pcaExperiment {ORFik} | R Documentation

## Simple PCA analysis

### Description

Detect outlier libraries with PCA analysis. Will output PCA plot of PCA component 1 (x-axis) vs PCA component 2 (y-axis) for each library (colored by library), shape by replicate. Will be extended to allow batch correction in the future.

### Usage

    pcaExperiment(
      df,
      output.dir = NULL,
      table = countTable(df, "cds", type = "fpkm"),
      title = "PCA analysis by CDS fpkm",
      subtitle = paste("Numer of genes/regions:", nrow(table)),
      plot.ext = ".pdf",
      return.data = FALSE,
      color.by.group = TRUE
    )

### Arguments

`df` | an ORFik `experiment`
`output.dir` | default NULL, else character path to directory. File saved as "PCAplot_(experiment name)(plot.ext)"
`table` | data.table, default countTable(df, "cds", type = "fpkm"), a data.table of counts per column (default normalized fpkm values).
`title` | character, default "CDS fpkm".
`subtitle` | character, default: `paste("Numer of genes:", nrow(table))`
`plot.ext` | character, default: ".pdf". Alternatives: ".png" or ".jpg". Note that in pdf format the complex correlation plots become very slow to load!
`return.data` | logical, default FALSE. Return data instead of plot
`color.by.group` | logical, default TRUE. Colors in PCA plot represent unique library groups, if FALSE. Color each sample in seperate color (harder to distinguish for > 10 samples)

### Value

ggplot or invisible(NULL) if output.dir is defined or < 3 samples. Returns data.table with PCA analysis if return.data is TRUE.

### Examples

    df <- ORFik.template.experiment()
    # Select only Ribo-seq and RNA-seq
    pcaExperiment(df[df$libtype %in% c("RNA", "RFP"),])

[Package ORFik version 1.14.7 Index]