dis.rel.tissues: Significance Of Disease Modules In Tissue-Specific...

In vittoriofortino84/ThETA: Transcriptome-based efficacy estimates of target(gene)-disease associations

Description

Compile significance of disease modules in tissue-specific interactomes.

Usage

dis.rel.tissues(
  disease_genes,
  ppi_network,
  weighted = FALSE,
  tissue_expr_data,
  thr = 1,
  top = 20,
  rand = 100,
  verbose = FALSE
)

list.dis.rel.tissues(
  disease_gene_list,
  ppi_network,
  weighted = FALSE,
  tissue_expr_data,
  thr = 1,
  top = 20,
  rand = 100,
  parallel = NULL
)

Arguments

disease_genes	character vector containing the IDs of the genes related to a particular disease. Gene IDs are expected to match with those provided in ppi_network and tissue_expr_data.
ppi_network	a matrix or a data frame with at least two columns reporting the ppi connections (or edges). Each line corresponds to a direct interaction. Columns give the gene IDs of the two interacting proteins.
weighted	logical indicating whether the ppi_network contain edge weights? If TRUE, then the third column is used to weight edges.
tissue_expr_data	a numeric matrix or data frame indicating expression significances in the form of Z-scores. Columns are tissues and rows are genes; colnames and rownames must be provided. Gene IDs are expected to match with those provided in ppi_network.
thr	an integer specifying the threshold for expression significance. Only genes with expression significance >= thr will be considered expressed in a particular tissue. Defaults to 1.
top	an integer indicating the number of genes to be considered to extend the disease gene set. Genes are selected based on the radial distance from the disease-relevant genes.
rand	an integer indicating the number of random sets of genes needed to calculate the singificance of disease-tissue associations. Defaults to 100.
verbose	logical indicating whether the messages will be displayed or not in the screen.
disease_gene_list	a list of disease-associated genes. Each element of the list is a character vector containing the IDs of the genes related to a particular disease.
parallel	an integer indicating how many cores will be registered for parallel computation. If NULL, the function will not use parallel computation.

Details

This function implements the method from \insertRefKitsak2016ThETA. The function tests the significance of disease modules in tissue-specific interactomes, consisting of genes with expression significance >= thr. First, disease maximal connected component is measured in tissue t. Then, the average of rand maximal connected components in t is determined to compute the significance of real data. As a major improvement, the radial distance between each gene and all disease-relevant genes is computed to extend the disease gene set.

Value

A list of five items:
- maxc: a vector or a matrix specifying the disease maximal connected components by tissue;
- mer: a vector or a matrix specifying the averages of rand maximal connected components by tissue;
- sdr: a vector or a matrix specifying the standard deviations of rand maximal connected components by tissue;
- z: a vector or a matrix specifying the significances of disease-tissue associations in the form of Z-scores;
- genes: a vector or a matrix specifying the cardinality of disease-relevant genes expressed in each tissue.

vittoriofortino84/ThETA documentation built on May 23, 2021, 4:24 a.m.