ArticlePloS one2014
Orthology detection combining clustering and synteny for very large datasets.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.
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48 citing papers in PubMed.
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- Quantifying the influence of genetic context on duplicated mammalian genes.bioRxiv : the preprint server for biology · 2025Article
- Efficient gene orthology inference via large-scale rearrangements.Algorithms for molecular biology : AMB · 2023Article
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- A high-quality reference genome for the fission yeast Schizosaccharomyces osmophilus.G3 (Bethesda, Md.) · 2023Article
- Recombination Facilitates Adaptive Evolution in Rhizobial Soil Bacteria.Molecular biology and evolution · 2021Article
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- Heuristic algorithms for best match graph editing.Algorithms for molecular biology : AMB · 2021Article
- Evolutionary Perspective and Expression Analysis of Intronless Genes Highlight the Conservation of Their Regulatory Role.Frontiers in genetics · 2021Article
- Genome compartmentalization predates species divergence in the plant pathogen genus Zymoseptoria.BMC genomics · 2020Article
- A New Analysis of Archaea-Bacteria Domain Separation: Variable Phylogenetic Distance and the Tempo of Early Evolution.Molecular biology and evolution · 2020Article
- Dual RNA-seq of Orientia tsutsugamushi informs on host-pathogen interactions for this neglected intracellular human pathogen.Nature communications · 2020Article
- Best match graphs and reconciliation of gene trees with species trees.Journal of mathematical biology · 2020Article
- Symbiosis genes show a unique pattern of introgression and selection within aMicrobial genomics · 2020Article
- Reciprocal best match graphs.Journal of mathematical biology · 2020Article
- Reconstruction of time-consistent species trees.Algorithms for molecular biology : AMB · 2020Article
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9 authors.
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Abstract
The elucidation of orthology relationships is an important step both in gene function prediction as well as towards understanding patterns of sequence evolution. Orthology assignments are usually derived directly from sequence similarities for large data because more exact approaches exhibit too high computational costs. Here we present PoFF, an extension for the standalone tool Proteinortho, which enhances orthology detection by combining clustering, sequence similarity, and synteny. In the course of this work, FFAdj-MCS, a heuristic that assesses pairwise gene order using adjacencies (a similarity measure related to the breakpoint distance) was adapted to support multiple linear chromosomes and extended to detect duplicated regions. PoFF largely reduces the number of false positives and enables more fine-grained predictions than purely similarity-based approaches. The extension maintains the low memory requirements and the efficient concurrency options of its basis Proteinortho, making the software applicable to very large datasets.
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