logReg: Logistic regression for predicting the probability to belong...

In a4Base: Automated Affymetrix Array Analysis Base Package

Description

Logistic regression for predicting the probability to belong to a certain class in binary classification problems.

Usage

logReg(
  object,
  groups,
  probesetId = NULL,
  geneSymbol = NULL,
  main = NULL,
  probe2gene = TRUE,
  ...
)

Arguments

object	ExpressionSet object for the experiment
groups	String containing the name of the grouping variable. This should be a the name of a column in the pData of the expressionSet object.
probesetId	The probeset ID. These should be stored in the featureNames of the expressionSet object.
geneSymbol	The gene symbol. These should be stored in the column `Gene Symbol` in the featureData of the expressionSet object.
main	Main title on top of the gra
probe2gene	Boolean indicating whether the probeset should be translated to a gene symbol (used for the default title of the plot)
...	Possibility to add extra plot options. See plot

Details

It will always estimate probability scores to belong to the second level of the factor variable. If a probability score to other level is preferred, then you need to change the order of the levels of the factor.

Value

A data.frame object with three columns and rownames

rownames	The 'sampleNames' of the expressionSet object
x	The expression values for the specified gene for all samples
y	The labels of the samples
fit	The fitted probability score to belong to one of the two classes.

Author(s)

Willem Talloen

See Also

ROCcurve,probabilitiesPlot

Examples

## Not run: 
if (require(ALL)){
  data(ALL, package = "ALL")
  ALL <- addGeneInfo(ALL)
  ALL$BTtype <- as.factor(substr(ALL$BT,0,1))
  logRegRes <- logReg(geneSymbol = "HLA-DPB1", object = ALL, groups = "BTtype")
  # scoresplot
  probabilitiesPlot(proportions = logRegRes$fit, classVar = logRegRes$y,
      sampleNames = rownames(logRegRes), main = 'Probability of being a T-cell type ALL')
  # barplot
  probabilitiesPlot(proportions = logRegRes$fit, classVar = logRegRes$y, barPlot=TRUE,
      sampleNames = rownames(logRegRes), main = 'Probability of being a T-cell type ALL')
 }

## End(Not run)

a4Base documentation built on Nov. 8, 2020, 5:41 p.m.