codonPCA {RiboProfiling} | R Documentation

## PCA graphs on codon coverage

### Description

PCA graphs on codon coverage

### Usage

    codonPCA(data, typeData)

### Arguments

`data` | a list of 2 data.frames: one with the number of times each codon type is found in each ORF and one with the number of reads for each codon in each ORF.
`typeData` | a character string. It is used as title for the PCA. Ex. typeData="codonCoverage"

### Value

a list of length 2: PCA_scores - matrix of the scores on the first 4 principal components. PCA_plots - a list of 5 PCA scatterplots.

### Examples

    #How to perform a PCA analysis based on codon coverage
    #adapted from
    #http://stackoverflow.com/questions/20260434/test-significance-of-clusters-on-a-pca-plot
    #either get the codon frequency, coverage, and annotation using a function
    #such as codonInfo in this package
    #or create a list of matrices with the above information
    data(codonDataCtrl)
    codonData <- codonDataCtrl
    codonUsage <- codonData[[1]]
    codonCovMatrix <- codonData[[2]]

    #keep only genes with a minimum number of reads
    nbrReadsGene <- apply(codonCovMatrix, 1, sum)
    ixExpGenes <- which(nbrReadsGene >= 50)
    codonCovMatrix <- codonCovMatrix[ixExpGenes, ]

    #get the PCA on the codon coverage
    codonCovMatrixTransp <- t(codonCovMatrix)
    rownames(codonCovMatrixTransp) <- colnames(codonCovMatrix)
    colnames(codonCovMatrixTransp) <- rownames(codonCovMatrix)

    listPCACodonCoverage <- codonPCA(codonCovMatrixTransp,"codonCoverage")
    print(listPCACodonCoverage[[2]])
    #See aditional examples in the pdf manual

[Package RiboProfiling version 1.16.0 Index]