Genome majority vote improves gene predictions.

Recent studies have noted extensive inconsistencies in gene start sites among orthologous genes in related microbial genomes. Here we provide the first documented evidence that imposing gene start consistency improves the accuracy of gene start-site prediction. We applied an algorithm using a genome...

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Auteurs principaux: Michael E Wall, Sindhu Raghavan, Judith D Cohn, John Dunbar
Format: article
Langue:EN
Publié: Public Library of Science (PLoS) 2011
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Accès en ligne:https://doaj.org/article/d0ed2a5550804a92ae45ece1ed78b69f
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spelling oai:doaj.org-article:d0ed2a5550804a92ae45ece1ed78b69f2021-11-18T05:51:46ZGenome majority vote improves gene predictions.1553-734X1553-735810.1371/journal.pcbi.1002284https://doaj.org/article/d0ed2a5550804a92ae45ece1ed78b69f2011-11-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22131910/?tool=EBIhttps://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Recent studies have noted extensive inconsistencies in gene start sites among orthologous genes in related microbial genomes. Here we provide the first documented evidence that imposing gene start consistency improves the accuracy of gene start-site prediction. We applied an algorithm using a genome majority vote (GMV) scheme to increase the consistency of gene starts among orthologs. We used a set of validated Escherichia coli genes as a standard to quantify accuracy. Results showed that the GMV algorithm can correct hundreds of gene prediction errors in sets of five or ten genomes while introducing few errors. Using a conservative calculation, we project that GMV would resolve many inconsistencies and errors in publicly available microbial gene maps. Our simple and logical solution provides a notable advance toward accurate gene maps.Michael E WallSindhu RaghavanJudith D CohnJohn DunbarPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 7, Iss 11, p e1002284 (2011)
institution DOAJ
collection DOAJ
language EN
topic Biology (General)
QH301-705.5
spellingShingle Biology (General)
QH301-705.5
Michael E Wall
Sindhu Raghavan
Judith D Cohn
John Dunbar
Genome majority vote improves gene predictions.
description Recent studies have noted extensive inconsistencies in gene start sites among orthologous genes in related microbial genomes. Here we provide the first documented evidence that imposing gene start consistency improves the accuracy of gene start-site prediction. We applied an algorithm using a genome majority vote (GMV) scheme to increase the consistency of gene starts among orthologs. We used a set of validated Escherichia coli genes as a standard to quantify accuracy. Results showed that the GMV algorithm can correct hundreds of gene prediction errors in sets of five or ten genomes while introducing few errors. Using a conservative calculation, we project that GMV would resolve many inconsistencies and errors in publicly available microbial gene maps. Our simple and logical solution provides a notable advance toward accurate gene maps.
format article
author Michael E Wall
Sindhu Raghavan
Judith D Cohn
John Dunbar
author_facet Michael E Wall
Sindhu Raghavan
Judith D Cohn
John Dunbar
author_sort Michael E Wall
title Genome majority vote improves gene predictions.
title_short Genome majority vote improves gene predictions.
title_full Genome majority vote improves gene predictions.
title_fullStr Genome majority vote improves gene predictions.
title_full_unstemmed Genome majority vote improves gene predictions.
title_sort genome majority vote improves gene predictions.
publisher Public Library of Science (PLoS)
publishDate 2011
url https://doaj.org/article/d0ed2a5550804a92ae45ece1ed78b69f
work_keys_str_mv AT michaelewall genomemajorityvoteimprovesgenepredictions
AT sindhuraghavan genomemajorityvoteimprovesgenepredictions
AT judithdcohn genomemajorityvoteimprovesgenepredictions
AT johndunbar genomemajorityvoteimprovesgenepredictions
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