pcaExperiment: Simple PCA analysis from ORFik experiment

In Roleren/ORFik: Open Reading Frames in Genomics

Simple PCA analysis from ORFik experiment

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,
  PCA_X = "PC1",
  PCA_Y = "PC2"
)

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, e.g. 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".
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)
PCA_X	name of priniciple component to use for x axis: valid options: PC1-PC6
PCA_Y	name of priniciple component to use for y axis: valid options: PC1-PC6

Value

ggplot if return.data is false, data.table of PCAs if return.data is TRUE, if data has < 3 samples, returns (invisible(NULL))

Examples

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

Roleren/ORFik documentation built on April 12, 2025, 5:31 a.m.