The Quest for Orthologs Benchmark Service and Consensus Calls in 2020

Overview

Journal Nucleic Acids Res

Publisher Oxford University Press

Specialty Biochemistry

Date 2020 May 7

PMID 32374845

Citations 27

Authors

Adrian M Altenhoff

Javier Garrayo-Ventas

Salvatore Cosentino

David Emms

Natasha M Glover

Ana Hernandez-Plaza

Yannis Nevers

Vicky Sundesha

Damian Szklarczyk

Jose M Fernandez

Laia Codo

The Quest For Orthologs Consortium

Josep Ll Gelpi

Jaime Huerta-Cepas

Wataru Iwasaki

Steven Kelly

Odile Lecompte

Matthieu Muffato

Maria J Martin

Salvador Capella-Gutierrez

Paul D Thomas

Erik Sonnhammer

Christophe Dessimoz

Affiliations

Soon will be listed here.

Abstract

The identification of orthologs-genes in different species which descended from the same gene in their last common ancestor-is a prerequisite for many analyses in comparative genomics and molecular evolution. Numerous algorithms and resources have been conceived to address this problem, but benchmarking and interpreting them is fraught with difficulties (need to compare them on a common input dataset, absence of ground truth, computational cost of calling orthologs). To address this, the Quest for Orthologs consortium maintains a reference set of proteomes and provides a web server for continuous orthology benchmarking (http://orthology.benchmarkservice.org). Furthermore, consensus ortholog calls derived from public benchmark submissions are provided on the Alliance of Genome Resources website, the joint portal of NIH-funded model organism databases.

Citing Articles

A metric and its derived protein network for evaluation of ortholog database inconsistency.

Yang W, Ji J, Fang G BMC Bioinformatics. 2025; 26(1):6.

PMID: 39773281 PMC: 11707888. DOI: 10.1186/s12859-024-06023-x.

New developments for the Quest for Orthologs benchmark service.

Altenhoff A, Nevers Y, Tran V, Jyothi D, Martin M, Cosentino S NAR Genom Bioinform. 2024; 6(4):lqae167.

PMID: 39664814 PMC: 11632614. DOI: 10.1093/nargab/lqae167.

SonicParanoid2: fast, accurate, and comprehensive orthology inference with machine learning and language models.

Cosentino S, Sriswasdi S, Iwasaki W Genome Biol. 2024; 25(1):195.

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Martin Del Pico E, Gelpi J, Capella-Gutierrez S Bioinformatics. 2024; 40(8).

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Ancient eukaryotic protein interactions illuminate modern genetic traits and disorders.

Cox R, Papoulas O, Shril S, Lee C, Gardner T, Battenhouse A bioRxiv. 2024; .

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