pcaplot {pcaExplorer} | R Documentation

## Sample PCA plot for transformed data

### Description

Plots the results of PCA on a 2-dimensional space

### Usage

    pcaplot(
      x,
      intgroup = "condition",
      ntop = 500,
      returnData = FALSE,
      title = NULL,
      pcX = 1,
      pcY = 2,
      text_labels = TRUE,
      point_size = 3,
      ellipse = TRUE,
      ellipse.prob = 0.95
    )

### Arguments

`x` | A `DESeqTransform` object, with data in `assay(x)`, produced for example by either `rlog` or `varianceStabilizingTransformation`
`intgroup` | Interesting groups: a character vector of names in `colData(x)` to use for grouping
`ntop` | Number of top genes to use for principal components, selected by highest row variance
`returnData` | logical, if TRUE returns a data.frame for further use, containing the selected principal components and intgroup covariates for custom plotting
`title` | The plot title
`pcX` | The principal component to display on the x axis
`pcY` | The principal component to display on the y axis
`text_labels` | Logical, whether to display the labels with the sample identifiers
`point_size` | Integer, the size of the points for the samples
`ellipse` | Logical, whether to display the confidence ellipse for the selected groups
`ellipse.prob` | Numeric, a value in the interval [0;1)

### Value

An object created by `ggplot`, which can be assigned and further customized.

### Examples

    dds <- makeExampleDESeqDataSet_multifac(betaSD_condition = 3, betaSD_tissue = 1)
    rlt <- DESeq2::rlogTransformation(dds)
    pcaplot(rlt, ntop = 200)

[Package pcaExplorer version 2.20.2 Index]