Sample Size Estimation while Controlling False Discovery Rate for Microarray Experiments Using the ssize.fdr Package
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چکیده
منابع مشابه
Sample Size Estimation while Controlling False Discovery Rate for Microarray Experiments Using the ssize.fdr Package
Microarray experiments are becoming more and more popular and critical in many biological disciplines. As in any statistical experiment, appropriate experimental design is essential for reliable statistical inference, and sample size has a crucial role in experimental design. Because microarray experiments are rather costly, it is important to have an adequate sample size that will achieve a de...
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1 Summary. Sample size estimation is important in microarray or proteomic experiments since biologists can typically afford only a few repetitions. Classical procedures to calculate sample size are based on controlling type I error, e.g., family-wise error rate (FWER). In the context of microarray and other large-scale genomic data, it is more powerful and more reasonable to control false disco...
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mRNA Expression Microarray technology is widely applied in biomedical and pharmaceutical research. The huge number of mRNA concentrations estimated for each sample make it difficult to apply traditional sample size calculation techniques and has left most practitioners to rely on rule-of-thumb techniques. In this paper, we briefly describe and then demonstrate a simple method for performing and...
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MOTIVATION In microarray data studies most researchers are keenly aware of the potentially high rate of false positives and the need to control it. One key statistical shift is the move away from the well-known P-value to false discovery rate (FDR). Less discussion perhaps has been spent on the sensitivity or the associated false negative rate (FNR). The purpose of this paper is to explain in s...
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ژورنال
عنوان ژورنال: The R Journal
سال: 2009
ISSN: 2073-4859
DOI: 10.32614/rj-2009-019