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Last data update: 2014.03.03

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

TAPPA

R Documentation

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

`x`	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

A list,

`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

Author(s)

Ivana Ihnatova

References

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

Examples


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)

Results


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> library(ToPASeq)
Loading required package: graphite
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Loading required package: gRbase
Loading required package: graph
Loading required package: locfit
locfit 1.5-9.1 	 2013-03-22
Loading required package: Rgraphviz
Loading required package: grid
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/ToPASeq/TAPPA.Rd_%03d_medium.png", width=480, height=480)
> ### Name: TAPPA
> ### Title: Function to use TAPPA method on microarray or RNA-Seq data
> ### Aliases: TAPPA
> ### Keywords: htest
> 
> ### ** Examples
> 
> 
> if (require(DEGraph)) {
+   data("Loi2008_DEGraphVignette")
+   pathways<-pathways("hsapiens","biocarta")[1:10]
+   TAPPA(exprLoi2008, classLoi2008, pathways, type="MA")
+ }
Loading required package: DEGraph
Warning message:
In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE,  :
  there is no package called 'DEGraph'
> 
> ## Not run: 
> ##D if (require(gageData)) {
> ##D 
> ##D  data(hnrnp.cnts)
> ##D  group<-c(rep("sample",4), rep("control",4))
> ##D  hnrnp.cnts<-hnrnp.cnts[rowSums(hnrnp.cnts)>0,]
> ##D pathways<-pathways("hsapiens","biocarta")[1:10]
> ##D  TAPPA( hnrnp.cnts, group, pathways, type="RNASeq", norm.method="TMM")
> ##D }
> ## End(Not run)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>