enrichmentTest {benchdamic} | R Documentation

## enrichmentTest

### Description

Perform the Fisher exact test for all the possible 2x2 contingency tables, considering differential abundance direction and enrichment variable.

### Usage

    enrichmentTest(method, enrichmentCol, alternative = "greater")

### Arguments

`method` | Output of differential abundance detection method in which DA information is extracted by the `getDA` function and the information related to enrichment is appropriately added through the `addKnowledge`.
`enrichmentCol` | name of the column containing information for enrichment analysis.
`alternative` | indicates the alternative hypothesis and must be one of `"two.sided"`, `"greater"` or `"less"`. You can specify just the initial letter. Only used in the 2 by 2 case.

### Value

a list of objects:

- `data` a `data.frame` object with DA directions, statistics, and feature names;

- `tables` a list of 2x2 contingency tables;

- `tests` the list of Fisher exact tests' p-values for each contingency table;

- `summaries` a list with the first element of each contingency table and its p-value (for graphical purposes);

### See Also

`extractDA`, `addKnowledge`, and `createEnrichment`

### Examples

    data("ps_plaque_16S")
    data("microbial_metabolism")

    # Extract genera from the phyloseq tax_table slot
    genera <- phyloseq::tax_table(ps_plaque_16S)[, "GENUS"]
    # Genera as rownames of microbial_metabolism data.frame
    rownames(microbial_metabolism) <- microbial_metabolism$Genus
    # Match OTUs to their metabolism
    priorInfo <- data.frame(genera,
        "Type" =  microbial_metabolism[genera, "Type"])
    # Unmatched genera becomes "Unknown"
    unknown_metabolism <- is.na(priorInfo$Type)
    priorInfo[unknown_metabolism, "Type"] <- "Unknown"
    priorInfo$Type <- factor(priorInfo$Type)
    # Add a more informative names column
    priorInfo[, "newNames"] <- paste0(rownames(priorInfo), priorInfo[, "GENUS"])

    # DA Analysis
    # Add scaling factors
    ps_plaque_16S <- norm_edgeR(object = ps_plaque_16S, method = "TMM")
    # DA analysis
    da.limma <- DA_limma(
        object = ps_plaque_16S,
        design = ~ 1 + HMP_BODY_SUBSITE,
        coef = 2,
        norm = "TMM"
    )

    DA <- getDA(method = da.limma, slot = "pValMat", colName = "adjP",
        type = "pvalue", direction = "logFC", threshold_pvalue = 0.05,
        threshold_logfc = 1, top = NULL)
    # Add a priori information
    DA_info <- addKnowledge(method = DA, priorKnowledge = priorInfo,
        enrichmentCol = "Type", namesCol = "newNames")
    # Create contingency tables and compute F tests
    DA_info_enriched <- enrichmentTest(method = DA_info, enrichmentCol = "Type",
        alternative = "greater")

[Package benchdamic version 1.0.0 Index]