Abstract P390: E-value Over P-value And Its Adjustments: Improving Dna Methylation Analysis With An Application To Hypertension Studies

Abstract

DNA methylation plays a crucial role in transcriptional regulation. Reduced representation bisulfite sequencing (RRBS) is a technique of increasing use for analyzing genome-wide methylation profiles. Many computational tools such as Metilene, MethylKit, BiSeq and DMRfinder have been developed to use RRBS data to detect differentially methylated regions (DMRs) that may be involved in epigenetic regulations of gene expression. For DMR detection tools, as for countless other medical literature applications, P-values and their adjustments are among the most widely reported statistics used to assess the statistical significance of biological findings. However, P-values are coming under increasing criticism related to their questionable accuracy and relatively high levels of false positive or negative indications. Here, we proposed a method to calculate E-value for DMR detection in RRBS data, which is defined as likelihood ratios falling into the null hypothesis over the entire parameter space. We also provided the corresponding R package ‘ metevalue ’ as a user-friendly interface to implement E-value calculations into various DMR detection tools. To evaluate the performance of E-value, we generated various RRBS benchmarking datasets using our simulator ‘ RRBSsim ’ with 8 samples in each experimental group. Our comprehensive benchmarking analyses showed that using E-value not only significantly improved accuracy, AUC and power, over that of P-value or adjusted P-value, but also reduced false discovery rates and Type I errors. To illustrate the utility of E-value, we applied it to identify DMRs in two real RRBS datasets. One was genome-wide DNA methylome and transcriptome of renal T lymphocytes from Dahl Salt Sensitive rats treated with high- or low-salt diets. The other was genome-wide DNA methylation and gene expression data of human arterioles from our clinical trial in which 10 subjects were placed on 2-week low-salt diet (1200-mg sodium/day). Compared to the classical adjusted P-value, the use of E-value detected biologically more relevant DMRs and improved the negative association between DNA methylation and gene expression.