Comparative microarray analysis
Comparative microarray analysis
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DOI：
10.1089/omi.2006.10.381
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发表时间：
2006-09-01
影响因子：
3.3
通讯作者：
Sandberg, Rickard
中科院分区：
文献类型：
--
作者：
Larsson, Ola;Wennmalm, Kristian;Sandberg, Rickard
微阵列使高通量并行基因表达分析成为可能，在过去十年中，其使用呈指数级增长。我们现在所处的位置是，个人实验可以从使用不断膨胀的公共数据库中受益，使微阵列从一个假设生成工具发展成为一个强大的资源，可以用来测试生物学假设。比较微阵列分析可以更好地区分表型和相关表型;通过结合许多研究来识别有效的差异表达基因;测试新的假设;并发现基因调控的基本模式。这篇综述的目的是描述这种比较微阵列分析所需的其他方法，我们确定并讨论了一些问题，如已发表的数据丢失，缺乏注释，和可变的阵列质量，这需要解决比较微阵列分析之前，可以使用一个更系统和强大的方式。
Microarrays enable high-throughput parallel gene expression analysis, and their use has grown exponentially during the past decade. We are now in a position where individual experiments could benefit from using the swelling public data repositories to allow microarrays to progress from being a hypothesis-generating tool to a powerful resource that can be used to test hypothesis about biology. Comparative microarray analysis could better distinguish phenotypes from associated phenotypes; identify valid differentially expressed genes by combining many studies; test new hypothesis; and discover fundamental patterns of gene regulation. This review aims to describe the additional methodology needed for such comparative microarray analysis, and we identify and discuss a number of problems such as loss of published data, lack of annotations, and variable array quality, which need to be solved before comparative microarray analysis can be used in a more systematic and powerful manner.