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微阵列实验中样本合并引起的偏差。

Biases induced by pooling samples in microarray experiments.

作者信息

Mary-Huard Tristan, Daudin Jean-Jacques, Baccini Michela, Biggeri Annibale, Bar-Hen Avner

机构信息

UMR AgroParisTech/INRA MIA 518, 16 rue Claude Bernard 75231 Paris Cedex 5, France.

出版信息

Bioinformatics. 2007 Jul 1;23(13):i313-8. doi: 10.1093/bioinformatics/btm182.

Abstract

MOTIVATION

If there is insufficient RNA from the tissues under investigation from one organism, then it is common practice to pool RNA. An important question is to determine whether pooling introduces biases, which can lead to inaccurate results. In this article, we describe two biases related to pooling, from a theoretical as well as a practical point of view.

RESULTS

We model and quantify the respective parts of the pooling bias due to the log transform as well as the bias due to biological averaging of the samples. We also evaluate the impact of the bias on the statistical differential analysis of Affymetrix data.

摘要

动机

如果从一个生物体的被研究组织中获得的RNA不足,那么将RNA混合是常见的做法。一个重要的问题是确定混合是否会引入偏差,这可能导致结果不准确。在本文中,我们从理论和实践的角度描述了与混合相关的两种偏差。

结果

我们对由于对数变换导致的混合偏差以及样本的生物学平均导致的偏差的各个部分进行建模和量化。我们还评估了该偏差对Affymetrix数据统计差异分析的影响。

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