addKnowledge: addKnowledge

In mcalgaro93/benchdamic: Benchmark of differential abundance methods on microbiome data

addKnowledge

Description

Add a priori knowledge for each feature tested by a method.

Usage

addKnowledge(method, priorKnowledge, enrichmentCol, namesCol = NULL)

Arguments

method	Output of differential abundance detection method in which DA information is extracted by the getDA function.
priorKnowledge	data.frame (with feature names as row.names) containing feature level metadata.
enrichmentCol	name of the column containing information for enrichment analysis.
namesCol	name of the column containing new names for features (default namesCol = NULL).

Value

A data.frame with a new column containing information for enrichment analysis.

See Also

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

# Make sure the subject ID variable is a factor
phyloseq::sample_data(ps_plaque_16S)[, "RSID"] <- as.factor(
    phyloseq::sample_data(ps_plaque_16S)[["RSID"]])

# 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 + RSID + HMP_BODY_SUBSITE,
    coef = "HMP_BODY_SUBSITESupragingival Plaque",
    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")

mcalgaro93/benchdamic documentation built on Nov. 28, 2022, 6:55 p.m.