im_cor_tcga: Finds Spearman correlation between an oncogene, an immune...

In korkutlab/imogimap: What the Package Does (One Line, Title Case)

Finds Spearman correlation between an oncogene, an immune checkpoint and immune associated phenotypes.

Description

Finds Spearman correlation between an oncogene, an immune checkpoint and immune associated phenotypes.

Usage

im_cor_tcga(onco_gene, icp_gene, cohort, sample_list)

Arguments

onco_gene	A character vector of gene Hugo symbols.
icp_gene	An optional character vector of immune checkpoint gene/protein IDs.
cohort	a character vector of TCGA diseases
sample_list	An optional character vector of TCGA samples barcodes indicating a subset of samples within a cohort.

Details

im_cor_tcga uses NASeq2GeneNorm expression data, as provided by curatedTCGAData, to find correlation between onco_genes and immune checkpoints and immuno-oncology features as listed in TCGA_immune_features_list.

By default (if no icp_gene is specified), icp_gene_list will be used.

For TCGA disease list see TCGA_disease_list

All barcodes in sample_list must be 15 character long and belong to the same cohort. When sample_list is provided, cohort should be the disease cohort that they belong to, otherwise only the first element of the cohort list will be used.

A non-FDR-adjusted p.value is reported for each correlation value to allow for easier adjustments by user.

All barcodes in sample_list must be 15 character long and belong to the same cohort. When sample_list is provided, cohort should be the disease cohort that they belong to, otherwise only the first element of the cohort list will be used.

Value

a list of dataframes containing Spearman correlations and non-FDR adjusted probability values.

Examples

im_cor_tcga(onco_gene=c("BRAF"),icp_gene=c("CD274","CTLA4"),cohort=c("gbm"))

korkutlab/imogimap documentation built on March 17, 2023, 8:22 a.m.