Optimizing the noise versus bias trade-off for Illumina whole genome expression BeadChips.
Optimizing the noise versus bias trade-off for Illumina whole genome expression BeadChips.
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DOI：
10.1093/nar/gkq871
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发表时间：
2010-12
影响因子：
14.9
通讯作者：
Smyth GK
中科院分区：
文献类型：
--
作者：
Shi W;Oshlack A;Smyth GK
从精密度和偏倚的角度评估了Illumina expression BeadChips预处理强度的五种策略。这些策略包括一个流行的方差稳定转换和基于模型的背景校正，要么使用或忽略控制探头。四个校准数据集用于评估精度，偏差和错误发现率（FDR）。原始算法被证明具有不容易比较的操作特性。一些倾向于最小化噪声，而另一些则最小化偏差。每个原始算法被证明有一个先天的强度偏移，其中未记录的强度有界远离零，这个偏移的大小决定了它的位置上的噪声偏置频谱。通过添加额外的偏移量，一个连续的相关算法与不同的噪声偏置的权衡产生，允许直接比较的性能的战略上的等价条款。增加一个正的偏移量，以减少每个原始算法的FDR。每种策略的潜力，以产生一个最佳的噪声偏置权衡算法探索通过寻找偏移，最大限度地减少其FDR。使用对照探针作为背景校正和标准化策略的一部分显示出对于给定的偏差实现最低的FDR。
Five strategies for pre-processing intensities from Illumina expression BeadChips are assessed from the point of view of precision and bias. The strategies include a popular variance stabilizing transformation and model-based background corrections that either use or ignore the control probes. Four calibration data sets are used to evaluate precision, bias and false discovery rate (FDR). The original algorithms are shown to have operating characteristics that are not easily comparable. Some tend to minimize noise while others minimize bias. Each original algorithm is shown to have an innate intensity offset, by which unlogged intensities are bounded away from zero, and the size of this offset determines its position on the noise–bias spectrum. By adding extra offsets, a continuum of related algorithms with different noise–bias trade-offs is generated, allowing direct comparison of the performance of the strategies on equivalent terms. Adding a positive offset is shown to decrease the FDR of each original algorithm. The potential of each strategy to generate an algorithm with an optimal noise–bias trade-off is explored by finding the offset that minimizes its FDR. The use of control probes as part of the background correction and normalization strategy is shown to achieve the lowest FDR for a given bias.
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