Toy MOAT Microbiome Dataset

A small, simulated SummarizedExperiment object for examples and testing. This dataset contains artificial read counts for 50 taxa across 40 samples, along with sample metadata including an outcome and a batch variable. It has been generated to exhibit a strong batch effect on the first half of the taxa.

Usage

data(toy_moat)

Format

A SummarizedExperiment object with 50 features (taxa) and 40 samples.

assays

A single assay named "counts" containing a matrix of simulated read counts (Poisson distributed).

colData

A DataFrame containing sample metadata:

• sample_id: Unique sample identifier.

• outcome: Binary outcome variable ("Control", "Disease").

• batch: Batch variable ("Batch_1", "Batch_2").

Source

Simulated data. See data-raw/simulate_toy_data.R for the generation script.

Examples

data("toy_moat")

# Inspect the object dimensions
dim(toy_moat)
#> [1] 50 40

# Check sample metadata
head(SummarizedExperiment::colData(toy_moat))
#> DataFrame with 6 rows and 3 columns
#>       sample_id     outcome       batch
#>     <character> <character> <character>
#> S01         S01     Control     Batch_1
#> S02         S02     Control     Batch_1
#> S03         S03     Control     Batch_1
#> S04         S04     Disease     Batch_1
#> S05         S05     Control     Batch_1
#> S06         S06     Disease     Batch_1

# View assay counts for the first 5 taxa and 5 samples
SummarizedExperiment::assay(toy_moat)[1:5, 1:5]
#>           S01 S02 S03 S04 S05
#> Taxon_001  89 103 103  99  82
#> Taxon_002  96  96  89 101 109
#> Taxon_003  92  92 123 102  94
#> Taxon_004 110 103  76 112 109
#> Taxon_005  98 110 103  94 106