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- Title
Variable locus length in the human genome leads to ascertainment bias in functional inference for non-coding elements.
- Authors
Leila Taher; Ivan Ovcharenko
- Abstract
Motivation: Several functional gene annotation databases have been developed in the recent years, and are widely used to infer the biological function of gene sets, by scrutinizing the attributes that appear over- and underrepresented. However, this strategy is not directly applicable to the study of non-coding DNA, as the non-coding sequence span varies greatly among different gene loci in the human genome and longer loci have a higher likelihood of being selected purely by chance. Therefore, conclusions involving the function of non-coding elements that are drawn based on the annotation of neighboring genes are often biased. We assessed the systematic bias in several particular Gene Ontology (GO) categories using the standard hypergeometric test, by randomly sampling non-coding elements from the human genome and inferring their function based on the functional annotation of the closest genes. While no category is expected to occur significantly over- or underrepresented for a random selection of elements, categories such as âcell adhesionâ, ânervous system developmentâ and âtranscription factor activitiesâ appeared to be systematically overrepresented, while others such as âolfactory receptor activityââunderrepresented. Results: Our results suggest that functional inference for non-coding elements using gene annotation databases requires a special correction. We introduce a set of correction coefficients for the probabilities of the GO categories that accounts for the variability in the length of the non-coding DNA across different loci and effectively eliminates the ascertainment bias from the functional characterization of non-coding elements. Our approach can be easily generalized to any other gene annotation database. Contact: ovcharei@ncbi.nlm.nih.gov Supplementary information: Supplementary data are available at Bioinformatics Online.
- Publication
Bioinformatics, 2009, Vol 25, Issue 5, p578
- ISSN
1367-4803
- Publication type
Academic Journal
- DOI
10.1093/bioinformatics/btp043