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基因表达谱微阵列实验分析

Analysis of microarray experiments of gene expression profiling.

作者信息

Tarca Adi L, Romero Roberto, Draghici Sorin

机构信息

Perinatology Research Branch, National Institute of Child Health and Human Development, National Institutes of Health, Department of Health and Human Services, Bethesda, MD, USA.

出版信息

Am J Obstet Gynecol. 2006 Aug;195(2):373-88. doi: 10.1016/j.ajog.2006.07.001.

DOI:10.1016/j.ajog.2006.07.001
PMID:16890548
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2435252/
Abstract

The study of gene expression profiling of cells and tissue has become a major tool for discovery in medicine. Microarray experiments allow description of genome-wide expression changes in health and disease. The results of such experiments are expected to change the methods employed in the diagnosis and prognosis of disease in obstetrics and gynecology. Moreover, an unbiased and systematic study of gene expression profiling should allow the establishment of a new taxonomy of disease for obstetric and gynecologic syndromes. Thus, a new era is emerging in which reproductive processes and disorders could be characterized using molecular tools and fingerprinting. The design, analysis, and interpretation of microarray experiments require specialized knowledge that is not part of the standard curriculum of our discipline. This article describes the types of studies that can be conducted with microarray experiments (class comparison, class prediction, class discovery). We discuss key issues pertaining to experimental design, data preprocessing, and gene selection methods. Common types of data representation are illustrated. Potential pitfalls in the interpretation of microarray experiments, as well as the strengths and limitations of this technology, are highlighted. This article is intended to assist clinicians in appraising the quality of the scientific evidence now reported in the obstetric and gynecologic literature.

摘要

细胞和组织的基因表达谱研究已成为医学发现的主要工具。微阵列实验能够描述健康和疾病状态下全基因组的表达变化。此类实验的结果有望改变妇产科疾病诊断和预后所采用的方法。此外,对基因表达谱进行无偏倚且系统的研究应能为妇产科综合征建立新的疾病分类法。因此,一个新的时代正在兴起,在这个时代里,生殖过程和疾病可以通过分子工具和指纹识别来加以表征。微阵列实验的设计、分析和解读需要专业知识,而这些知识并非我们学科标准课程的一部分。本文描述了可通过微阵列实验开展的研究类型(类别比较、类别预测、类别发现)。我们讨论了与实验设计、数据预处理和基因选择方法相关的关键问题。文中还举例说明了常见的数据呈现类型。重点强调了微阵列实验解读中的潜在陷阱以及该技术的优势和局限性。本文旨在帮助临床医生评估目前妇产科文献中所报道的科学证据的质量。

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本文引用的文献

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