PomaBoxplots: Classical Boxplots

In POMA: User-friendly Workflow for Pre-processing and Statistical Analysis of Mass Spectrometry Data

Description

PomaBoxplots() generates a boxplot for subjects or features. This boxplot can help in the comparison between pre and post normalized data and in the "validation" of the normalization process.

Usage

PomaBoxplots(
  data,
  group = "samples",
  jitter = TRUE,
  feature_name = NULL,
  label_size = 10
)

Arguments

data	A MSnSet object. First pData column must be the subject group/type.
group	Groupping factor for the plot. Options are "samples" and "features". Option "samples" (default) will create a boxplot for each sample and option "features" will create a boxplot of each variable.
jitter	Logical. If it's TRUE (default), the boxplot will show all points.
feature_name	A vector with the name/s of feature/s to plot. If it's NULL (default) a boxplot of all features will be created.
label_size	Numeric indicating the size of x-axis labels.

Value

A ggplot2 object.

Author(s)

Pol Castellano-Escuder

Examples

data("st000284")

# samples
PomaBoxplots(st000284)

# features
PomaBoxplots(st000284, group = "features")
             
# concrete features
PomaBoxplots(st000284, group = "features", 
             feature_name = c("ornithine", "orotate"))

POMA documentation built on Nov. 8, 2020, 6:26 p.m.