Abstract
Backgroundq-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.ResultsWe 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.ConclusionsThe 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.
Highlights
Microarray and sequencing technologies have been widely used in genome-wide expression experimental for biological and medical studies [1,2,3,4,5]
We proposed a statistical method for the conservative adjustment of q-value, which is one of the most frequently used procedure for estimating false discovery rate (FDR)
In this study, we proposed a statistical method for the conservative adjustment of q-value, which is widely used to estimate false discovery rate (FDR) in practice
Summary
Microarray and sequencing technologies have been widely used in genome-wide expression experimental for biological and medical studies [1,2,3,4,5]. After screening a large number of genes simultaneously, we expect to achieve new biological discoveries. In these situations, an important statistical concept is multiple hypothesis testing, in which many statistical tests are conducted at the same time. Since the introduction of microarray technology, the concept of false discovery rate (FDR) and its related statistical methods have been well developed [6, 7]. Q-value is a statistical method for the estimation of FDRs [8] It has been widely used in the analysis of microarray and sequencing data
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