With ASHG only four weeks away, the hype has only continued to grow. The 64th Annual Meeting of the American Society of Human Genetics is shaping up to be one of the best with some amazing abstracts, including one from our very own Greta Linse Peterson. Greta will be presenting Monday, October 20th in room 20A at 6:15 PM in the Statistical Methods for Population Based Studies session on “A logistic mixed model approach to obtain a reduced model score for KBAC to adjust for population structure and relatedness between samples.”
Current methods do not readily extend to a logistic regression framework and use mixed-model logistic regression on a binary dependent variable to account for population structure and cryptic relatedness. Golden Helix has implemented a new solution that combines a mixed model regression analysis with the KBAC (Kernel-Based Adaptive Cluster method) in order to access the rare variant burden.
While several linear mixed model regressions are available on a genome-wide scale, it can be useful to efficiently solve a logistic mixed model regression for every gene. That being said, Golden Helix has derived a transformed linear pseudo-model for solving the logistic mixed model equation optimized using EMMA (Efficient Mixed Model Algorithm) and pre-computed and reused the permutations for KBAC and the reduced models for those permutations to give us MM-KBAC.
If you have any questions or would like to see how the method works for yourself, please let us know. We look forward to seeing you at ASHG – and don’t forget that we will be unveiling our new Golden Helix t-shirts from our design contest. Stay tuned for more info on our scheduled giveaways or swing by booth 422 at ASHG to find out how to get your hands on one!