title: Hypothesis testing approaches to the exon prediction problem.
abstract: BACKGROUND
  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.
authors.affiliation: Statistics Department, University of Barcelona Barcelona, Spain.
authors.forename: Mireia
authors.initials: M
authors.lastname: Vilardell
authors.forename: Alex
authors.initials: A
authors.lastname: Sánchez-Pla
mesh_terms: D000465:Algorithms; D001483:Base Sequence; D002874:Chromosome Mapping / Q000379:methods*; D003198:Computer Simulation; D005091:Exons / Q000235:genetics*; D005815:Genetic Code / Q000235:genetics*; D008957:Models, Genetic; D015233:Models, Statistical; D008969:Molecular Sequence Data; D011506:Proteins / Q000737:chemistry* / Q000235:genetics*; D016415:Sequence Alignment / Q000379:methods; D017422:Sequence Analysis, DNA / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods*
chemical_list: D011506:Proteins