TAPPA: Function to use TAPPA method on microarray or RNA-Seq data

Description

The functions analyses the differential expression of pathways via TAPPA method. Expression is compared between two groups of samples by Mann-Whitney test. P-values are later adjusted for multiple hypothesis testing by Benjamini-Hochberg's FDR method.

Usage

TAPPA(x, group, pathways, type, preparePaths=TRUE, norm.method=NULL, test.method=NULL, test=t.test, normalize=TRUE, verbose=FALSE, both.directions=TRUE,  maxNodes=150, minEdges=0, commonTh=2, filterSPIA=FALSE, convertTo="none", convertBy=NULL)

Arguments

An ExpressionSet object or a gene expression data matrix or count matrix, rows refer to genes, columns to samples

group

Name or number of the phenoData column or a character vector or factor that contains required class assigments

pathways

A list of pathways in a form from graphite package or created by preparePathways()

type

Type of the input data, "MA" for microarray and "RNASeq" for RNA-Seq

preparePaths

Logical, by default the pathways are transformed with preparePathways(). Use FALSE, if you have done this transformation separately

norm.method

Character, the method to normalize RNAseq data. If NULL then TMM-normalization is performed. Possible values are: "TMM", "DESeq2", "rLog", "none"

test.method

Character, the method for differentiall expression analysis of RNAseq data. If NULL then "voomlimma" is used. Possible values are: "DESeq2", "voomlimma", "vstlimma", "edgeR". This analysis is needed only for the visualization.

test

Function implementing a statistical test comparing PCI scores between groups. It is employed as test(PCI~group)$p.value, where PCI is a numeric vector of the same length as group

normalize

Logical, should data be normalized?

verbose

Logical, if TRUE names of the pathways are printed as they are analysed

both.directions, maxNodes, minEdges, commonTh, filterSPIA, convertTo, convertBy

Arguments for the preparePathways()

Value

res: A data frame, rows refer to pathways. Columns contain: number of valid PCI-scores, median, min and max of the PCI scores for each group of samples, p-value of the test (p.val) and adjusted p-value (p.adj). If less than two nodes are present in the data, the function puts NA's in all columns.
topo.sig: NULL, it is preserved for the compatibility with other methods implemented in this package
degtest: A numeric vector of gene-level differential expression statistics

References

Gao, S. and Wang, X. (2007) TAPPA: topological analysis of pathway phenotype association. Bioinformatics, 23, pages 3100-3102

Examples

Run this code


if (require(DEGraph)) {
  data("Loi2008_DEGraphVignette")
  pathways<-pathways("hsapiens","biocarta")[1:10]
  TAPPA(exprLoi2008, classLoi2008, pathways, type="MA")
}

## Not run: 
# if (require(gageData)) {
# 
#  data(hnrnp.cnts)
#  group<-c(rep("sample",4), rep("control",4))
#  hnrnp.cnts<-hnrnp.cnts[rowSums(hnrnp.cnts)>0,]
# pathways<-pathways("hsapiens","biocarta")[1:10]
#  TAPPA( hnrnp.cnts, group, pathways, type="RNASeq", norm.method="TMM")
# }
# ## End(Not run)