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

ABSTRACT:

Background

Functional 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.

Results

We developed a genome-scale model that assigns Bayesian probability to each gene utilizing a known property of functional similarity between neighboring genes in bacteria.

Conclusions

Our 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.

SUBMITTER: Jun SR 

PROVIDER: S-EPMC5517811 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature