I wonder how to evaluate the performance of the tools that associate a variable (example: SNP, gene...) with a phenotype. In a few papers [1,2], people would wonder whether found traits improve prediction of a phenotype. Is this the correct way to evaluate the associated traits? What does it mean if an associated trait doesn't improve prediction of the phenotype?

I have also a few related questions to the subject:
1) Is there a difference in "properties" of variables that are good for prediction and those that are good for association (example : variability in between patients)?

2) Why would we sometimes go for techniques that associate a variable (example: SNP, gene) to an outcome variable (example: phenotype), rather than a technique that improves prediction?

Thank you a lot in advance for your responses!


[1]Dufresne, L. et al. (2014). Pathway analysis for genetic association studies: to do, or not to do? That is the question. BMC Proceedings doi:10.1186/1753-6561-8-S1-S103,

[2]Staiger, C., Cadot, S., Kooter, R., Dittrich, M., Müller, T., Klau, G. W., & Wessels, L. F. a. (2012). A critical evaluation of network and pathway-based classifiers for outcome prediction in breast cancer. PloS One, 7(4), e34796. doi:10.1371/journal.pone.0034796)