readyomics (version 0.1.1)

add_taxa: Add taxonomic information to dana object

Description

Appends features taxonomy to the dana object tables.

Usage

add_taxa(
  dana_obj,
  taxa_table,
  taxa_rank = c("asv", "substrain", "strain", "species", "genus", "family", "order",
    "class", "phylum", "domain")
)

Value

A modified version of dana_obj, with taxonomy information added to relevant tables.

Arguments

dana_obj

A dana object returned by dana().

taxa_table

A taxonomy table data.frame with taxonomy ranks in columns and row names corresponding to feat_ids in dana object.

taxa_rank

A character string specifying the taxonomy level of input features. Accepts one of: "asv", "substrain", "strain", "species", "genus", "family", "order", "class", "phylum", or "domain".

Details

• If taxa_rank = "asv", a taxon_name is constructed by pasting the ASV ID to the species (if available) or genus name.

• For other ranks, taxon_name is taken directly from the corresponding column in taxa_table.

• All higher-level taxonomy ranks available in taxa_table are also appended.

See Also

dana() for fitting differential analysis models on omics datasets.

Examples

set.seed(123)
mock_X <- matrix(rnorm(20 * 5), nrow = 20)
colnames(mock_X) <- paste0("feat_", seq_len(5))
rownames(mock_X) <- paste0("sample_", seq_len(20))

mock_taxa <- data.frame(
  Domain = rep("Bacteria", 5),
  Phylum = c("Firmicutes", "Bacteroidota", "Proteobacteria",
             "Actinobacteriota", "Firmicutes"),
  Class = c("Bacilli", "Bacteroidia", "Gammaproteobacteria",
            "Actinobacteria", "Clostridia"),
  Order = c("Lactobacillales", "Bacteroidales", "Enterobacterales",
            "Bifidobacteriales", "Clostridiales"),
  Family = c("Lactobacillaceae", "Bacteroidaceae", "Enterobacteriaceae",
             "Bifidobacteriaceae", "Clostridiaceae"),
  Genus = c("Lactobacillus", "Bacteroides", "Escherichia",
            "Bifidobacterium", "Clostridium"),
  Species = c("acidophilus", "fragilis", "coli", "longum", "butyricum"),
  row.names = paste0("feat_", seq_len(5)),
  stringsAsFactors = FALSE
)

sample_data <- data.frame(
  sample_id = rownames(mock_X),
  group = factor(rep(c("A", "B"), each = 10)),
  time = factor(rep(c("T1", "T2"), times = 10)),
  subject_id = factor(rep(seq_len(10), each = 2)),
  stringsAsFactors = FALSE
)
rownames(sample_data) <- sample_data$sample_id

fit_df <- data.frame(
  feat_id = rep(colnames(mock_X), each = 2),
  Coefficient = rep(c("(Intercept)", "groupB"), 5),
  Estimate = rnorm(10),
  `Pr(>|t|)` = runif(10),
  padj = runif(10),
  stringsAsFactors = FALSE
)

# Mock dana object
dana_obj <- list(
  X = mock_X,
  sdata = sample_data,
  formula_rhs = ~ group,
  fit = fit_df,
  lrt = data.frame(),
  ranef = data.frame()
)
class(dana_obj) <- "dana"

# Add taxonomy
dana_obj <- dana_obj |>
  add_taxa(mock_taxa, taxa_rank = "genus")