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Statistical models in assessing fold change of gene expression in real-time RT-PCR experiments

Paper ID Volume ID Publish Year Pages File Format Full-Text
15411 1411 2006 6 PDF Available
Title
Statistical models in assessing fold change of gene expression in real-time RT-PCR experiments
Abstract

Real-time RT-PCR has been frequently used in quantitative research in molecular biology and bioinformatics. It provides remarkably useful technology to assess expression of genes. Although mathematical models for gene amplification process have been studied, statistical models and methods for data analysis in real-time RT-PCR have received little attention. In this paper, we briefly introduce current mathematical models, and study statistical models for real-time RT-PCR data. We propose a generalized estimation equations (GEE) model that properly reflects the structure of repeated data in RT-PCR experiments for both cross-sectional and longitudinal data. The GEE model takes the correlation between observations within the same subjects into consideration, and prevents from producing false positives or false negatives. We further demonstrate with a set of actual real-time RT-PCR data that different statistical models yield different estimations of fold change and confidence interval. The SAS program for data analysis using the GEE model is provided to facilitate easy computation for non-statistical professionals.

Keywords
Correlation; Differential expression; Longitudinal studies; Repeated samples
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Publisher
Database: Elsevier - ScienceDirect
Journal: Computational Biology and Chemistry - Volume 30, Issue 1, February 2006, Pages 21–26
Authors
, , , , ,
Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us