OrthoMCL

OrthoMCL is a software framework for identifying orthologous gene groups across multiple genomes. It combines sequence similarity data with a clustering approach to group proteins into orthologs and co-orthologs, while accommodating in-paralogs that arise after speciation. The method typically relies on all-vs-all protein comparisons, usually generated by BLASTP, and then applies the Markov Clustering (MCL) algorithm to a graph of protein relationships. OrthoMCL uses reciprocal best hits and normalization steps to reduce biases from gene length and uneven species representation, aiming to separate true orthologs from paralogs.

Workflow and methodology: input consists of protein sequences from several genomes. An all-vs-all similarity search produces pairwise scores, which are formatted for OrthoMCL and loaded into a relational database. Edges in the similarity graph are weighted and filtered, and the MCL algorithm is run with an inflation parameter that controls cluster granularity. The resulting clusters are interpreted as ortholog groups, with within-group paralogs from the same species identified as in-paralogs or co-orthologs as appropriate.

Output and applications: the primary product is a collection of ortholog groups (OGs), each containing one or more proteins from one or more species. OGs can include multiple members from a single species when in-paralogs are present. OrthoMCL OGs support functional annotation transfer, comparative genomics, and phylogenomic analyses, enabling researchers to study gene family evolution, conservation, and diversification across lineages.

Implementation notes: OrthoMCL is distributed as a pipeline of scripts that operate with a relational database (often MySQL) and require sequence data, BLAST results, and appropriate computational resources. The inflation parameter and filtering thresholds are common points for tuning based on dataset size and duplication level.