Systematic management and analysis of yeast gene expression data
Systematic management and analysis of yeast gene expression data
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DOI：
10.1101/gr.10.4.431
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发表时间：
2000-04-01
期刊：
影响因子：
7
通讯作者：
Church, GM
中科院分区：
文献类型：
--
作者：
Aach, J;Rindone, W;Church, GM
我们报告了功能基因组学数据的系统化管理、标准化和分析的步骤。我们开发了酵母RNA表达数据的DBDB数据库，并加载了与II研究报告的1750万条数据相似的数据，这些数据采用了三种不同的高通量RNA检测方法。一个基于网络的工具支持查询这些研究的数据。我们通过将来自9项研究（217种条件）的数据转换为mRNA相对丰度估计值（ERA）并通过ERA聚类条件来检查数据的可比性。我们在我们的网站http://arep.med.harvard.edu DB上报告了非微阵列数据的ERA生成和条件聚类（5项研究，63种条件），并描述了生成基于微阵列的ERA的初步尝试（4项研究，154种条件），这些尝试显示出增加的错误。我们建议数据报告的标准，建议研究通过量化和标准化控制条件RNA群体，提高微阵列数据的可比性，并建议研究不同的RNA检测的校准。我们介绍了一个数据库模型，它集成了不同类型的功能基因组学数据，生物分子相互作用，生长和表达数据库（BIGED）。
We report steps toward the systematic management, standardization, and analysis of functional genomics data. We developed the ExpressDB database for yeast RNA expression data and loaded it with similar to 17.5 million pieces of data reported by II studies with three different kinds of high-throughput RNA assays. A web-based tool supports queries across the data From these studies. We examined comparability of data by converting data from 9 studies (217 conditions) into mRNA relative abundance estimates (ERAs) and by clustering of conditions by ERAs. We report on generation of ERAs and condition clustering for non-microarray data (5 studies, 63 conditions) and describe initial attempts to generate microarray-based ERAs (4 studies, 154 conditions), which exhibit increased error, on our web site http://arep.med.harvard.edu /ExpressDB. We recommend standards for data reporting, suggest research into improving comparability of microarray data through quantifying and standardizing control condition RNA populations, and also suggest research into the calibration of different RNA assays. We introduce a model for a database that integrates different kinds of Functional genomics data, Biomolecule Interaction, Growth and Expression Database (BIGED).