A concentration-dependent analysis method for high density protein microarrays
A concentration-dependent analysis method for high density protein microarrays
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DOI：
10.1021/pr700892h
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发表时间：
2008-05-01
影响因子：
4.4
通讯作者：
Wu, Catherine J.
中科院分区：
文献类型：
--
作者：
Marina, Ovidiu;Biernacki, Melinda A.;Wu, Catherine J.
蛋白质微阵列技术正在迅速发展，并有可能加速发现癌症、自身免疫和传染病的血清抗体反应目标。然而，用于解释这种高通量阵列数据的分析工具并不完善。我们开发了一种浓度依赖分析（CDA）方法，该方法基于斑点探针的浓度对蛋白质微阵列数据进行规范化。我们表明，该分析采样的数据空间与其他常用的分析互补，并演示了通过CDA与其他工具交叉识别的92%的命中实验验证。这些数据支持使用CDA作为更完整的蛋白质组学微阵列数据分析的预处理步骤或作为独立的分析方法。
Protein microarray technology is rapidly growing and has the potential to accelerate the discovery of targets of serum antibody responses in cancer, autoimmunity and infectious disease. Analytical tools for interpreting this high-throughput array data, however, are not well-established. We developed a concentration-dependent analysis (CDA) method which normalizes protein microarray data based on the concentration of spotted probes. We show that this analysis samples a data space that is complementary to other commonly employed analyses, and demonstrate experimental validation of 92% of hits identified by the intersection of CDA with other tools. These data support the use of CDA either as a preprocessing step for a more complete proteomic microarray data analysis or as a stand-alone analysis method.