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Open Access Methodology article

Gene capture prediction and overlap estimation in EST sequencing from one or multiple libraries

Ji-Ping Z Wang1*, Bruce G Lindsay2, Liying Cui3, P Kerr Wall3, Josh Marion4, Jiaxuan Zhang5 and Claude W dePamphilis3

Author Affiliations

1 Department of Statistics, Northwestern University, Evanston, IL 60208, USA

2 Department of Statistics, Penn State University, University Park 16802, USA

3 Department of Biology, Penn State University, University Park 16802, USA

4 Department of Computer Science, Penn State University, University Park 16802, USA

5 College of Software, Tsinghua University, Beijing, 100086, PR China

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BMC Bioinformatics 2005, 6:300  doi:10.1186/1471-2105-6-300

Published: 13 December 2005

Abstract

Background

In expressed sequence tag (EST) sequencing, we are often interested in how many genes we can capture in an EST sample of a targeted size. This information provides insights to sequencing efficiency in experimental design, as well as clues to the diversity of expressed genes in the tissue from which the library was constructed.

Results

We propose a compound Poisson process model that can accurately predict the gene capture in a future EST sample based on an initial EST sample. It also allows estimation of the number of expressed genes in one cDNA library or co-expressed in two cDNA libraries. The superior performance of the new prediction method over an existing approach is established by a simulation study. Our analysis of four Arabidopsis thaliana EST sets suggests that the number of expressed genes present in four different cDNA libraries of Arabidopsis thaliana varies from 9155 (root) to 12005 (silique). An observed fraction of co-expressed genes in two different EST sets as low as 25% can correspond to an actual overlap fraction greater than 65%.

Conclusion

The proposed method provides a convenient tool for gene capture prediction and cDNA library property diagnosis in EST sequencing.