TAPPA {ToPASeq} | R Documentation

## Topological Analysis of Pathway Phenotype Association (TAPPA)

### 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, which = "proteins", edgeType = NULL,
      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
`which` | Character, which type of nodes is preserved in a pathway. Possible values are `"proteins"`,`"metabolites"`,`"mixed"`
`edgeType` | Character, which type of edges is preserved in a pathway. If `NULL`, all edges are kept.
`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 vst-normalization is performed. Possible values are: `"edgeR", "vst", "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(breastCancerVDX)) {
    data("vdx")
    pathways<-pathways("hsapiens","biocarta")[1:10]
    MAdata<-Biobase::exprs(vdx)[,1:10]
    rownames(MAdata)<-Biobase::fData(vdx)[,"Gene.symbol"]
    MAdata<-MAdata[!duplicated(rownames(MAdata)),]

    TAPPA(MAdata, Biobase::pData(vdx)[,"er"][1:10], pathways, type="MA", convertTo="SYMBOL")
    }

[Package ToPASeq version 1.20.0 Index]