Creates an agglomerated dataframe from feature counts, sample metadata, and taxonomy annotations.
agglomerated(features, samples, taxonomy, sample_col, otu_col = "otu_id", count_col = "count")
| features | a matrix-like object with features as columns and samples as rows |
|---|---|
| samples | an optional dataframe containing sample metadata, with each sample a separate row |
| taxonomy | an optional dataframe containing taxonomy information, with each taxa a row and rownames providing taxa id |
| sample_col | a string giving the name of the column in `samples` corresponding to the rows in the features table |
| otu_col | a string giving the desired name of the otu column in the resulting dataframe |
| count_col | a string giving the desired name of the counts column in the resulting dataframe |
A dataframe with each row representing a unique feature+sample+count observation, plus any metadata about the sample and any taxonomic annotation about the feature. This results in a lot of repetition, but is very easy to manipulate with dplyr and the tidyverse.