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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

1
Department of Population and Quantitative Health Sciences, Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA.
2
Division of Medical Genetics, University of Washington, Seattle, WA, USA.
3
Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA.
4
Division of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center, Houston, TX, USA.
5
Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
6
Nationwide Children's Hospital, Columbus, OH, USA.

Abstract

Motivation:

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.

Results:

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 https://www.niagads.org/genomics/ tools-and-software/databases/genomics-database. Annotations are also available for bulk download at https://www.niagads.org/datasets. Annotation processing software is available at http://www.icompbio.net/resources/software-and-downloads/.

Supplementary information:

Supplementary data are available at Bioinformatics online.

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