IGES is finished today. Try to write down something before I may forget.
IGES oral presentations include many interesting topics including rare variants, secondary phenotype, gene pleiotropy, multiple phenotypes, gene-gene interactions, gene-environment interactions, and signaling pathways. I list some about rare variants and secondary/multiple phenotype discussion.
Though it's still early, it looks that people has started to work on mapping rare variants that are associated with diseases. I noticed that there are interesting and new methods about rare variants. Particularly, a work from David Conti and his student considered two directions when collapsing rare variants. A work from Qunyuan Zhang and Michael Province used p-value based sum which considered both the significance and the direction of rare variants. The work from Joon Sang Lee et al. also tried to identify the optimal pooling size for rare variants.
A secondary phenotype from J Wang and S. Shete considered the problem differently from ours. We and the ones including Danyu Lin considered the secondary phenotype conditional on the primary disease status. However, this work tries to correct the bias that may be brought in if consider the secondary phenotype as either a case or a control. There are also a bunch of studies about multiple phenotypes. This intrigues me to wonder whether the problem of multiple phenotypes should include the problem of the secondary phenotype. Or any inherent connection between them.
People used a lot of linear or logistic regression based models by adding more variants including GXG, GXE and others. A simple mind comes up: can we get better models instead of only logistic or linear models?
People also tried to use Bayesian to do some works. According to my observation, most people used Bayesian is only for the convenience of calculation. The strategies of incorporating prior information are not that mature now.