Microarray Data Analysis for Differential Expression: a Tutorial

被引:0
|
作者
Suarez, Erick [1 ]
Burguete, Ana [2 ]
Mclachlan, Geoffrey J. [3 ,4 ]
机构
[1] Univ Puerto Rico, Dept Biostat & Epidemiol, Sch Publ Hlth, San Juan, PR 00936 USA
[2] Inst Nacl Salud Publ Mexico, Mexico City, DF, Mexico
[3] Univ Queensland, Dept Math, Brisbane, Qld 4072, Australia
[4] Univ Queensland, Inst Mol Biosci, Brisbane, Qld 4072, Australia
关键词
Preprocessing data for microarrays; Pairwise comparison for microarrays; False discovery rate; Free microarray analysis software; FALSE DISCOVERY RATE; GENE-EXPRESSION; SAMPLE-SIZE; OLIGONUCLEOTIDE ARRAY; NORMALIZATION; TECHNOLOGY; POWER;
D O I
暂无
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
DNA microarray is a technology that simultaneously evaluates quantitative measurements for the expression of thousands of genes. DNA microarrays have been used to assess gene expression between groups of cells of different organs or different populations. In order to understand the role and function of the genes, one needs the complete information about their mRNA transcripts and proteins. Unfortunately, exploring the protein functions is very difficult, due to their unique 3-dimentional complicated structure. To overcome this difficulty, one may concentrate on the mRNA molecules produced by the gene expression. In this paper, we describe some of the methods for preprocessing data for gene expression and for pairwise comparison from genomic experiments. Previous studies to assess the efficiency of different methods for pairwise comparisons have found little agreement in the lists of significant genes. Finally, we describe the procedures to control false discovery rates, sample size approach for these experiments, and available software for microarray data analysis. This paper is written for those professionals who are new in microarray data analysis for differential expression and want to have an overview of the specific steps or the different approaches for this sort of analysis.
引用
收藏
页码:89 / 104
页数:16
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