This case study focuses on how to use JMP Pro 17 for 'omic data analysis, specifically metabolite data. It primarily looks at differential gene expression (DGE) workflow and adds predictive modeling. This type of analysis is typical of Translational Scientists/Biomarker Researchers.
This case study can be used to give demos to customers by SEs for those interested in analyzing 'omic data in the clinical research space. It is designed so that you can show only the capabilities that are requested by the customer (use Great Demo! method) but also in context to the whole analytic workflow of analyzing this kind of data. If you do try to demo all of the capabilities, it will take you over an hour since there are many capabilities that are used.
The included journal contains output as well as script buttons to perform the analysis at each step. There are also script buttons that perform some data manipulation tasks as well.
The Venn Diagram add-in could also be used.
What's Available
- A journal with an introduction to the workflow, the scientific/research question, and the data set used
- JMP Project that contains files, journal, analysis results and data tables
- The data set so you can do it yourself
Why is this useful?
- JMP Genomics as a product was discontinued earlier this year so we need case studies to show how to perform 'omic analysis in JMP Pro 17
- It also highlights what is new in JMP/JMP Pro 17 for wide data, especially in the context of 'omic data
- It additionally is meant to help SEs become more self-sufficient in given demos and talking about capabilities in the 'omic space
- Data analysis in the 'omic world can be scripted/workflow oriented or exploratory in nature. This case study will focus on the more exploratory nature of data analysis and not the "automated" or scripted type analysis. One can convert the steps into a workflow using JMP Pro 17's workflow building capabilities. I will try to create one and attach it to this case study as a proof of concept in the near future.
