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Testing for trends in dose-response microarray experiments: a comparison of several testing procedures, multiplicity

Dan Lin¹, Ziv Shkedy, Dani Yekutieli

¹Hasselt University. dan.lin@uhasselt.be

Statistical Applications in Genetics and Molecular Biology

|December 7, 2007

Summary

This study compares statistical tests for dose-response microarray experiments, identifying differentially expressed genes. The research introduces a modified M statistic and evaluates gene expression trends across multiple doses.

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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

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Area of Science:

Bioinformatics
Statistical Genetics
Genomics

Background:

Dose-response studies are crucial in pharmaceutical research to understand toxicity trends.
Microarray experiments enable the analysis of gene expression across various dose levels.

Purpose of the Study:

To evaluate statistical testing procedures for identifying differentially expressed genes in dose-response microarray experiments.
To compare the performance of Williams', Marcus', global likelihood ratio, and M statistics.
To introduce a modified M statistic for enhanced analysis.

Main Methods:

Review and comparison of established statistical tests: Williams', Marcus', global likelihood ratio, and M statistics.
Application of False Discovery Rate and Familywise Error Rate for multiple testing correction.
Implementation and simulation study using the R library IsoGene.

Main Results:

The study applied five statistical methods to a dataset of 16,998 genes across 4 dose levels.
Performance comparison and discussion of one-sided versus two-sided testing procedures were conducted.
A simulation study assessed the statistical power of each method.

Conclusions:

The research provides a comparative analysis of statistical methods for dose-response gene expression analysis.
The findings aid in selecting appropriate statistical tools for identifying gene expression trends in toxicological studies.
An R library, IsoGene, is available for implementing these methods.