The Gene Identification Problem from a Hypotheses Test Perspective.
Mireia Vilardell, Alex Sánchez · 2004
Many gene identification methods assign scores to gene elementsas a previous step to their assembly in predicted genes. The scoring system is often based on log likelihood ratios (LLRs) whose meaning is somehow different from the usual likelihood ratio tests that appear in many statistical problems. In the first part of this work we have tried to give an interpretation of the statistical meaning of LLRs based scoring systems. We have developed several tests of significance for the scores: the “Sum-of-Scores test” (SSt), based on the straightforward score obtained by the programs, the “Intersection-Union test ” (IUt) based on a multiple hypothesis testing interpretation of an exon’s score and several meta-analytical approaches which combines p-values corresponding to the exon’s parts. We have performed simulation studies to analyze the performance of these tests. Whereas SSt and IUt tests are appealing from the statistical point of view the meta-analytic approach has proved to have a much better sensitivity and specificity which suggests they may be incorporated in actual gene prediction methods as a complimentary “probabilistic ” score. To approximate the distribution of the tests under the