Balancing false discovery and false negative rates in selection of differentially expressed genes in microarrays

A general method for accurate estimation of false discovery rates in identification of differentially expressed genes

UNLABELLED The 'omic' data such as genomic data, transcriptomic data, proteomic data and single nucleotide polymorphism data have been rapidly growing. The omic data are large-scale and high-throughput data. Such data challenge traditional statistical methodologies and require multiple tests. Several multiple-testing procedures such as Bonferroni procedure, Benjamini-Hochberg (BH) procedure and...

Identifying differentially expressed genes using false discovery rate controlling procedures

MOTIVATION DNA microarrays have recently been used for the purpose of monitoring expression levels of thousands of genes simultaneously and identifying those genes that are differentially expressed. The probability that a false identification (type I error) is committed can increase sharply when the number of tested genes gets large. Correlation between the test statistics attributed to gene co...

Microarrays, Empirical Bayes Methods, and False Discovery Rates

False Discovery Rates

In hypothesis testing, statistical significance is typically based on calculations involving p-values and Type I error rates. A p-value calculated from a single statistical hypothesis test can be used to determine whether there is statistically significant evidence against the null hypothesis. The upper threshold applied to the p-value in making this determination (often 5% in the scientific li...

Local False Discovery Rates

Modern scientific technology is providing a new class of large-scale simultaneous inference problems, with hundreds or thousands of hypothesis tests to consider at the same time. Microarrays epitomize this type of technology but similar problems arise in proteomics, time of flight spectroscopy, flow cytometry, FMRI imaging, and massive social science surveys. This paper uses local false discove...