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Bioinformatics. 2018 Aug 15;34(16):2724-2731. doi: 10.1093/bioinformatics/bty177.

Functional annotation of genomic variants in studies of late-onset Alzheimer's disease.

Author information

Department of Population and Quantitative Health Sciences, Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA.
Division of Medical Genetics, University of Washington, Seattle, WA, USA.
Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Division of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center, Houston, TX, USA.
Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Nationwide Children's Hospital, Columbus, OH, USA.



Annotation of genomic variants is an increasingly important and complex part of the analysis of sequence-based genomic analyses. Computational predictions of variant function are routinely incorporated into gene-based analyses of rare-variants, though to date most studies use limited information for assessing variant function that is often agnostic of the disease being studied.


In this work, we outline an annotation process motivated by the Alzheimer's Disease Sequencing Project, illustrate the impact of including tissue-specific transcript sets and sources of gene regulatory information and assess the potential impact of changing genomic builds on the annotation process. While these factors only impact a small proportion of total variant annotations (∼5%), they influence the potential analysis of a large fraction of genes (∼25%).

Availability and implementation:

Individual variant annotations are available via the NIAGADS GenomicsDB, at tools-and-software/databases/genomics-database. Annotations are also available for bulk download at Annotation processing software is available at

Supplementary information:

Supplementary data are available at Bioinformatics online.

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