plotAnnotatedPCA {GenomicSuperSignature} | R Documentation

## Two-dimentional PCA plot with the PC annotation

### Description

Two-dimentional PCA plot with the PC annotation

### Usage

    plotAnnotatedPCA(
      dataset,
      RAVmodel,
      PCnum,
      val_all = NULL,
      scoreCutoff = 0.5,
      nesCutoff = NULL,
      color_by = NULL,
      color_lab = NULL,
      trimed_pathway_len = 45
    )

### Arguments

`dataset` | A gene expression profile to be validated. Different classes of objects can be used including ExpressionSet, SummarizedExperiment, RangedSummarizedExperiment, or matrix. Rownames (genes) should be in symbol format. If it is a matrix, genes should be in rows and samples in columns.
`RAVmodel` | PCAGenomicSignatures-class object
`PCnum` | A numeric vector length of 2. It should be between 1 and 8.
`val_all` | The output from `validate`
`scoreCutoff` | A numeric value for the minimum correlation. Default 0.5.
`nesCutoff` | A numeric value for the minimum NES. Default is `NULL` and the suggested value is 3.
`color_by` | A named vector with the feature you want to color by. Name should be match with the sample names of the dataset.
`color_lab` | A name for color legend. If this argument is not provided, the color legend will be labeled as "Color By" by default.
`trimed_pathway_len` | Positive inter values, which is the display width of pathway names. Default is 45.

### Value

Scatter plot and the table with annotation. If enriched pathway didn't pass the `scoreCutoff` the table will be labeled as "No significant pathways". If any enriched pathway didn't pass the `nesCutoff`, it will labeled as NA.

### Examples

    data(miniRAVmodel)
    library(bcellViper)
    data(bcellViper)
    ## Not run:
    plotAnnotatedPCA(exprs(dset), miniRAVmodel, PCnum = c(1,2))

    ## End(Not run)

[Package GenomicSuperSignature version 1.2.1 Index]