pcaPlot: Simple PCA analysis from table

In Roleren/ORFik: Open Reading Frames in Genomics

Simple PCA analysis from table

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.

Usage

pcaPlot(
  table,
  path = NULL,
  group = sub("_r[0-9]+$", "", colnames(table)),
  replicate = sub(".*_r([0-9]+)$", "\\1", colnames(table)),
  PCA_X = "PC1",
  PCA_Y = "PC2",
  title = "PCA analysis by CDS fpkm",
  subtitle = paste("Numer of genes/regions:", nrow(table)),
  plot.ext = ".pdf",
  return.data = FALSE
)

Arguments

table	data.table, e.g. countTable(df, "cds", type = "fpkm"), a data.table of counts per column (default normalized fpkm values).
path	default NULL, else character path to file to save. File saved as "PCAplot_(experiment name)(plot.ext)"
group	character vector of equal size to nrow of dt, default group = sub("_r[0-9]+$", "", colnames(table))
replicate	haracter vector of equal size to nrow of dt, sub(".*_r([0-9]+)$", "\1", colnames(table))
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
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

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
df <- df[df$libtype %in% c("RNA", "RFP"),]
table <- countTable(df, "cds", type = "fpkm")
pcaPlot(table)

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