Hypothesis testing approaches to the exon prediction problem.

Mireia Vilardell; Alex Sánchez-Pla

doi:10.1093/bioinformatics/btl544

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Hypothesis testing approaches to the exon prediction problem.

Mireia Vilardell·Alex Sánchez-Pla

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Abstract

MOTIVATION: Many gene identification methods assign scores to gene elements prior to their assembly into predicted genes. The scoring system is often based on log-likelihood ratios. These methods usually perform well but it is difficult to interpret how significant a score is. RESULTS: We have developed several tests of significance for the scores: (1) a sum-of-scores test (SST), (2) an intersection-union test (IUT), based on a multiple hypothesis testing interpretation of an exon's score and (3) a meta-analytical approach (MA), which combines several P-values, corresponding to the exon's parts, to yield a global P-value. We performed simulation studies, which show that the MA has better sensitivity and specificity than other methods and is easier to interpret by non-expert users. This is an improvement over other methods and is especially relevant for users who would like to predict incomplete gene sequences.

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Algorithms Base Sequence Chromosome Mapping Computer Simulation Exons Genetic Code Models, Genetic Models, Statistical Molecular Sequence Data Proteins Sequence Alignment Sequence Analysis, DNA Sequence Analysis, Protein Journal Article

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Mireia Vilardell, Alex Sánchez-Pla. 2006-10-25. Hypothesis testing approaches to the exon prediction problem.. https://doi.org/10.1093/bioinformatics%2Fbtl544

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