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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). For phenotypic information for the participants in this dataset, please also apply for access to the ADSP. A crosswalk file that maps the IDs between this dataset and the ADSP IDs is provided within this dataset.

Sample Summary per Data Type

Sample SetAccessionData TypeNumber of Samples
Camouflaged Variants snd10074Camouflaged Variants14,526

Available Filesets

NameAccessionLatest ReleaseDescription
Camouflaged Variants in VCF Formatfsa000090NG00116.v1Camouflaged Variants in VCF Format, README

View the File Manifest for a full list of files released in this dataset.

This sample set includes a .vcf file containing camouflaged variants from the 14,526 ADSP samples that were described in Ebbert et al. 2019. PMID: 31104630 This dataset was originally derived from the primary ADSP data available in NG00067.

Sample SetAccession NumberNumber of Subjects
Camouflaged Variants snd1007414,314
Consent LevelNumber of Subjects

Visit the Data Use Limitations page for definitions of the consent levels above.

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.

Use the study-specific acknowledgement statements below (as applicable):

For investigators using any data from this dataset:

Please cite/reference the use of NIAGADS data by including the accession NG00116.

For investigators using Resolving mutations in challenging genomic regions to test association with disease phenotypes (sa000042) 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).

Ebbert, M.T.W., Jensen, T.D., Jansen-West, K. et al. Systematic analysis of dark and camouflaged genes reveals disease-relevant genes hiding in plain sight. Genome Biol. 2019 May. doi: 10.1186/s13059-019-1707-2. PubMed link