expFeatureMatrix: Expression-based feature matrix

In mlDNA: Machine Learning-based Differential Network Analysis of Transcriptome Data

Description

This function generates expression-based features for each gene with the consideration of z-scores, fold changes and actural expression values.

Usage

expFeatureMatrix(expMat1, sampleVec1, expMat2, sampleVec2, 
                 logTransformed = TRUE, base = 2, 
                 features = c("zscore", "foldchange", "cv", "expression"))

Arguments

expMat1	a numeric matrix recording gene expression data from condition 1. Each row represent the expression values of one gene, each column represents the expression values of all genes from one biological experiment.
sampleVec1	a numeric vector representing biological replication (or different time points) and technical replication for condition 1. For instance, c(1,1,2,2,3,3) denotes three biological replications, and two technicial replications for each biological sample.
expMat2	a numeric matrix recording gene expression data from condition 2.
sampleVec2	a numeric vector representing biological experiments and technical replications for condition 2. Definition is similar as sampleVec1.
logTransformed	logic value, TRUE indicates that the expression data in expMat1 and expMat2 have been log-transformed.
base	base of log transformation.
features	A character fector specifying different features will be used to generate feature matrix.

Value

value

a numeric matrix with express-based features for each gene.

Note

The expression-based features including:

(1) expression variance across all samples calculated with z-scores of genes under two conditions;

(2) fold change of gene expression under two conditions;

(3) expression values of genes in two conditions used for retaining the information from actual expression values.

Author(s)

Chuang Ma, Xiangfeng Wang

Examples

 ## Not run: 
 
   ##generated expression features
   sampleVec1 <- c(1, 2, 3, 4, 5, 6)
   sampleVec2 <- c(1, 2, 3, 4, 5, 6)
   featureMat <- expFeatureMatrix( expMat1 = ControlExpMat, sampleVec1 = sampleVec1, 
                                   expMat2 = SaltExpMat, sampleVec2 = sampleVec2, 
                                   logTransformed = TRUE, base = 2, 
                               features = c("zscore", "foldchange", "cv", "expression"))

## End(Not run)

mlDNA documentation built on May 2, 2019, 2:15 p.m.