convert2biodata: Format biological data

In tcgaViz: Visualization Tool for the Cancer Genome Atlas Program (TCGA)

Format biological data

Description

Merges gene and cell datasets with the same TCGA sample identifiers, splits samples according to the expression levels of a selected gene into two categories (below or above average) and formats into a 3-column data frame: gene expression levels, cell types, and gene expression values.

Usage

convert2biodata(algorithm, disease, tissue, gene_x, stat = "mean", path = ".")

Arguments

algorithm	character for the algorithm used to estimate the distribution of cell type abundance among : 'Cibersort', 'Cibersort_ABS', 'EPIC', 'MCP_counter', 'Quantiseq', 'Timer', 'Xcell', 'Xcell (2)' and 'Xcell64'.
disease	character for the type of TCGA cancer (see the list in extdata/disease_names.csv).
tissue	character for the type of TCGA tissue among : 'Additional - New Primary', 'Additional Metastatic', 'Metastatic', 'Primary Blood Derived Cancer - Peripheral Blood', 'Primary Tumor', 'Recurrent Tumor', 'Solid Tissue Normal'
gene_x	character for the gene selected in the differential analysis (see the list in extdata/gene_names.csv).
stat	character for the statistic to be chosen among "mean", "median" or "quantile".
path	character for the path name of the tcga dataset.

Value

data frame with the following columns:

• high (logical): the expression levels of a selected gene, TRUE for below or FALSE for above average.

• cells (factor): cell types.

• value (float): the abundance estimation of the cell types.

Examples

data(tcga)
(convert2biodata(
    algorithm = "Cibersort_ABS",
    disease = "breast invasive carcinoma",
    tissue = "Primary Tumor",
    gene_x = "ICOS"
))

tcgaViz documentation built on April 4, 2023, 5:14 p.m.