Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY, USA.
BMC Bioinformatics. 2011 Sep 16;12:369. doi: 10.1186/1471-2105-12-369.
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.
最近开发了一种新的微阵列预处理方法——冷冻稳健多阵列分析（fRMA）。该算法允许用户在保留多阵列预处理方法优势的同时单独预处理阵列。该算法所需的冷冻参数估计是使用大型公共可用阵列数据库生成的。此类数据库的整理和冷冻参数估计的创建非常耗时；因此，fRMA 仅在最广泛使用的 Affymetrix 平台上实现。
我们提出了一个 R 包 frmaTools，它允许用户快速创建自己的冷冻参数向量。我们描述了该软件包如何融入预处理工作流程，并探讨了生成可靠冷冻参数估计所需的训练数据集的大小。接下来讨论了在某些特定情况下，可能希望创建自己的 fRMA 实现的情况。对于一些特定的情况，我们证明即使没有大量的阵列数据库，fRMA 也能很好地执行。
通过允许用户轻松创建自己的 fRMA 实现，frmaTools 软件包大大增加了 fRMA 算法的适用性。frmaTools 软件包作为 Bioconductor 项目的一部分免费提供。
