regenrich_diffExpr {RegEnrich} | R Documentation

## Differential expression analysis step

### Description

This is the first step of RegEnrich analysis. differential expression analysis by this function needs to be performed on a 'RegenrichSet' object.

### Usage

    regenrich_diffExpr(object, ...)

    ## S4 method for signature 'RegenrichSet'
    regenrich_diffExpr(object, ...)

### Arguments

`object` | a 'RegenrichSet' object, which is initialized by `RegenrichSet` function.
`...` | arguments for differential analysis. After constructing a 'RegenrichSet' object, all arguments for RegEnrich analysis have been initialized and stored in 'paramsIn“ slot. while the arguments for differential analysis can be re-specified here. These arguments include 'method', 'minMeanExpr', 'design', 'reduced', 'contrast', 'coef', 'name', 'fitType', 'sfType', 'betaPrior', 'minReplicatesForReplace', 'useT', 'minmu', 'parallel', 'BPPARAM', 'altHypothesis', 'listValues', 'cooksCutoff', 'independentFiltering', 'alpha', 'filter', 'theta', 'filterFun', 'addMLE', 'blind', 'ndups', 'spacing', 'block', 'correlation', 'weights', 'proportion', 'stdev.coef.lim', 'trend', 'robust', and 'winsor.tail.p'. See `RegenrichSet` function for more details about these arguments.

### Value

This function returns a 'RegenrichSet' object with an updated 'resDEA' slot, which is a 'DeaSet' object, and an updated 'paramsIn' slot. See `newDeaSet` function for more details about 'DeaSet' class. If an argument not in the above list is specified in the regenrich_diffExpr function, a warning or error will be raised.

### See Also

Initialization of a 'RegenrichSet' object `RegenrichSet`,and next step `regenrich_network`.

### Examples

    # library(RegEnrich)
    data("Lyme_GSE63085")
    data("TFs")

    data = log2(Lyme_GSE63085$FPKM + 1)
    colData = Lyme_GSE63085$sampleInfo

    # Take first 2000 rows for example
    data1 = data[seq(2000), ]

    design = model.matrix(~0 + patientID + week, data = colData)

    # Initializing a 'RegenrichSet' object
    object = RegenrichSet(expr = data1,
                          colData = colData,
                          method = 'limma', minMeanExpr = 0,
                          design = design,
                          contrast = c(rep(0, ncol(design) - 1), 1),
                          networkConstruction = 'COEN',
                          enrichTest = 'FET')
    # Using the predifined parameters in the previous step
    (object = regenrich_diffExpr(object))

    # re-specifying parameter 'minMeanExpr'
    print(slot(object, 'paramsIn')$minMeanExpr)
    (object = regenrich_diffExpr(object, minMeanExpr = 1))
    print(slot(object, 'paramsIn')$minMeanExpr)

    # Unrecognized argument 'unrecognizedArg' (Error)
    # object = regenrich_diffExpr(object, minMeanExpr = 1,
    #                             unrecognizedArg = 23)

    # Argument not for differential expression analysis (Warning)
    # print(slot(object, 'paramsIn')$networkConstruction)
    # (object = regenrich_diffExpr(object, minMeanExpr = 1,
    #                              networkConstruction = 'GRN'))
    # print(slot(object, 'paramsIn')$networkConstruction) # not changed

[Package RegEnrich version 1.0.1 Index]