A statistical method for the conservative adjustment of false discovery rate (q-value).
A statistical method for the conservative adjustment of false discovery rate (q-value).
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DOI：
10.1186/s12859-017-1474-6
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发表时间：
2017-03-14
影响因子：
3
通讯作者：
Lai Y
中科院分区：
文献类型：
--
作者：
Lai Y
q值是用于估计错误发现率（FDR）的广泛使用的统计方法，其是全基因组表达数据分析中的常规显著性度量。q值是一个随机变量，在实际应用中可能会低估FDR。一个被低估的FDR会在后续的验证实验中导致意想不到的错误发现。这个问题在文献中没有得到很好的解决，特别是在需要置换过程进行p值计算的情况下。提出了一种q值保守调整的统计方法。在实践中，通常需要通过置换过程来计算p值。我们的调整方法也考虑到了这一点。我们使用模拟数据以及实验微阵列或测序数据来说明我们的方法的有用性。在这项研究中，我们的方法的保守性已经在数学上得到了证实。我们已经证明了保守调整q值的重要性，特别是在差异表达基因的比例很小或整体差异表达信号很弱的情况下。
q-value is a widely used statistical method for estimating false discovery rate (FDR), which is a conventional significance measure in the analysis of genome-wide expression data. q-value is a random variable and it may underestimate FDR in practice. An underestimated FDR can lead to unexpected false discoveries in the follow-up validation experiments. This issue has not been well addressed in literature, especially in the situation when the permutation procedure is necessary for p-value calculation. We proposed a statistical method for the conservative adjustment of q-value. In practice, it is usually necessary to calculate p-value by a permutation procedure. This was also considered in our adjustment method. We used simulation data as well as experimental microarray or sequencing data to illustrate the usefulness of our method. The conservativeness of our approach has been mathematically confirmed in this study. We have demonstrated the importance of conservative adjustment of q-value, particularly in the situation that the proportion of differentially expressed genes is small or the overall differential expression signal is weak.