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 journalArticlepeer-review

23 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 - Aug 15 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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