geva.summarize: Summarizes the GEVAInput

In sbcblab/geva: Gene Expression Variation Analysis (GEVA)

Description

Performs the summarization step by calculating the central points and variation estimates of logFC values from the input data.

Usage

geva.summarize(
  ginput,
  summary.method = options.summary,
  variation.method = options.variation,
  ...
)

options.summary
# c("mean", "median")

options.variation
# c("sd", "var", "mad")

Arguments

ginput	a GEVAInput object
summary.method	single character, method used to calculate the central (summarized) logFC values
variation.method	single character, method used to calculate the distribution degree (variation) of the logFC values
...	additional arguments. Accepts verbose (logical, default is TRUE) to enable or disable printing the current progress

Details

The options.summary refer to the available operations to calculate central logFC values (mean or median), whereas options.variation presents three functions to calculate logFC variation (sd: Standard Deviation; var: Variance; and mad: Median Absolute Deviation). Moreover, all those operations include a weighted counterpart applied using the weights table from the GEVAInput object.

Value

A GEVASummary object

See Also

base::mean(), stats::median()

stats::var(), stats::sd(), stats::mad()

Examples

## Summarization of a randomly generated input
ginput <- geva.ideal.example()     # Generates a random input example
gsummary <- geva.summarize(ginput) # Summarizes with the default parameters
plot(gsummary)                     # Plots the summarized data

sbcblab/geva documentation built on March 15, 2021, 10:08 p.m.