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A framework for list representation, enabling list stabilization through incorporation of gene exchangeabilities

机译:列表表示的框架,通过整合基因交换能力实现列表稳定

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Analysis of multivariate data sets from, for example, microarray studies frequently results in lists of genes which are associated with some response of interest. The biological interpretation is often complicated by the statistical instability of the obtained gene lists, which may partly be due to the functional redundancy among genes, implying that multiple genes can play exchangeable roles in the cell. In this paper, we use the concept of exchangeability of random variables to model this functional redundancy and thereby account for the instability. We present a flexible framework to incorporate the exchangeability into the representation of lists. The proposed framework supports straightforward comparison between any 2 lists. It can also be used to generate new more stable gene rankings incorporating more information from the experimental data. Using 2 microarray data sets, we show that the proposed method provides more robust gene rankings than existing methods with respect to sampling variations, without compromising the biological significance of the rankings. The Author 2011. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. 2011
机译:来自例如微阵列研究的多元数据集的分析经常产生与感兴趣的反应相关的基因列表。生物学解释通常由于获得的基因列表的统计不稳定而变得复杂,这可能部分是由于基因之间的功能冗余所致,这意味着多个基因可以在细胞中发挥可交换的作用。在本文中,我们使用随机变量可交换性的概念来对此功能冗余进行建模,从而解决了不稳定性。我们提出了一个灵活的框架,以将可交换性纳入列表的表示中。提议的框架支持任何两个列表之间的直接比较。它也可以用来生成新的更稳定的基因排名,并结合来自实验数据的更多信息。使用2个微阵列数据集,我们表明,在采样变异方面,所提出的方法比现有方法提供了更可靠的基因排名,而不会影响排名的生物学意义。作者2011。牛津大学出版社出版。版权所有。有关权限,请发送电子邮件至:journals.permissions@oup.com。 2011年

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