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

2015; BioMed Central; Volume: 16; Issue: 1 Linguagem: Inglês

10.1186/s13059-015-0721-2

1474-760X

David Emms, Steven Kelly,

Machine Learning in Bioinformatics

Abstract 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.