Mathematics, Statistics, and Computer Science
GAW20, methylation, triglycerides, analysis, simulation methods, testing
Although methylation data continues to rise in popularity, much is still unknown about how to best analyze methylation data in genome-wide analysis contexts. Given continuing interest in gene-based tests for next-generation sequencing data, we evaluated the performance of novel gene-based test statistics on simulated data from GAW20. Our analysis suggests that most of the gene-based tests are detecting real signals and maintaining the Type I error rate. The minimum pvalue and threshold-based tests performed well compared to single-marker tests in many cases, especially when the number of variants was relatively large with few true causal variants in the set.
Source Publication Title
Vander Woude, J., Huisman, J., Vander Berg, L., Veenstra, J., Bos, A., Kalsbeek, A., Koster, K., Ryder, N., & Tintle, N. L. (2018). Evaluating the Performance of Gene-Based Tests of Genetic Association when Testing for Association Between Methylation and Change in Triglyceride Levels at GAW20. BMC Proceedings, 12 (Supp. 9), 50. Retrieved from https://digitalcollections.dordt.edu/faculty_work/1027