hi_loadings {pcaExplorer} | R Documentation

## Extract genes with highest loadings

### Description

Extract genes with highest loadings

### Usage

    hi_loadings(pcaobj, whichpc = 1, topN = 10, exprTable = NULL,
      annotation = NULL, title = "Top/bottom loadings")

### Arguments

`pcaobj` | A `prcomp` object
`whichpc` | An integer number, corresponding to the principal component of interest
`topN` | Integer, number of genes with top and bottom loadings
`exprTable` | A `matrix` object, e.g. the counts of a `DESeqDataSet`. If not NULL, returns the counts matrix for the selected genes
`annotation` | A `data.frame` object, with row.names as gene identifiers (e.g. ENSEMBL ids) and a column, `gene_name`, containing e.g. HGNC-based gene symbols
`title` | The title of the plot

### Value

A ggplot2 object, or a `matrix`, if `exprTable` is not null

### Examples

    dds <- makeExampleDESeqDataSet_multifac(betaSD = 3,betaSD_tissue = 1)
    rlt <- DESeq2::rlogTransformation(dds)
    pcaobj <- prcomp(t(SummarizedExperiment::assay(rlt)))
    hi_loadings(pcaobj, topN = 20)
    hi_loadings(pcaobj, topN = 10, exprTable=dds)
    hi_loadings(pcaobj, topN = 10, exprTable=counts(dds))

[Package pcaExplorer version 2.14.2 Index]