runDiffMeanAnalysis {MEAL} | R Documentation

## Run differential mean analysis

### Description

Run differential mean analysis using t-moderated statistics. This function relies on `lmFit` from limma package.

### Usage

    runDiffMeanAnalysis(
      set,
      model,
      weights = NULL,
      method = "ls",
      max_iterations = 100,
      betas = TRUE,
      resultSet = TRUE,
      warnings = TRUE
    )

### Arguments

`set` | Matrix, `GenomicRatioSet`, `SummarizedExperiment` or `ExpressionSet`.
`model` | Model matrix or formula to get model matrix from `set`.
`weights` | weights used in the lmFit model.
`method` | String indicating the method used in the regression: "ls" or "robust". (Default: "ls")
`max_iterations` | Numeric indicating the maximum number of iterations done in the robust method.
`betas` | If `set` is a `GenomicRatioSet`, should beta values be used? (Default: TRUE)
`resultSet` | Should results be encapsulated in a `resultSet`? (Default: TRUE)
`warnings` | Should warnings be displayed? (Default:TRUE)

### Value

`MArrayLM` or `resultSet` with the result of the differential mean analysis.

### Examples

    if (require(minfiData)){
     mvalues <- getM(MsetEx)[1:100, ]
     model <- model.matrix(~ Sample_Group, data = pData(MsetEx))
     res <- runDiffMeanAnalysis(mvalues, model, method = "ls")
     res
    }

[Package MEAL version 1.22.0 Index]