regenrich_rankScore {RegEnrich} | R Documentation

## Regulator scoring and ranking

### Description

As the fourth step of RegEnrich analysis, regulator ranking is followed by differential expression analysis (regenrich_diffExpr), regulator-target network inference (regenrich_network), and enrichment analysis (regenrich_enrich).

### Usage

    regenrich_rankScore(object)

    ## S4 method for signature 'RegenrichSet'
    regenrich_rankScore(object)

### Arguments

`object` | a 'RegenrichSet' object, to which `regenrich_diffExpr`, `regenrich_network`, and `regenrich_enrich` functions all have been already applied.

### Value

This function returns a 'RegenrichSet' object with an updated 'resScore' slots, which is a 'regEnrichScore' (also 'data.frame') object, and an updated 'paramsIn' slot. In the 'regEnrichScore' object there are five columns, which are 'reg' (regulator), 'negLogPDEA' (-log10(p values of differential expression analysis)), 'negLogPEnrich' (-log10(p values of enrichment analysis), 'logFC' (log2 fold changes), and 'score' (RegEnrich ranking score).

### See Also

Previous step `regenrich_enrich`.

### 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')

    # Differential expression analysis
    object = regenrich_diffExpr(object)

    # Network inference using 'COEN' method
    object = regenrich_network(object)

    # Enrichment analysis by Fisher's exact test (FET)
    object = regenrich_enrich(object)

    # Regulators ranking
    (object = regenrich_rankScore(object))

[Package RegEnrich version 1.2.0 Index]