Statistical detection of short periodic gene expression time series profiles

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Title Statistical detection of short periodic gene expression time series profiles
Author Liew, Alan Wee-Chung; Law, N.F.; Yan, Hong
Publication Title Proceedings of the International Symposium on Computational Models for Life Sciences
Editor Tuan Pham & Xiaobo Zhou
Year Published 2007
Place of publication USA
Publisher American Institute of Physics
Abstract Many cellular processes exhibit periodic behaviors. Hence, one of the important tasks in gene expression data analysis is to detect subset of genes that exhibit cyclicity or periodicity in their gene expression time series profiles. Unfortunately, gene expression time series profiles are usually of very short length and highly contaminated with noise. This makes detection of periodic profiles a very difficult problem. Recently, a hypothesis testing method based on the Fisher g-statistic with correction for multiple testing has been proposed to detect periodic gene expression profiles. However, it was observed that the test is not reliable if the signal length is too short. In this paper, we performed extensive simulation study to investigate the statistical power of the test as a function of signal length, SNR, and the false discovery rate. We found that the number of periodic profiles can be severely underestimated for short length signal. The findings indicated that caution needs to be exercised when interpreting the test result for very short length signals.
Peer Reviewed Yes
Published Yes
Publisher URI http://scitation.aip.org/dbt/dbt.jsp?KEY=APCPCS&Volume=952&Issue=1
Alternative URI http://dx.doi.org/10.1063/1.2816619
Copyright Statement Copyright 2007 American Institute of Physics. The attached file is reproduced here in accordance with the copyright policy of the publisher. Use hypertext link for access to the conference website.
Conference name International Symposium on Computational Models for Life Sciences
Location Gold Coast, Australia
Date From 2007-12-17
Date To 2007-12-19
URI http://hdl.handle.net/10072/18030
Date Accessioned 2008-03-06
Date Available 2009-10-16T05:20:03Z
Language en_AU
Research Centre Institute for Integrated and Intelligent Systems
Faculty Faculty of Science, Environment, Engineering and Technology
Subject PRE2009-Computation Theory and Mathematics; PRE2009-Gene Expression
Publication Type Conference Publications (Full Written Paper - Refereed)
Publication Type Code e1

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