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Using Pathway Signatures as Means of Identifying Similarities among Microarray Experiments

机译:使用通路签名作为鉴定微阵列实验之间相似性的手段

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摘要

Widespread use of microarrays has generated large amounts of data, the interrogation of the public microarray repositories, identifying similarities between microarray experiments is now one of the major challenges. Approaches using defined group of genes, such as pathways and cellular networks (pathway analysis), have been proposed to improve the interpretation of microarray experiments. We propose a novel method to compare microarray experiments at the pathway level, this method consists of two steps: first, generate pathway signatures, a set of descriptors recapitulating the biologically meaningful pathways related to some clinical/biological variable of interest, second, use these signatures to interrogate microarray databases. We demonstrate that our approach provides more reliable results than with gene-based approaches. While gene-based approaches tend to suffer from bias generated by the analytical procedures employed, our pathway based method successfully groups together similar samples, independently of the experimental design. The results presented are potentially of great interest to improve the ability to query and compare experiments in public repositories of microarray data. As a matter of fact, this method can be used to retrieve data from public microarray databases and perform comparisons at the pathway level.
机译:微阵列的广泛使用已经产生了大量数据,对公共微阵列储存库的询问,识别微阵列实验之间的相似性现在是主要挑战之一。已经提出了使用定义的基因组的方法,例如途径和细胞网络(途径分析)来改善微阵列实验的解释。我们提出了一种在途径水平上比较微阵列实验的新方法,该方法包括两个步骤:首先,生成途径签名,一组描述了与某些临床/生物学变量有关的生物学意义途径的描述符,其次,使用这些方法签名以查询微阵列数据库。我们证明,与基于基因的方法相比,我们的方法可提供更可靠的结果。尽管基于基因的方法往往会因采用的分析程序而产生偏差,但基于路径的方法成功地将相似的样本归为一组,而与实验设计无关。提出的结果可能对提高查询和比较微阵列数据公共存储库中的实验的能力非常感兴趣。实际上,该方法可用于从公共微阵列数据库检索数据并在途径水平上进行比较。

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