OrthoFinder: solving fundamental biases in whole genome comparisons dramatically improves orthogroup inference accuracy

Identifying homology relationships between sequences is fundamental to biological research. Here we provide a novel orthogroup inference algorithm called OrthoFinder that solves a previously undetected gene length bias in orthogroup inference, resulting in significant improvements in accuracy. Using...

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Bibliographic Details
Published in:Genome Biology 2015-08, Vol.16 (1), p.157-157, Article 157
Main Authors: Emms, David M, Kelly, Steven
Format: Article
Language:English
Subjects:
Acids
Algorithms
Bias
Biochemistry
Bioinformatics
Biological research
Gene families
Genes
Genes, Plant
Genomes
Genomics
Genomics - methods
Homology
Methods
Molecular biology
Multigene Family
Phylogenetics
Phylogeny
Proteins - genetics
Software
Transcription Factors - genetics
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Summary:Identifying homology relationships between sequences is fundamental to biological research. Here we provide a novel orthogroup inference algorithm called OrthoFinder that solves a previously undetected gene length bias in orthogroup inference, resulting in significant improvements in accuracy. Using real benchmark datasets we demonstrate that OrthoFinder is more accurate than other orthogroup inference methods by between 8 % and 33 %. Furthermore, we demonstrate the utility of OrthoFinder by providing a complete classification of transcription factor gene families in plants revealing 6.9 million previously unobserved relationships.
ISSN:1474-760X
1474-7596
1474-760X
DOI:10.1186/s13059-015-0721-2