LSGFA: Domain-based infraspecific large-scale prokaryotic genomic orthologous gene inference

Orthologous gene inference is a crucial technical challenge in evolutionary biology. It typically depends on sequence similarity searches and employs a graph clustering method to infer homologous gene families. However, the all-vs-all sequence similarity search is time-consuming for large-scale genome datasets. In this work, we present LSGFA, a method that detects subgraphs based on the similarity of protein domain architectures and then performs graph clustering within each subgraph, corresponding to sequences that share similar compositions of protein domains. LSGFA carries out four steps in the analysis workflow: protein domain annotation, initial clustering based on Pfam domain architecture, SSN-based clustering, and detection of pan-genomic patterns. The test results demonstrated that LSGFA’s performance is between that of Roary and OrthoFinder. It took less time than OrthoFinder and identified more core genes than Roary.