kruskalWallis {ASICS} | R Documentation

## Kruskal-Wallis rank sum tests on a `SummarizedExperiment` object

### 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")
    }

[Package ASICS version 2.6.1 Index]