames(mut_mat_TCGA_after_Annovar),gene_set_mut),intersect(colnames(mut_mat_TCGA_after_Annovar),TCGA_id_and_tumor_type[which(TCGA_id_and_tumor_type[,2] == cancer_type),1])],file="tumor_mut.txt", sep = "\t", quote = FALSE)
write.table(TCGA_Pancan_all_thresholded_by_genes_whitelisted[intersect(rownames(TCGA_Pancan_all_thresholded_by_genes_whitelisted),gene_set_cna),intersect(colnames(TCGA_Pancan_all_thresholded_by_genes_whitelisted),TCGA_id_and_tumor_type[which(TCGA_id_and_tumor_type[,2] == cancer_type),1])],file="tumor_cna.txt", sep = "\t", quote = FALSE)
write.table(CCLP_Microarray_TCGA_Tumors_RPKMs_quantile_normalized[intersect(rownames(CCLP_Microarray_TCGA_Tumors_RPKMs_quantile_normalized),gene_set_exp),intersect(colnames(CCLP_Microarray_TCGA_Tumors_RPKMs_quantile_normalized),TCGA_id_and_tumor_type[which(TCGA_id_and_tumor_type[,2] == cancer_type),1])],file="tumor_exp.txt", sep = "\t", quote = FALSE)
# Create weight files
write.table(file="Genes_and_weights_exp.txt",as.matrix(TCGA_PanCan_RNASeq_RPKMs_Weights)[,cancer_type],quote = FALSE,sep="\t")
system(paste0("cp ",paste0("MUT_Weights_TCGA_",cancer_type,".txt") ," Genes_and_weights_mut.txt"))
system(paste0("cp ",paste0("CNA_Weights_TCGA_",cancer_type,".txt") ," Genes_and_weights_cna.txt"))
# Create cell line mut, cna and exp files
if(cancer_type == "COAD" || cancer_type == "READ"){cancer_type <- "COAD/READ"} # CCLP uses COAD/READ
if(cancer_type != "OV")
{
write.table(mut_mat_CCLP_after_Annovar[intersect(rownames(mut_mat_CCLP_after_Annovar),gene_set_mut),intersect(colnames(mut_mat_CCLP_after_Annovar),colnames(GDSC_1000_Binary_Event_Matrix)[which(GDSC_1000_Binary_Event_Matrix[1,] == cancer_type & GDSC_1000_Binary_Event_Matrix[2,] == "cell line")])],file="cell_line_mut.txt", sep = "\t", quote = FALSE)
write.table(CCLP_GISTIC_thresholded[intersect(rownames(CCLP_GISTIC_thresholded),gene_set_cna),intersect(colnames(CCLP_GISTIC_thresholded),colnames(GDSC_1000_Binary_Event_Matrix)[which(GDSC_1000_Binary_Event_Matrix[1,] == cancer_type & GDSC_1000_Binary_Event_Matrix[2,] == "cell line")])],file="cell_line_cna.txt", sep = "\t", quote = FALSE)
write.table(CCLP_Microarray_TCGA_Tumors_RPKMs_quantile_normalized[intersect(rownames(CCLP_Microarray_TCGA_Tumors_RPKMs_quantile_normalized),gene_set_exp),intersect(colnames(CCLP_Microarray_TCGA_Tumors_RPKMs_quantile_normalized),colnames(GDSC_1000_Binary_Event_Matrix)[which(GDSC_1000_Binary_Event_Matrix[1,] == cancer_type & GDSC_1000_Binary_Event_Matrix[2,] == "cell line")])],file="cell_line_exp.txt", sep = "\t", quote = FALSE)
}
else
{
write.table(mut_mat_CCLP_after_Annovar[intersect(rownames(mut_mat_CCLP_after_Annovar),gene_set_mut),intersect(colnames(mut_mat_CCLP_after_Annovar),CCLP_Cell_Lines_And_Tissue_Types$`Cell lines`[which(CCLP_Cell_Lines_And_Tissue_Types$`Tissue type` == "ovary")])],file="cell_line_mut.txt", sep = "\t", quote = FALSE)
write.table(CCLP_GISTIC_thresholded[intersect(rownames(CCLP_GISTIC_thresholded),gene_set_cna),intersect(colnames(CCLP_GISTIC_thresholded),CCLP_Cell_Lines_And_Tissue_Types$`Cell lines`[which(CCLP_Cell_Lines_And_Tissue_Types$`Tissue type` == "ovary")])],file="cell_line_cna.txt", sep = "\t", quote = FALSE)
write.table(CCLP_Microarray_TCGA_Tumors_RPKMs_quantile_normalized[intersect(rownames(CCLP_Microarray_TCGA_Tumors_RPKMs_quantile_normalized),gene_set_exp),intersect(colnames(CCLP_Microarray_TCGA_Tumors_RPKMs_quantile_normalized),CCLP_Cell_Lines_And_Tissue_Types$`Cell lines`[which(CCLP_Cell_Lines_And_Tissue_Types$`Tissue type` == "ovary")])],file="cell_line_exp.txt", sep = "\t", quote = FALSE)
}
cat(cancer_type,":\n")
system.time(source(system.file("pancan_analysis", "RunTumorComparerExample_updated_cont_exp.R", package="tumorcomparer")))
comparison_results_list[[i]] <- comparison_result
categorization_results_list[[i]] <- categorization_list
names(comparison_results_list[[i]]) <- cancer_type
names(categorization_results_list[[i]]) <- cancer_type
#comparison_results_list <- list(comparison_results_list,comparison_result)
#categorization_results_list <- list(categorization_results_list,categorization_list)
}
tc_results <- list(cancers_list = cancers_list,
comparison_results_list_of_lists = comparison_results_list,
categorization_results_list_of_lists = categorization_results_list)
return(tc_results)
}
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