Development of detection and feature selection methods for small copy number variations in non-oncology studies

In this project summarization and copy number call methods for Affymetrix Gemome-Wide SNP and CNV arrays are developed with respect to reduce the false discovery rate. These methods extent our FARMS algorithm that is succefully applied to transcriptomics to the field of genetics. Goal is to detect and associate small copy number variations with complex diseases like multiple sclerosis and Alzheimer. In a second part supervised feature selection methods should identify CNVs or CNV patterns which are predictive for the disease that is are genetically related to the disease. Using these genetic markers a classifier should be able to predict genetic risks for the disease.