ArticleBMC bioinformatics2018
Efficient inference of homologs in large eukaryotic pan-proteomes.
Article in BMC bioinformatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 30 citations in OpenAlex.
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- Evolutionary trends in the emergence of skeletal cell types.Evolution letters · 2025Article
- Pangenomics to understand prophage dynamics in theMicrobial genomics · 2025Article
- Lactuca super-pangenome reduces bias towards reference genes in lettuce research.BMC plant biology · 2024Article
- Quest for Orthologs in the Era of Biodiversity Genomics.Genome biology and evolution · 2024Review
- Cross-species transcriptomics reveals differential regulation of essential photosynthesis genes in Hirschfeldia incana.G3 (Bethesda, Md.) · 2024Article
- An Efficient Triplex TaqMan Quantitative PCR to Detect a Blackleg-Causing Lineage ofMicroorganisms · 2023Article
- The genome sequence of Hirschfeldia incana, a new Brassicaceae model to improve photosynthetic light-use efficiency.The Plant journal : for cell and molecular biology · 2022Article
- Sequence-based pangenomic core detection.iScience · 2022Article
- The Pectobacterium pangenome, with a focus on Pectobacterium brasiliense, shows a robust core and extensive exchange of genes from a shared gene pool.BMC genomics · 2021Article
- Pangenome Graphs.Annual review of genomics and human genetics · 2020Review
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
backgroundIdentification of homologous genes is fundamental to comparative genomics, functional genomics and phylogenomics. Extensive public homology databases are of great value for investigating homology but need to be continually updated to incorporate new sequences. As new sequences are rapidly being generated, there is a need for efficient standalone tools to detect homologs in novel data.
resultsTo address this, we present a fast method for detecting homology groups across a large number of individuals and/or species. We adopted a k-mer based approach which considerably reduces the number of pairwise protein alignments without sacrificing sensitivity. We demonstrate accuracy, scalability, efficiency and applicability of the presented method for detecting homology in large proteomes of bacteria, fungi, plants and Metazoa.
conclusionsWe clearly observed the trade-off between recall and precision in our homology inference. Favoring recall or precision strongly depends on the application. The clustering behavior of our program can be optimized for particular applications by altering a few key parameters. The program is available for public use at https://github.com/sheikhizadeh/pantools as an extension to our pan-genomic analysis tool, PanTools.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.