FOAM (Functional Ontology Assignments for Metagenomes):…

FOAM (Functional Ontology Assignments for Metagenomes): a Hidden Markov Model (HMM) database with environmental focus by Emmanuel Prestat, et al. (Nucl. Acids Res. (2014) doi: 10.1093/nar/gku702 )

Abstract:

A new functional gene database, FOAM (Functional Ontology Assignments for Metagenomes), was developed to screen environmental metagenomic sequence datasets. FOAM provides a new functional ontology dedicated to classify gene functions relevant to environmental microorganisms based on Hidden Markov Models (HMMs). Sets of aligned protein sequences (i.e. ‘profiles’) were tailored to a large group of target KEGG Orthologs (KOs) from which HMMs were trained. The alignments were checked and curated to make them specific to the targeted KO. Within this process, sequence profiles were enriched with the most abundant sequences available to maximize the yield of accurate classifier models. An associated functional ontology was built to describe the functional groups and hierarchy. FOAM allows the user to select the target search space before HMM-based comparison steps and to easily organize the results into different functional categories and subcategories. FOAM is publicly available at http://portal.nersc.gov/project/m1317/FOAM/.

Aside from its obvious importance for genomics and bioinformatics, I mention this because the authors point out:

A caveat of this approach is that we did not consider the quality of the tree in the tree-splitting step (i.e. weakly supported branches were equally treated as strongly supported ones), producing models of different qualities. Nevertheless, we decided that the approach of rational classification is better than no classification at all. In the future, the groups could be recomputed, or split more optimally when more data become available (e.g. more KOs). From each cluster related to the KO in process, we extracted the alignment from which HMMs were eventually built.

I take that to mean that this “ontology” represents no unchanging ground truth but rather an attempt to enhance the “…screening of environmental metagenomic and metatranscriptomic sequence datasets for functional genes.”

As more information is gained, the present “ontology” can and will change. Those future changes create the necessity to map those changes and the facts that drove them.

I first saw this in a tweet by Jonathan Eisen

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