Optimal Strategies for Sequential Validation of Significant Features from High-Dimensional Genomic Data
Optimal Strategies for Sequential Validation of Significant Features from High-Dimensional Genomic Data
复制标题
高维基因组数据重要特征的顺序验证的最佳策略
DOI：
10.1080/15287394.2012.674912
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发表时间：
2012
期刊：
影响因子：
--
通讯作者：
Rahnenführer J.
中科院分区：
文献类型：
--
作者：
Lohr M;Köllmann C;Freis E;Hellwig B;Hengstler J.G;Ickstadt K.;Rahnenführer J.
高维基因组研究在识别与表型结果显著相关的关键特征方面发挥着关键作用。两个最重要的例子是：(1)来自全基因组基因表达研究的差异表达基因的检测；(2)来自全基因组关联研究的单核苷酸多态性（snp）的检测。这类实验通常与高噪声水平相关，并且与大量特征相比，统计结论的有效性受到低样本量的影响。相应的多重测试问题要求识别控制错误发现和错误未发现数量的最优策略。此外，一个常见的验证问题是，在一项研究中被确定为重要的特征在另一项研究中往往不那么重要。在两项研究中分别调整多重测试，进一步增加了遗漏关键特征的风险。这些问题可以通过顺序验证策略来解决，其中只有在一个研究中确定的重要特征才能作为下一个研究的候选特征。与不同研究相关的质量，例如，在噪音水平方面，可能会有很大差异。通过进行模拟研究，可以证明这种逐步过程的最佳顺序是根据实验研究的质量按降序进行排序。分析了多重测试调整方法（Bonferroni-Holm， FDR）的影响。最后，将顺序验证策略应用于三个具有基因表达测量的大型乳腺癌研究，确认了在实际应用中验证步骤顺序的关键影响。
High-dimensional genomic studies play a key role in identifying critical features that are significantly associated with a phenotypic outcome. The two most important examples are the detection of (1) differentially expressed genes from genome-wide gene expression studies and (2) single-nucleotide polymorphisms (SNPs) from genome-wide association studies. Such experiments are often associated with high noise levels, and the validity of statistical conclusions suffers from low sample size compared to large number of features. The corresponding multiple testing problem calls for the identification of optimal strategies for controlling the numbers of false discoveries and false nondiscoveries. In addition, a frequent validation problem is that features identified as important in one study are often less so in another study. Adjustment for multiple testing in both studies separately increases the risk of missing the crucial features even further. These problems can be addressed by sequential validation strategies, where only significant features identified in one study enter as candidates in the next study. The quality associated with different studies, for example, in terms of noise levels, may vary considerably. By performing simulation studies it is possible to demonstrate that the optimal order for this stepwise procedure is to sort experimental studies according to their quality in descending order. The impact of the method for multiple testing adjustment (Bonferroni-Holm, FDR) was also analyzed. Finally, the sequential validation strategy was applied to three large breast cancer studies with gene expression measurements, confirming the crucial impact of the order of the validation steps in a real-world application.
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影响因子：
30.8
作者：
Carroll, Jason S.;Meyer, Clifford A.;Brown, Myles
通讯作者：
Brown, Myles
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DOI：
--
发表时间：
2007
期刊：
影响因子：
--
作者：
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通讯作者：
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影响因子：
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作者：
Edgar, R;Domrachev, M;Lash, AE
通讯作者：
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DOI：
10.1093/gerona/57.5.b189
发表时间：
2002
期刊：
The journals of gerontology. Series A, Biological sciences and medical sciences
影响因子：
--
作者：
Allison,DavidB;Coffey,ChristopherS
通讯作者：
Coffey,ChristopherS