ArticleBMC genomics2017
Orthonome - a new pipeline for predicting high quality orthologue gene sets applicable to complete and draft genomes.
Article in BMC genomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed.
- Transcriptomic analyses of labial glands and gut tissue from two wax moths, Achroia grisella and Galleria mellonella.G3 (Bethesda, Md.) · 2026Article
- Chromosome-scale genome of Culicoides brevitarsis provides a resource for comparative and vector biology studies.Parasites & vectors · 2026Article
- Transcriptomic Temperature Stress Responses Show Differentiation Between Biomes for Diverse Plants.Genome biology and evolution · 2025Article
- Uncovering transcriptional reprogramming during callus development in soybean: insights and implications.Frontiers in plant science · 2023Article
- Tripartite factors leading to molecular divergence between human and murine smooth muscle.PloS one · 2020Article
- OrthoVenn2: a web server for whole-genome comparison and annotation of orthologous clusters across multiple species.Nucleic acids research · 2019Article
- Genomic changes associated with adaptation to arid environments in cactophilic Drosophila species.BMC genomics · 2019Article
- Divergent evolutionary trajectories following speciation in two ectoparasitic honey bee mites.Communications biology · 2019Article
- De-Extinction.Genes · 2018Review
- New Tools in Orthology Analysis: A Brief Review of Promising Perspectives.Frontiers in genetics · 2017Review
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5 authors.
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Abstract
backgroundDistinguishing orthologous and paralogous relationships between genes across multiple species is essential for comparative genomic analyses. Various computational approaches have been developed to resolve these evolutionary relationships, but strong trade-offs between precision and recall of orthologue prediction remains an ongoing challenge.
resultsHere we present Orthonome, an orthologue prediction pipeline, designed to reduce the trade-off between orthologue capture rates (recall) and accuracy of multi-species orthologue prediction. The pipeline compares sequence domains and then forms sequence-similar clusters before using phylogenetic comparisons to identify inparalogues. It then corrects sequence similarity metrics for fragment and gene length bias using a novel scoring metric capturing relationships between full length as well as fragmented genes. The remaining genes are then brought together for the identification of orthologues within a phylogenetic framework. The orthologue predictions are further calibrated along with inparalogues and gene births, using synteny, to identify novel orthologous relationships. We use 12 high quality Drosophila genomes to show that, compared to other orthologue prediction pipelines, Orthonome provides orthogroups with minimal error but high recall. Furthermore, Orthonome is resilient to suboptimal assembly/annotation quality, with the inclusion of draft genomes from eight additional Drosophila species still providing >6500 1:1 orthologues across all twenty species while retaining a better combination of accuracy and recall than other pipelines. Orthonome is implemented as a searchable database and query tool along with multiple-sequence alignment browsers for all sets of orthologues. The underlying documentation and database are accessible at http://www.orthonome.com .
conclusionWe demonstrate that Orthonome provides a superior combination of orthologue capture rates and accuracy on complete and draft drosophilid genomes when tested alongside previously published pipelines. The study also highlights a greater degree of evolutionary conservation across drosophilid species than earlier thought.
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