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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.

Original publication

DOI

10.1186/s13059-015-0721-2

Type

Journal article

Journal

Genome Biol

Publication Date

06/08/2015

Volume

16

Keywords

Algorithms, Genes, Plant, Genomics, Multigene Family, Phylogeny, Proteins, Software, Transcription Factors