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DOI 10.1093/bioinformatics/bty177

Медицинская библиотека · Bioinformatics (Oxford, England) · 2018

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

СтатьяПоддержка NIH: внешняя программаПеревод пока не подготовлен

Аннотация

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.

Для цитирования: 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.. Bioinformatics (Oxford, England). 2018. DOI: 10.1093/bioinformatics/bty177.

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