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DNA Microarrays

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...

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Performing Custom MicroRNA Microarray Experiments

Performing Custom MicroRNA Microarray Experiments

Published on: October 28, 2011

Sample sizes for a robust ranking and selection of genes in microarray experiments.

Shigeyuki Matsui¹, Tomonori Oura

¹Department of Data Science, The Institute of Statistical Mathematics, Tokyo, Japan. smatsui@ism.ac.jp

Statistics in Medicine

|July 18, 2009

Summary

This study introduces a new method for calculating sample sizes in gene expression studies using the Mann-Whitney-Wilcoxon statistic for robust gene ranking. This approach enhances the reliability of gene selection for future research and clinical applications.

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Area of Science:

Bioinformatics
Statistical Genetics
Genomics

Background:

High-throughput microarrays are crucial for screening candidate genes.
Gene ranking by phenotype association is vital for prioritizing genes in subsequent studies.
Current methods may lack robustness when dealing with non-normal data or platform variations.

Purpose of the Study:

To propose novel sample size calculations for microarray experiments.
To utilize the non-parametric Mann-Whitney-Wilcoxon statistic for gene ranking and selection.
To enhance the robustness of gene ranking against deviations from normality and scale changes.

Main Methods:

Development of sample size calculation methods tailored for gene ranking.
Application of the Mann-Whitney-Wilcoxon statistic for non-parametric gene ranking.
Validation using a clinical lymphoma dataset.

Main Results:

The proposed method provides a statistically sound basis for sample size determination in microarray studies.
The Mann-Whitney-Wilcoxon statistic demonstrates robustness in gene ranking, accommodating non-normal distributions.
The approach is applicable to gene expression data and compatible with different platforms.

Conclusions:

The proposed sample size calculation method improves gene selection accuracy in microarray experiments.
Non-parametric statistics offer advantages for robust gene ranking in genomics research.
This methodology supports more reliable prioritization of genes for further investigation.