Tutorial- Monday at 3:00 PM EDT
Title: Network Analysis of RNA Sequence and Drug Safety Data
Presenters: Kai-Tai Tsai, JPHCOPH & BMS; Karl Peace JPHCOPH

Abstract:
"In the conventional statistical data analysis, to keep the model parsimonious, most of the correlated variables are usually eliminated except for one. However, in genomics RNA sequence data analysis, this is not appropriate because the genes are usually working together in a modular consists of several highly-correlated genes. To eliminate most of the genes except for one does not fully reflect the natural of functionality of genomics data.
In this research, we demonstrate how this issue can be dealt with using network analysis, which groups the correlated genes into a modular and use that to evaluate the effect on the outcome variables. Similar approaches can be applied to drug safety data as the adverse events are usually correlated. Using network analysis to analyze drug safety data provides a more in-depth examination about how the treatment affects drug safety. Data from clinical trials will be used to illustrate the approaches."


References:



Targeted Learning in Data Science, Causal Inference for Complex Longitudinal Studies, Springer New York, van der Laan, Rose (2018)



Bio:
Kao-Tai Tsai obtained his Ph.D. in Mathematical Statistics from University of California, San Diego and had worked at AT&T Bell Laboratories to conduct statistical research, modeling, and exploratory data analysis. After that, he joined the US FDA and later pharmaceutical companies focusing on biostatistics, clinical trial research and data analysis to address the unmet needs in human health.
He has been quite active in statistical profession and had engaged in numerous invited lectures, short courses, presentations and seminars on practical statistical issues related to clinical trials. In addition, he had also served as President of the NJ chapter of the ASA, member of the Board of Directors and various committees of ICSA, and symposium organizers for several professional organizations. His recent research includes topics in clinical trials, biomarkers, big data analysis, and applications of statistical graphics in data analysis."