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

Mariusz Butkiewicz, Elizabeth E. Blue, Yuk Yee Leung, Xueqiu Jian, Edoardo Marcora, Alan E. Renton, Amanda Kuzma, Li San Wang, Daniel C. Koboldt, Jonathan L. Haines, William S. Bush

Research output: Contribution to journalArticle

9 Scopus citations

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/.

Original languageEnglish (US)
Pages (from-to)2724-2731
Number of pages8
JournalBioinformatics
Volume34
Issue number16
DOIs
StatePublished - 2018
Externally publishedYes

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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