Assessment of genome annotation using gene function similarity within the gene neighborhood

BMC Bioinformatics

Methodology Article

Loren Hauser¹  Andrey Gorin²  Intawat Nookaew³  Se-Ran Jun³ 

[1] Comparative Genomics Group, Biosciences Division, Oak Ridge National Laboratory, 37831, Oak Ridge, TN, USA;Computer Science and Mathematics Division, Oak Ridge National Laboratory, 37831, Oak Ridge, TN, USA;Department of Biomedical Informatics, College of Medicine, University of Arkansas for Medical Sciences, 72205, Little Rock, AR, USA;

关键词: Genome functional annotation;    Gene function similarity;    Gene neighborhood;    Bayesian probability;   

DOI  :  10.1186/s12859-017-1761-2

 received in 2017-01-24, accepted in 2017-07-13,  发布年份 2017

来源: Springer

【 摘 要 】

BackgroundFunctional annotation of bacterial genomes is an obligatory and crucially important step of information processing from the genome sequences into cellular mechanisms. However, there is a lack of computational methods to evaluate the quality of functional assignments.ResultsWe developed a genome-scale model that assigns Bayesian probability to each gene utilizing a known property of functional similarity between neighboring genes in bacteria.ConclusionsOur model clearly distinguished true annotation from random annotation with Bayesian annotation probability >0.95. Our model will provide a useful guide to quantitatively evaluate functional annotation methods and to detect gene sets with reliable annotations.

【 授权许可】

CC BY   
© The Author(s). 2017