Estimating and comparing the rates of gene discovery and expressed sequence tag (EST) frequencies in EST surveys.
BACKGROUND
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. However, few statistical methods have been developed to assess and compare redundancies of various libraries from preliminary EST surveys.


RESULTS
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 one of several libraries is more likely to yield new genes in future reads and what proportion of additional reads one might want to take from the libraries in order to be likely to obtain new genes. One approach is to compare single sample measures that have been successfully used in species estimation problems, such as coverage of a library, defined as the proportion of the library that is represented in the given sample of reads. Another single library measure is an estimate of the expected number of additional genes that will be found in a new sample of reads. We also propose statistics that jointly use data from all the libraries. Analogous formulas for coverage and the expected numbers of new genes are presented. These measures consider coverage in a single library based upon reads from all libraries and similarly, the expected numbers of new genes that will be discovered by taking reads from all libraries with fixed proportions. Together, the statistics presented provide useful comparative measures for the libraries that can be used to guide sampling from each of the libraries to maximize the rate of gene discovery. Finally, we present tests for whether genes are equally represented or expressed in a set of libraries. Binomial and chi2 tests are presented for gene-by-gene comparisons of expression. Overall tests of the equality of proportional representation are presented and multiple comparisons issues are addressed. These methods can be used to evaluate changes in gene expression reflected in the composition of EST libraries prepared from different tissue types or cells exposed to different environmental conditions.


BACKGROUND
Software will be made available at http://www.mathstat.dal.ca/~tsusko
Susko
Edward
E
Genome Atlantic, Department of Mathematics and Statistics, Dahlhousie University, Nova Scotia, Canada. susko@mathstat.dal.ca
Roger
Andrew J
AJ
D000465:Algorithms; D002874:Chromosome Mapping / Q000379:methods*; D020224:Expressed Sequence Tags; D020869:Gene Expression Profiling / Q000379:methods*; D015723:Gene Library; D008957:Models, Genetic; D015233:Models, Statistical; D016415:Sequence Alignment / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods*; D012689:Sequence Homology, Nucleic Acid