sigFeatureSelection: Selecting informative features

Description Usage Arguments Value Author(s) Examples

View source: R/sigFeatureSelection.R

Description

This function extracting informative features with feature selection algorithms including the student's t-test and chi-square test feature selection algorithms.

Usage

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  sigFeatureSelection(featureMatrix, positives, negatives, binary = FALSE, level = 0.05)

Arguments

featureMatrix

A numeric matrix of features where rows represent genes, cols represent features

positives

A character vector of positive samples

negatives

A character vector of negative samples

binary

A logical value, where TRUE represents the features are binary with 0 and 1, the default is FALSE

level

A numeric value recording the significant level, the default is 0.05

Value

A numeric feature matrix with only significant features were contained

Author(s)

Jingjing Zhai, Chuang Ma

Examples

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  ## Not run: 
    positives <- c("AT1G01060", "AT1G09530", "AT1G09570", "AT1G12610")
    sifFeatureMat <- sigFeatureSelection(featureMatrix = featureMat, 
                                   positives = positives, 
                                   negatives = negatives)
    ## featureMat can be calculated by function FeatureExtract
    ## negatives can be calculated by function selectNegSamples
  
## End(Not run)

cma2015/RAP documentation built on Aug. 18, 2019, 8:02 p.m.