Many regions of the human genome present challenges that prohibit scientists from discovering potential disease causing mutations. We developed methods to characterize mutations in these regions to rescue mutations that are otherwise overlooked. PMID: 31104630
Provided here are variant calls in VCF format for 14,526 samples derived from the ADSP whole-exome and whole-genome sequencing dataset (available via DSS: NG00067).

Mark Ebbert, Ph.D.
University of Kentucky

John Fryer, Ph.D.
Mayo Clinic

Leonard Petrucelli, M.D., Ph.D.
Mayo Clinic

R01 AG068331-02: Using long-range technologies as a multi-omic approach to understand Alzheimer’s disease in brain tissue

R35 GM138636: Understanding how structural mutations and individual RNA isoforms are involved in human health and disease

Acknowledgment statement for any data distributed by NIAGADS:

Data for this study were prepared, archived, and distributed by the National Institute on Aging Alzheimer's Disease Data Storage Site (NIAGADS) at the University of Pennsylvania (U24-AG041689), funded by the National Institute on Aging.

For investigators using Resolving mutations in challenging genomic regions to test association with disease phenotypes data:

This work was funded by the following grants awarded to Dr. Mark Ebbert from: (1) the NIH (NIA: R01AG068331 and NIGMS: R35GM138636), the Alzheimer’s Association (2019-AARG-644082), and the BrightFocus Foundation (A2020161S). Additional support from the NIH/NCATS awarded to Dr. P. Kern (UL1 TR001998).