Import data

Monday, August 25, 2025

Microbiome data science workflow

Microbiome data science workflow

Importers and converters

  • mia includes importers and converters for standard data formats
    • Importer: Import file
    • Converter: Convert R object to other format
  • You can also create TreeSE object manually

Open databases

Data resource Package # studies or datasets # samples
Curated metagenomic data (Pasolli et al. 2017) curatedMetagenomicData (Pasolli et al. 2017) 93 22,588
HoloFood (Rogers et al. 2025) HoloFoodR (Borman, Sannikov, and Lahti 2025) - 9,990
MGnify (Gurbich et al. 2023) MGnifyR (Borman, Allen, and Lahti 2025) 5129 616,138
Microbiome benchmark data (Gamboa-Tuz et al. 2025) MicrobiomeBenchmarkData (Gamboa-Tuz et al. 2025) 6 1,125
microbiomeDataSets (Lahti, Ernst, and Shetty 2025) microbiomeDataSets (Lahti, Ernst, and Shetty 2025) 6 19,100

Demonstration

library(mia)

tse <- importBIOM("file_path.biom")
print(tse)
class: TreeSummarizedExperiment 
dim: 19216 26 
metadata(0):
assays(1): counts
rownames(19216): 549322 522457 ... 200359 271582
rowData names(7): Kingdom Phylum ... Genus Species
colnames(26): CL3 CC1 ... Even2 Even3
colData names(7): X.SampleID Primer ... SampleType Description
reducedDimNames(0):
mainExpName: NULL
altExpNames(0):
rowLinks: a LinkDataFrame (19216 rows)
rowTree: 1 phylo tree(s) (19216 leaves)
colLinks: NULL
colTree: NULL

Exercises

From OMA online book, Chapter 4: Import

  • Exercise 1

References