kruskalWallis: Kruskal-Wallis rank sum tests on a 'SummarizedExperiment'...

In GaelleLefort/ASICS: Automatic Statistical Identification in Complex Spectra

Description

Perform Kruskal-Wallis tests on a SummarizedExperiment object obtained with the formatForAnalysis function

Usage

kruskalWallis(
  analysis_data,
  condition,
  alpha = 0.05,
  type.data = "quantifications",
  ...
)

Arguments

analysis_data	A SummarizedExperiment object obtained with the formatForAnalysis function.
condition	The name of the design variable (two level factor) specifying the group of each sample.
alpha	Cutoff for adjusted p-values. Default to 0.05.
type.data	Type of data used for the analyses (e.g.,
...	Arguments to be passed to p.adjust such as the correction method to use with the method argument. "quantifications", "buckets"...). Default to "quantifications".

Value

A S4 object of class AnalysisResults containing test results.

See Also

AnalysisResults

Examples

# Import quantification results
if (require("ASICSdata", quietly = TRUE)) {
  quantif_path <- system.file("extdata", "results_ASICS.txt",
                              package = "ASICSdata")
  quantification <- read.table(quantif_path, header = TRUE, row.names = 1)

  # Import design
  design <- read.table(system.file("extdata", "design_diabete_example.txt",
                                   package = "ASICSdata"), header = TRUE)
  design$condition <- factor(design$condition)

  # Create object for analysis and remove features with more than 25% of
  # zeros
  analysis_obj <- formatForAnalysis(quantification,
                                    zero.threshold = 25, design = design)
  res_tests <- kruskalWallis(analysis_obj, "condition", method = "BH")
}

GaelleLefort/ASICS documentation built on July 19, 2020, 2:08 p.m.