The role of statistical power analysis in quantitative proteomics
The role of statistical power analysis in quantitative proteomics
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DOI：
10.1002/pmic.201100033
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发表时间：
2011-06-01
期刊：
影响因子：
3.4
通讯作者：
Levin, Yishai
中科院分区：
文献类型：
--
作者：
Levin, Yishai
设计一个定量蛋白质组学分析的实验不是一件小事。影响这类研究成功的关键因素之一是分析中包含的生物重复的数量。这与测量的变化一起将决定分析的统计能力。提出了一个简单而有力的分析，以确定可靠和可重复结果所需的适当样本量，基于总变异（技术和生物）。这种方法也可以回顾性地应用于结果的解释，因为它考虑了结果的显著性（p值）和数量差异（折次变化）。
Designing an experiment for quantitative proteomic analysis is not a trivial task. One of the key factors influencing the success of such studies is the number of biological replicates included in the analysis. This, along with the measured variation will determine the statistical power of the analysis. Presented is a simple yet powerful analysis to determine the appropriate sample size required for reliable and reproducible results, based on the total variation (technical and biological). This approach can also be applied retrospectively for the interpretation of results as it takes into account both significance (p value) and quantitative difference (fold change) of the results.