PomaBoxplots: Classical Boxplots

Description Usage Arguments Value Author(s) Examples

View source: R/PomaBoxplots.R

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

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

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.

legend_position

Character indicating the legend position. Options are "none", "top", "bottom", "left", and "right".

Value

A ggplot2 object.

Author(s)

Pol Castellano-Escuder

Examples

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data("st000284")

# samples
PomaBoxplots(st000284)

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

pcastellanoescuder/POMA documentation built on May 14, 2021, 11:07 p.m.