Validation is an evolving process and the documentation should reflect the experiences of users as they discover new and useful bits of information. Updating the docs is easy, and you can share comments and questions at this forum.

Validate 1.0

Validation is the positive control for your experimental data analysis. You have control over how long data analysis takes. Completing your positive controls first allows you to be ready for your data when you get it. Why validate a particular data analysis?

  • Trust but verify: check that a widely used method will work for your data.
  • Have analysis pipeline optimized; the moment you’ve collected all your data you can start the analysis (saving weeks or months to complete afterwards)
  • Fewer requests from reviewers for changes to your data analysis methods
  • Be confident you are doing the best possible data analysis

The CyVerse Validate workflow is versatile enough to handle you importing your GWAS tools, functions, or simulation methods to use in conjunction with the existing software. Speaking of imports, Validate is capable of handling a range of file formats, and each piece of software is very customizable. You have multiple options for adjusting your output each step of the way.

Finally, since the analysis are run on the NSF-supported national XSEDE computer systems, scalability of simulations is a non-issue; the computational demand for your simulations will scale up as your needs increase. All of your necessary files may be uploaded and accessed from the CyVerse Data Store.

Version 1.0 Features

Version 1.0 features include:

  • The ability to test prediction
  • Incorporate the following prediction applications: GenSel, BayesR, BLR/BATools, ridge regression
  • Updated Demonstrate to handle prediction graphics
  • Managing GWAS and prediction applications in parallel
  • Incorporate D. Hand’s H-measure to the current performance metrics
  • Additional documentation to onboard new developers and statisticians