Pigengene-package {Pigengene} | R Documentation

## Infers robust biological signatures from gene expression data

### Description

Pigengene identifies gene modules (clusters), computes an eigengene for each module, and uses these biological signatures as features for classification. The resulting biological signatures are very robust with respect to the profiling platform. For instance, if Pigenegene computes a biological signature using a microarray dataset, it can infer the same signature in an RNA Seq dataset such that it is directly comparable across the two datasets.

### Details

Package: | Pigengene
Type: | Package
Version: | 0.99.0
Date: | 2016-04-25
License: | GPL (>= 2)

The main function is `one.step.pigengene` which requires a gene expression profile and the corresponding conditions (types). Individual functions are provided to facilitate running the pipeline in a customized way. Also, the inferred biological signatures (computed eigengenes) are useful for other supervised or unsupervised analyses.

In most functions of this package, eigenegenes are computed or used as robust biological signatures. Briefly, each eigengene is a weighted average of the expression of all genes in a module (cluster), where the weights are adjusted in a way that the explained variance is maximized.

### Author(s)

Amir Foroushani, Habil Zare, and Rupesh Agrahari

Maintainer: Habil Zare <zare@txstate.edu>

### References

Large-scale gene network analysis reveals the significance of extracellular matrix pathway and homeobox genes in acute myeloid leukemia, Foroushani A, Agrahari R, Docking R, Karsan A, and Zare H. In preparation.

### See Also

`Pigengene-package`, `one.step.pigengene`, `compute.pigengene`, `WGCNA-package`

### Examples

    data(aml)
    data(mds)
    d1 <- rbind(aml,mds)
    Labels <- c(rep("AML",nrow(aml)),rep("MDS",nrow(mds)))
    names(Labels) <- rownames(d1)
    p1 <- one.step.pigengene(Data=d1,saveDir='pigengene', bnNum=10, verbose=1,
       seed=1, Labels=Labels, toCompact=FALSE, doHeat=FALSE)
    plot(p1$c5treeRes$c5Trees[["34"]])
    ## See pigengene for results.

[Package Pigengene version 1.6.0 Index]