The Biological Observation Matrix (BIOM) format or: how I learned to stop worrying and love the ome-ome

By Daniel McDonald, José Carlos Clemente, J. Kuczynski, J. Rideout, Jesse Stombaugh, Doug Wendel, Andreas Wilke, Susan M. Huse, John Hufnagle, Folker Meyer and 2 more. GigaScience, 2012

774 citations recorded by the source corpus.

BackgroundWe present the Biological Observation Matrix (BIOM, pronounced “biome”) format: a JSON-based file format for representing arbitrary observation by sample contingency tables with associated sample and observation metadata. As the number of categories of comparative omics data types (collectively, the “ome-ome”) grows rapidly, a general format to represent and archive this data will facilitate the interoperability of existing bioinformatics tools and future meta-analyses.FindingsThe BIOM file format is supported by an independent open-source software project (the biom-format project), which initially contains Python objects that support the use and manipulation of BIOM data in Python programs, and is intended to be an open development effort where developers can submit implementations of these objects in other programming languages.ConclusionsThe BIOM file format and the biom-format project are steps toward reducing the “bioinformatics bottleneck” that is currently being experienced in diverse areas of biological sciences, and will help us move toward the next phase of comparative omics where basic science is translated into clinical and environmental applications. The BIOM file format is currently recognized as an Earth Microbiome Project Standard, and as a Candidate Standard by the Genomic Standards Consortium.

Subfields: Ecology, Health, Toxicology and Mutagenesis, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/1fb73381d2499f66f0f19f318dcf80922a366cec

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

In Health, Toxicology and Mutagenesis

P. Polymenakou

In Molecular Biology

Citations in the corpus

Compact graphical representation of phylogenetic data and metadata with GraPhlAn (2015, methodology): “The export2graphlan framework can further accept the widely adopted BIOM format, both versions 1 and 2 ( McDonald et al., 2012 ).”
FunGene: the functional gene pipeline and repository (2013, methodology): “The output cluster ﬁle can be converted to BIOM (McDonald et al., 2012) format using a tool available in the mcClust package.”
Biological, physicochemical and plant health responses in lettuce and strawberry in soil or peat amended with biochar (2016, positive): “Finally, sequences of individual samples were mapped back to the representative OTUs using the “ usearch_global ” algorithm at 97% identity, and converted to an OTU table (McDonald et al., 2012).”
Metagenomics: Tools and Insights for Analyzing Next-Generation Sequencing Data Derived from Biodiversity Studies (2015, methodology): “QIIME output includes a representation of a taxonomic tree in Newick format, which can be visualized in applications such as FigTree, 142 and a file in Biom (Biological Observation Matrix) format 143 representing OTU tables.”
A Novel Sparse Compositional Technique Reveals Microbial Perturbations (2019, methodology): “TheresultingBIOM(50)tableswerethenﬁlteredforsamples greater than 1,000 reads per sample.”
BugBase predicts organism-level microbiome phenotypes (2017, methodology): “Predicting organism-level phenotypes To predict microbiome phenotypes, BugBase takes as input either a biom-formatted OTU table (JSON version) [38], for 16S data, or a QIIME-formatted OTU table (biom or classic) for WGS data.”