AI Article Synopsis
- Genomes and transcriptomes are often difficult to analyze; identifying orthologs (corresponding genes across species) is a critical but challenging step in this process.
- The Orthologous MAtrix (OMA) database is a key resource for finding orthologs, and the OMA pipeline can be run as a standalone program on Linux and Mac, supporting various job schedulers and scaling up for large data processing.
- OMA standalone allows users to integrate their own data with public genomic data and offers applications like phylogenetic analysis and identifying gene family changes or potential drug targets, and is available as open-source software.
Article Abstract
Genomes and transcriptomes are now typically sequenced by individual laboratories but analyzing them often remains challenging. One essential step in many analyses lies in identifying orthologs-corresponding genes across multiple species-but this is far from trivial. The Orthologous MAtrix (OMA) database is a leading resource for identifying orthologs among publicly available, complete genomes. Here, we describe the OMA pipeline available as a standalone program for Linux and Mac. When run on a cluster, it has native support for the LSF, SGE, PBS Pro, and Slurm job schedulers and can scale up to thousands of parallel processes. Another key feature of OMA standalone is that users can combine their own data with existing public data by exporting genomes and precomputed alignments from the OMA database, which currently contains over 2100 complete genomes. We compare OMA standalone to other methods in the context of phylogenetic tree inference, by inferring a phylogeny of Lophotrochozoa, a challenging clade within the protostomes. We also discuss other potential applications of OMA standalone, including identifying gene families having undergone duplications/losses in specific clades, and identifying potential drug targets in nonmodel organisms. OMA standalone is available under the permissive open source Mozilla Public License Version 2.0.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6633268 | PMC |
| http://dx.doi.org/10.1101/gr.243212.118 | DOI Listing |
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