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| Title | Functional annotation of genomic variants in studies of late-onset Alzheimer's disease. |
| Publication Type | Journal Article |
| Year of Publication | 2018 |
| Authors | Butkiewicz M, Blue EE, Leung YYee, Jian X, Marcora E, Renton AE, Kuzma A, Wang L-S, Koboldt DC, Haines JL, Bush WS |
| Journal | Bioinformatics |
| Volume | 34 |
| Issue | 16 |
| Pagination | 2724-2731 |
| Date Published | 2018 Aug 15 |
| ISSN | 1367-4811 |
| 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. |
| DOI | 10.1093/bioinformatics/bty177 |
| Alternate Journal | Bioinformatics |
| PubMed ID | 29590295 |
| PubMed Central ID | PMC6084586 |
| Grant List | U01 AG032984 / AG / NIA NIH HHS / United States |