PlotRegulationHeatmap

gene

The xseq posteriors, output of <code>InferXseqPosterior</code>
or <code>LearnXseqParameter</code>

posterior

A data.frame of mutations. The data.frame should have at least
three columns of characters: sample, hgnc_symbol, and variant_type.
The variant_type column cat be either "HOMD", "HLAMP",
  "MISSENSE", "NONSENSE", "FRAMESHIFT", "INFRAME", "SPLICE", "NONSTOP",
  "STARTGAINED", "SYNONYMOUS", "OTHER", "FUSION", "COMPLEX".

A vector representing a character of each patient,
e.g., subtype

subtype

main


Heatmap showing the connected genes' dysregulation probabilities


A hierarchical Bayesian approach to assess functional impact of mutations on gene expression in cancer. Given a patient-gene matrix encoding the presence/absence of a mutation, a patient-gene expression matrix encoding continuous value expression data, and a graph structure encoding whether two genes are known to be functionally related, xseq outputs: a) the probability that a recurrently mutated gene g influences gene expression across the population of patients;
and b) the probability that an individual mutation in gene g in an individual patient m influences expression within that patient.

PlotRegulationHeatmap: Heatmap showing the connected genes' dysregulation probabilities

Description

Usage

Arguments