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Genome majority vote improves gene predictions.

Authors
  • Wall, Michael E1
  • Raghavan, Sindhu
  • Cohn, Judith D
  • Dunbar, John
  • 1 Computer, Computational, and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, New Mexico, USA. [email protected] , (Mexico)
Type
Published Article
Journal
PLoS Computational Biology
Publisher
Public Library of Science
Publication Date
Nov 01, 2011
Volume
7
Issue
11
Identifiers
DOI: 10.1371/journal.pcbi.1002284
PMID: 22131910
Source
Medline
Language
English
License
Unknown

Abstract

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.

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