Document Type
Presentation
Publication Date
11-20-2012
Subjects
Bioinformatics, Genetics, System theory
Abstract
Reconstructability Analysis (RA) is an information- and graph-theory-based method which has been successfully used in previous genomic studies. Here we apply it to genetic (14 SNPs) and non-genetic (Education, Age, Gender) data on Alzheimer disease in a well-characterized Case/Control sample of 424 individuals. We confirm the importance of APOE as a predictor of the disease, and identify one non-genetic factor, Education, and two SNPs, one in BINI and the other in SORCS1, as likely disease predictors. SORCS1 appears to be a common risk factor for people with or without APOE. We also identify a possible interaction effect between Education and BINI. Methodologically, we introduce and use to advantage some more powerful features of RA not used in prior genomic studies.
Keywords: Reconstructability Analysis, Alzheimer Disease, Genetics, Bioinformatics, OCCAM
Rights
This is the accepted version of paper presented at an IEEE meeting. The final version is available here: https://ieeexplore.ieee.org/document/6505196
Persistent Identifier
https://archives.pdx.edu/ds/psu/42745
Citation Details
Kramer, P., Westaway, S., Zwick, M., and Shervais, S. (2012) "Reconstructability Analysis of Genetic Loci Associated with Alzheimer Disease." IEEE 6th International Conference on Soft Computing and Intelligent Systems and13th International Symposium on Advanced Intelligent Systems, SCIS-ISIS2012, Kobe, Japan, Nov. 20-24, 2012.
Included in
Bioinformatics Commons, Data Science Commons, Genetics and Genomics Commons, Neuroscience and Neurobiology Commons