In part one, we simulated a successive of two-armed randomized clinical trial with the time-to-event outcome over 15 years. We used three different accrual pattern representing slow, medium and fast accrual, which is in fact related to the number of trials for the sequential trials interested in the 15-year period. We used a historical survival distribution to explore the treatment effects and analyzed by the Cox proportional hazard ratio model and log-rank test. We computed the mean and median overall hazard ratio (year 15 versus year 0), and the probability of detrimental effect to find the optimal design parameters. Finally, we carried out a sensitivity analysis to study the effect of an additional 6 month turnaround time. In Part two, we have described a general workflow for the normalization of ChIP-seq data by estimating the normalization factor from peak-less regions. Using publicly available histone 3 lysine 36 trimethylation (H3K36me3) data from human kidney cancer, we demonstrated the better performance of our method over the existing approach.
University of Minnesota M.S. thesis.July 2017. Major: Biomedical Informatics and Computational Biology. Advisors: Karla Ballman, Huihuang Yan. 1 computer file (PDF); viii, 49 pages.
A Simulation Study of Patient Accrual Patterns in Clinical Trials and Data Analysis of Histone 3 Lysine 36 Trimethylation ChIP-seq in Human Kidney Cancer.
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