Data Visualization for Life Sciences with JMP (ADDED FEE) — Professional Development Computer Technology Workshop
ASA , JMP , SAS
Statisticians are extremely effective at analyzing complex data; however, many struggle to communicate the story hidden within the data to their colleagues. Due to the high cost of conducting clinical and translational life science research, it is common to collect as much data as possible on multiple endpoints. For example, in a clinical trial one will collect data for safety, efficacy, and clinical site operational metrics. The data collected on each patient is also growing, often including biological/genomic data. In this environment, the traditional means of data summary - tables and listings - are ineffective for gaining insight; visualization is key to effective communication for the modern statistician. The goal of this workshop is to describe data visualization techniques for understanding and communicating results from applications in clinical trials and genomics research using the JMP family of products (JMP, JMP Pro, JMP Clinical, and JMP Genomics). Topics include distributional summaries, signal detection safety outcomes, findings trends and abnormalities, data integrity, co-occurrence, clustering and correlations, genomic associations, subgroup analysis, and meta-analysis.
Instructor(s): Kelci Miclaus, JMP Life Sciences, SAS Institute Inc., Richard C. Zink, JMP Life Sciences, SAS Institute, Inc.
