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

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 inf...

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Autores principales: Butkiewicz, Mariusz, Blue, Elizabeth E, Leung, Yuk Yee, Jian, Xueqiu, Marcora, Edoardo, Renton, Alan E, Kuzma, Amanda, Wang, Li-San, Koboldt, Daniel C, Haines, Jonathan L, Bush, William S
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6084586/
https://www.ncbi.nlm.nih.gov/pubmed/29590295
http://dx.doi.org/10.1093/bioinformatics/bty177
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author Butkiewicz, Mariusz
Blue, Elizabeth E
Leung, Yuk Yee
Jian, Xueqiu
Marcora, Edoardo
Renton, Alan E
Kuzma, Amanda
Wang, Li-San
Koboldt, Daniel C
Haines, Jonathan L
Bush, William S
author_facet Butkiewicz, Mariusz
Blue, Elizabeth E
Leung, Yuk Yee
Jian, Xueqiu
Marcora, Edoardo
Renton, Alan E
Kuzma, Amanda
Wang, Li-San
Koboldt, Daniel C
Haines, Jonathan L
Bush, William S
author_sort Butkiewicz, Mariusz
collection PubMed
description 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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spelling pubmed-60845862018-08-14 Functional annotation of genomic variants in studies of late-onset Alzheimer’s disease Butkiewicz, Mariusz Blue, Elizabeth E Leung, Yuk Yee Jian, Xueqiu Marcora, Edoardo Renton, Alan E Kuzma, Amanda Wang, Li-San Koboldt, Daniel C Haines, Jonathan L Bush, William S Bioinformatics Original Papers 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. Oxford University Press 2018-08-15 2018-03-24 /pmc/articles/PMC6084586/ /pubmed/29590295 http://dx.doi.org/10.1093/bioinformatics/bty177 Text en © The Author(s) 2018. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Original Papers
Butkiewicz, Mariusz
Blue, Elizabeth E
Leung, Yuk Yee
Jian, Xueqiu
Marcora, Edoardo
Renton, Alan E
Kuzma, Amanda
Wang, Li-San
Koboldt, Daniel C
Haines, Jonathan L
Bush, William S
Functional annotation of genomic variants in studies of late-onset Alzheimer’s disease
title Functional annotation of genomic variants in studies of late-onset Alzheimer’s disease
title_full Functional annotation of genomic variants in studies of late-onset Alzheimer’s disease
title_fullStr Functional annotation of genomic variants in studies of late-onset Alzheimer’s disease
title_full_unstemmed Functional annotation of genomic variants in studies of late-onset Alzheimer’s disease
title_short Functional annotation of genomic variants in studies of late-onset Alzheimer’s disease
title_sort functional annotation of genomic variants in studies of late-onset alzheimer’s disease
topic Original Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6084586/
https://www.ncbi.nlm.nih.gov/pubmed/29590295
http://dx.doi.org/10.1093/bioinformatics/bty177
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