get.consensus.subtypes: Get consensusOV ovarian cancer subtypes

Description Usage Arguments Value Examples

View source: R/get.consensus.subtypes.R

Description

Get consensusOV ovarian cancer subtypes

Usage

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get.consensus.subtypes(expression.matrix, entrez.ids,
  concordant.tumors.only = TRUE, remove.using.cutoff = FALSE,
  percentage.dataset.removed = 0.75,
  .training.dataset = consensus.training.dataset.full,
  .dataset.names.to.keep = names(esets.rescaled.classified.filteredgenes))

Arguments

expression.matrix

A matrix of gene expression values with rows as genes, columns as samples.

entrez.ids

A vector of Entrez Gene IDs, corresponding to the rows of expression.matrix

concordant.tumors.only

Logical. Should the classifier trained only on tumors that are concordantly classified by Helland, Konecny, and Verhaak? Defaults to TRUE.

remove.using.cutoff

Specify whether to classify NA for samples that do not meet a margin cutoff

percentage.dataset.removed

If remove.using.cutoff is TRUE, then classify this percentage of samples to NA based on margin values

.training.dataset

ExpressionSet containing the training data. Defaults to the pooled dataset across selected MetaGxOvarian datasets.

.dataset.names.to.keep

Names of MetaGxOvarian datasets to use for training

Value

A list with first value consensusOV.subtypes containing a factor of subtype names; and second value rf.probs containing a matrix of subtype probabilities

Examples

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library(Biobase)
data(GSE14764.eset)
expression.matrix <- exprs(GSE14764.eset)
entrez.ids <- as.character(fData(GSE14764.eset)$EntrezGene.ID)
get.consensus.subtypes(expression.matrix, entrez.ids)

bhklab/consensusOV documentation built on Nov. 2, 2018, 1:52 p.m.