Biomarker discovery with microarray and genetic data sets is complicated by the fact that there are often far more biomarkers than samples. The goal is to reduce the number of informative markers for further testing and to determine how the genetic biomarkers rank versus other clinical markers. JMP Genomics offers a number of different methods available for predictive modeling with a model comparison capability to determine the best overall fit. In this session, you will see tools for:
- Candidate marker reduction.
- Cross-validation methods.
- Ranking models and candidate markers.
- Whole-model fit.
- Special case – survival predictive modeling.
JMP Technical Specialist Doug Robinson, PhD, who supports JMP Genomics and JMP Clinical life sciences software from SAS, will teach you how to easily start making discoveries on your own.