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ABSTRACT: Motivation
Correct gene predictions are crucial for most analyses of genomes. However, in the absence of transcript data, gene prediction is still challenging. One way to improve gene-finding accuracy in such genomes is to combine the exons predicted by several gene-finders, so that gene-finders that make uncorrelated errors can correct each other.Results
We present a method for combining gene-finders called Genomix. Genomix selects the predicted exons that are best conserved within and/or between species in terms of sequence and intron-exon structure, and combines them into a gene structure. Genomix was used to combine predictions from four gene-finders for Caenorhabditis elegans, by selecting the predicted exons that are best conserved with C.briggsae and C.remanei. On a set of approximately 1500 confirmed C.elegans genes, Genomix increased the exon-level specificity by 10.1% and sensitivity by 2.7% compared to the best input gene-finder.Availability
Scripts and Supplementary Material can be found at http://www.sanger.ac.uk/Software/analysis/genomix
SUBMITTER: Coghlan A
PROVIDER: S-EPMC2880447 | biostudies-literature | 2007 Jun
REPOSITORIES: biostudies-literature

Bioinformatics (Oxford, England) 20070505 12
<h4>Motivation</h4>Correct gene predictions are crucial for most analyses of genomes. However, in the absence of transcript data, gene prediction is still challenging. One way to improve gene-finding accuracy in such genomes is to combine the exons predicted by several gene-finders, so that gene-finders that make uncorrelated errors can correct each other.<h4>Results</h4>We present a method for combining gene-finders called Genomix. Genomix selects the predicted exons that are best conserved wit ...[more]