Data Analysis and Determination of Sample Size for the Dye-Swap Two-Color Spotted Microarray Experiments
Date Issued
2004
Date
2004
Author(s)
Yu, Ting-Wan
DOI
zh-TW
Abstract
Microarray technology is a powerful tool to detect the expression level of many thousands of genes. However there are many sources of systematic variation which may bias the estimation of the gene expression. Hence how to remove the systematic variation and estimate the gene expression correctly are important topics in the micr- oarray experiment.
In this study, we focus on the dye-swap two-color DNA spotted microarray experiments. We try to analyze the data collected from this kind of microarray experiments by some log-ratio models, which can be classified as one-stage log-ratio models and two-stage log-ratio models. In one-stage log- ratio models, we assume the variances of the gene expression for different genes are homogenous. However most genes in microarray experiments are not significantly expressed, hence the estimate of this unique variance may be actually smaller than the true values for the rest significant genes. Consider the two-stage log-ratio models, the first part of the two-stage log-ratio models can be regarded as a global normalization model and the second part is a gene-specific model. Moreover the gene-specific model can be regarded as gene-by-gene models or mixture probability density function models under different assumptions. The variances of the gene expression are assumed to be different in the gene-bye-gene models, leading to that every gene has it own model. Mixture probability density function models regard genes in microarray experiments as significantly expressed genes and non-significantly expressed genes, each population has its own probability density function. The Student’s t statistic is used in one stage log-ratio models to identify differentially expressed genes. Similarly, Sg statistic proposed by Efron et al. (2001) is used in two-stage gene-by-gene models. In mixture probability density function models, differentially expressed genes are determined by the posterior odds which is a kind of Bayesian approach.
Finally, we consider the sample size based on the one-stage log-ratio models and the gene-by-gene models, respectively.
Subjects
裂區設計
重複數
染劑對調
點印微陣列試驗
microarray
sample size
dye-swap
Type
thesis
File(s)![Thumbnail Image]()
Loading...
Name
ntu-93-R91621208-1.pdf
Size
23.31 KB
Format
Adobe PDF
Checksum
(MD5):d8cc8a454639808047cbf8da55b9dfb1