FOAM (Functional Ontology Assignments for Metagenomes): a Hidden Markov Model (HMM) database with environmental focus.
Bottom Line: 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.
Affiliation: Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA Division of Biology, Kansas State University, Manhattan, Kansas 66506, USA.Show MeSH
Related in: MedlinePlus
Mentions: The reduced size of the resultant FOAM database, compared to non-specific sequence databases, was a first step towards significant improvement in the speed and specificity of similarity searches. In addition, to improve upon the sensitivity of conventional heuristic alignment programs, we turned each KO set into Hidden Markov Models (HMMs; 19) by fetching their corresponding protein family (Pfam) profiles (20) as described in Figure 1. This step generated a sizeable number of conflicts (several Pfam per KO and vice versa) that were automatically resolved by functional assignments to KO. For the few remaining unresolved assignations, the corresponding set of sequences was manually split according to the topology of their phylogenetic trees. At this point the HMMs were re-trained from the new pool of sequences.
Affiliation: Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA Division of Biology, Kansas State University, Manhattan, Kansas 66506, USA.