Thawing Frozen Robust Multi-array Analysis (fRMA).

Thawing Frozen Robust Multi-array Analysis (fRMA).
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DOI:
10.1186/1471-2105-12-369
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发表时间:
2011-09-16
期刊:
影响因子:
3
通讯作者:
Irizarry RA
Irizarry RA
中科院分区:
生物学4区
文献类型:
--
作者:
McCall MN;Irizarry RA

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冷冻稳健多阵列分析(Frozen Robust Multi-Array Analysis,fRMA)是近年来发展起来的一种新的微阵列预处理方法。该算法允许用户单独预处理阵列,同时保留多阵列预处理方法的优点。该算法所需的冻结参数估计是使用一个大型数据库的公开可用的数组。这样一个数据库的管理和冻结参数估计值的创建是耗时的;因此,fRMA仅在最广泛使用的Affytechnology平台上实现。我们提出了一个R包,frmaTools,它允许用户快速创建他或她自己的冻结参数向量。我们描述了这个包如何适应预处理工作流程,并探索了生成可靠的冻结参数估计所需的训练数据集的大小。接下来是对特定情况的讨论,在这些情况下,人们可能希望创建自己的fRMA实现。对于一些特定的场景,我们证明了fRMA即使在大型阵列数据库不可用时也能很好地执行。通过允许用户轻松创建自己的fRMA实现,frmaTools软件包极大地提高了fRMA算法的适用性。frmaTools软件包作为Bioconductor项目的一部分免费提供。
A novel method of microarray preprocessing - Frozen Robust Multi-array Analysis (fRMA) - has recently been developed. This algorithm allows the user to preprocess arrays individually while retaining the advantages of multi-array preprocessing methods. The frozen parameter estimates required by this algorithm are generated using a large database of publicly available arrays. Curation of such a database and creation of the frozen parameter estimates is time-consuming; therefore, fRMA has only been implemented on the most widely used Affymetrix platforms. We present an R package, frmaTools, that allows the user to quickly create his or her own frozen parameter vectors. We describe how this package fits into a preprocessing workflow and explore the size of the training dataset needed to generate reliable frozen parameter estimates. This is followed by a discussion of specific situations in which one might wish to create one's own fRMA implementation. For a few specific scenarios, we demonstrate that fRMA performs well even when a large database of arrays in unavailable. By allowing the user to easily create his or her own fRMA implementation, the frmaTools package greatly increases the applicability of the fRMA algorithm. The frmaTools package is freely available as part of the Bioconductor project.
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