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

By David M. Emms, Steven Kelly. Genome Biology, 2015

3,130 citations recorded by the source corpus.

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.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/e41081c55d4a6efc4415eb0dc9b8e57eb7b353fa

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In Molecular Biology

Citations in the corpus

Subgenome dominance in an interspecific hybrid, synthetic allopolyploid, and a 140 year old naturally established neo-allopolyploid monkeyflower (2016, background): “4 (Emms and Kelly, 2015) from 499 translated transcriptome and full genome data sets with default parameters.”
PlantTFDB 4.0: toward a central hub for transcription factors and regulatory interactions in plants (2016, methodology): “Given the recent reported methodology bias for OrthoMCL (28), we employed a new tool OrthoFinder (28) to infer orthologous groups (OGs) for proteins from 156 species with genome sequences (Figure 3), and got 2368 TF OGs for all species, 800 TF OGs for 17 representative species (Supplementary Table S”
IQ-TREE 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era (2019, background): “2018), OrthoFinder (Emms and Kelly 2015), and QIIME 2 (Bolyen et al.”
OrthoVenn2: a web server for whole-genome comparison and annotation of orthologous clusters across multiple species (2019, methodology): “The second is graphbased, and this methodology is found in tools including PanOCT (8), OrthoFinder (9), OrthoMCL (10), COCOCL (11), OrthoDB (12), OMA (13) and Roary (14).”
Mutation severity spectrum of rare alleles in the human genome is predictive of disease type (2019, methodology): “The orthologous groups of human proteins were obtained by OrthoFinder [88] applied to a set of representative vertebrate proteomes.”
PLAZA 4.0: an integrative resource for functional, evolutionary and comparative plant genomics (2017, methodology): “Some programs within the workflow have been replaced in favor of alternatives offering better performance or efficiency: NCBI BLAST (29) has been replaced by DIAMOND (30), while OrthoMCL (31) has been replaced by OrthoFinder (32).”
STAG: Species Tree Inference from All Genes (2018, methodology): “It can be launched with a single command directly from a set of OrthoFinder results.”
A taxonomic note on the genus Lactobacillus: Description of 23 novel genera, emended description of the genus Lactobacillus Beijerinck 1901, and union of Lactobacillaceae and Leuconostocaceae. (2020, methodology): “3 [37] with MMseqs2 version d36de [38] as the sequence search program.”
Phylogenomics provides a robust topology of the major cnidarian lineages and insights on the origins of key organismal traits (2018, positive): “We show that given the same input data, the Agalma pipeline under default parameters [45] tended to produce larger though sparser data matrices than the OF-PTP procedure [46, 47].”