pca2go {pcaExplorer} | R Documentation

## Functional interpretation of the principal components

### Description

Extracts the genes with the highest loadings for each principal component, and performs functional enrichment analysis on them using routines and algorithms from the `topGO` package

### Usage

    pca2go(
      se,
      pca_ngenes = 10000,
      annotation = NULL,
      inputType = "geneSymbol",
      organism = "Mm",
      ensToGeneSymbol = FALSE,
      loadings_ngenes = 500,
      background_genes = NULL,
      scale = FALSE,
      return_ranked_gene_loadings = FALSE,
      annopkg = NULL,
      ...
    )

### Arguments

`se` | A `DESeqTransform` object, with data in `assay(se)`, produced for example by either `rlog` or `varianceStabilizingTransformation`
`pca_ngenes` | Number of genes to use for the PCA
`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
`inputType` | Input format type of the gene identifiers. Will be used by the routines of `topGO`
`organism` | Character abbreviation for the species, using `org.XX.eg.db` for annotation
`ensToGeneSymbol` | Logical, whether to expect ENSEMBL gene identifiers, to convert to gene symbols with the `annotation` provided
`loadings_ngenes` | Number of genes to extract the loadings (in each direction)
`background_genes` | Which genes to consider as background.
`scale` | Logical, defaults to FALSE, scale values for the PCA
`return_ranked_gene_loadings` | Logical, defaults to FALSE. If TRUE, simply returns a list containing the top ranked genes with hi loadings in each PC and in each direction
`annopkg` | String containing the name of the organism annotation package. Can be used to override the `organism` parameter, e.g. in case of alternative identifiers used in the annotation package (Arabidopsis with TAIR)
`...` | Further parameters to be passed to the topGO routine

### Value

A nested list object containing for each principal component the terms enriched in each direction. This object is to be thought in combination with the displaying feature of the main `pcaExplorer` function

### Examples

    library(airway)
    library(DESeq2)
    data(airway)
    airway
    dds_airway <- DESeqDataSet(airway, design= ~ cell + dex)
    ## Not run:
    rld_airway <- rlogTransformation(dds_airway)
    # constructing the annotation object
    anno_df <- data.frame(gene_id = rownames(dds_airway),
                          stringsAsFactors = FALSE)
    library("AnnotationDbi")
    library("org.Hs.eg.db")
    anno_df$gene_name <- mapIds(org.Hs.eg.db,
                                keys = anno_df$gene_id,
                                column = "SYMBOL",
                                keytype = "ENSEMBL",
                                multiVals = "first")
    rownames(anno_df) <- anno_df$gene_id
    bg_ids <- rownames(dds_airway)[rowSums(counts(dds_airway)) > 0]
    library(topGO)
    pca2go_airway <- pca2go(rld_airway,
                            annotation = anno_df,
                            organism = "Hs",
                            ensToGeneSymbol = TRUE,
                            background_genes = bg_ids)

    ## End(Not run)

[Package pcaExplorer version 2.20.2 Index]