title: Statistical analysis of expressed sequence tags.
abstract: Expressed sequence tag (EST) surveys are an efficient way to characterize large numbers of genes from an organism. The rate of gene discovery in an EST survey depends on the degree of redundancy of the cDNA libraries from which sequences are obtained. We consider statistics for the comparison of EST libraries based upon the frequencies with which genes occur in subsamples of reads. These measures are useful in determining which of the libraries, having a large proportion of genes in common, is more likely to yield new genes in future reads. We also present tests, with multiple corrections adjustments, for whether genes are equally represented or expressed in a pair of libraries.
authors.affiliation: Department of Mathematics and Statistics, Dalhousie University, Halifax, Nova Scotia, Canada.
authors.forename: Edward
authors.initials: E
authors.lastname: Susko
authors.forename: Andrew J
authors.initials: AJ
authors.lastname: Roger
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D018076:DNA, Complementary / Q000378:metabolism; D003627:Data Interpretation, Statistical; D030541:Databases, Genetic; D020224:Expressed Sequence Tags; D020869:Gene Expression Profiling / Q000379:methods; D015723:Gene Library; D006801:Humans; D015233:Models, Statistical; D011336:Probability
chemical_list: D018076:DNA, Complementary