Orthogonal projections to latent structures as a strategy for microarray data normalization.
Orthogonal projections to latent structures as a strategy for microarray data normalization.
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DOI：
10.1186/1471-2105-8-207
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发表时间：
2007-06-18
影响因子：
3
通讯作者：
Trygg J
中科院分区：
文献类型：
--
作者：
Bylesjö M;Eriksson D;Sjödin A;Jansson S;Moritz T;Trygg J
在微阵列数据的生成过程中，经常引入各种形式的系统偏差，这限制了结果的准确性和精确度。为了正确估计生物效应，必须识别和排除这些偏差。我们介绍了一种基于正交投影潜在结构（OPLS）的多通道微阵列数据的归一化策略;一种多元回归方法。说明了单通道Affyphin数据以及双通道cDNA数据上应用归一化方法的效果。我们提供了一个平行的比较，广泛的常用的归一化方法与不同的属性和强度的基础上的灵敏度和特异性从外部（加标）控制。在所示的数据集上，与其他评估方法相比，OPLS归一化策略表现出领先的平均真阴性和真阳性率。OPLS方法识别生物样本内的联合变异，以去除与样本内变异不相关（正交）的变异源。这确保了与基础生物样本相关的结构化变异与系统变异的剩余偏倚相关来源分离。因此，该方法不需要有关某些偏见的存在或特征的任何明确知识。此外，没有基本的假设，即大多数元素应该是无差异表达的，使其适用于专门的精品阵列。
During generation of microarray data, various forms of systematic biases are frequently introduced which limits accuracy and precision of the results. In order to properly estimate biological effects, these biases must be identified and discarded. We introduce a normalization strategy for multi-channel microarray data based on orthogonal projections to latent structures (OPLS); a multivariate regression method. The effect of applying the normalization methodology on single-channel Affymetrix data as well as dual-channel cDNA data is illustrated. We provide a parallel comparison to a wide range of commonly employed normalization methods with diverse properties and strengths based on sensitivity and specificity from external (spike-in) controls. On the illustrated data sets, the OPLS normalization strategy exhibits leading average true negative and true positive rates in comparison to other evaluated methods. The OPLS methodology identifies joint variation within biological samples to enable the removal of sources of variation that are non-correlated (orthogonal) to the within-sample variation. This ensures that structured variation related to the underlying biological samples is separated from the remaining, bias-related sources of systematic variation. As a consequence, the methodology does not require any explicit knowledge regarding the presence or characteristics of certain biases. Furthermore, there is no underlying assumption that the majority of elements should be non-differentially expressed, making it applicable to specialized boutique arrays.
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DOI：
10.1016/s0169-7439(98)00109-9
发表时间：
1998-12-14
影响因子：
3.9
作者：
Wold, S;Antti, H;Öhman, J
通讯作者：
Öhman, J
影响因子：
5.8
作者：
Woo, Y;Krueger, W;Churchill, G
通讯作者：
Churchill, G
DOI：
10.1111/j.2517-6161.1995.tb02031.x
发表时间：
1995-01-01
影响因子：
5.8
作者：
BENJAMINI, Y;HOCHBERG, Y
通讯作者：
HOCHBERG, Y
影响因子：
12.3
作者：
Futschik M;Crompton T
通讯作者：
Crompton T
影响因子：
3.7
作者：
SHAO, J
通讯作者：
SHAO, J