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Genome-wide variant-based study of genetic effects with the largest neuroanatomic coverage
BACKGROUND: Brain image genetics provides enormous opportunities for examining the effects of genetic variations on the brain. Many studies have shown that the structure, function, and abnormality (e.g., those related to Alzheimer’s disease) of the brain are heritable. However, which genetic variati...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8086096/ https://www.ncbi.nlm.nih.gov/pubmed/33931008 http://dx.doi.org/10.1186/s12859-021-04145-0 |
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author | Li, Jin Liu, Wenjie Li, Huang Chen, Feng Luo, Haoran Bao, Peihua Li, Yanzhao Jiang, Hailong Gao, Yue Liang, Hong Fang, Shiaofen |
author_facet | Li, Jin Liu, Wenjie Li, Huang Chen, Feng Luo, Haoran Bao, Peihua Li, Yanzhao Jiang, Hailong Gao, Yue Liang, Hong Fang, Shiaofen |
author_sort | Li, Jin |
collection | PubMed |
description | BACKGROUND: Brain image genetics provides enormous opportunities for examining the effects of genetic variations on the brain. Many studies have shown that the structure, function, and abnormality (e.g., those related to Alzheimer’s disease) of the brain are heritable. However, which genetic variations contribute to these phenotypic changes is not completely clear. Advances in neuroimaging and genetics have led us to obtain detailed brain anatomy and genome-wide information. These data offer us new opportunities to identify genetic variations such as single nucleotide polymorphisms (SNPs) that affect brain structure. In this paper, we perform a genome-wide variant-based study, and aim to identify top SNPs or SNP sets which have genetic effects with the largest neuroanotomic coverage at both voxel and region-of-interest (ROI) levels. Based on the voxelwise genome-wide association study (GWAS) results, we used the exhaustive search to find the top SNPs or SNP sets that have the largest voxel-based or ROI-based neuroanatomic coverage. For SNP sets with >2 SNPs, we proposed an efficient genetic algorithm to identify top SNP sets that can cover all ROIs or a specific ROI. RESULTS: We identified an ensemble of top SNPs, SNP-pairs and SNP-sets, whose effects have the largest neuroanatomic coverage. Experimental results on real imaging genetics data show that the proposed genetic algorithm is superior to the exhaustive search in terms of computational time for identifying top SNP-sets. CONCLUSIONS: We proposed and applied an informatics strategy to identify top SNPs, SNP-pairs and SNP-sets that have genetic effects with the largest neuroanatomic coverage. The proposed genetic algorithm offers an efficient solution to accomplish the task, especially for identifying top SNP-sets. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-021-04145-0. |
format | Online Article Text |
id | pubmed-8086096 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-80860962021-04-30 Genome-wide variant-based study of genetic effects with the largest neuroanatomic coverage Li, Jin Liu, Wenjie Li, Huang Chen, Feng Luo, Haoran Bao, Peihua Li, Yanzhao Jiang, Hailong Gao, Yue Liang, Hong Fang, Shiaofen BMC Bioinformatics Research Article BACKGROUND: Brain image genetics provides enormous opportunities for examining the effects of genetic variations on the brain. Many studies have shown that the structure, function, and abnormality (e.g., those related to Alzheimer’s disease) of the brain are heritable. However, which genetic variations contribute to these phenotypic changes is not completely clear. Advances in neuroimaging and genetics have led us to obtain detailed brain anatomy and genome-wide information. These data offer us new opportunities to identify genetic variations such as single nucleotide polymorphisms (SNPs) that affect brain structure. In this paper, we perform a genome-wide variant-based study, and aim to identify top SNPs or SNP sets which have genetic effects with the largest neuroanotomic coverage at both voxel and region-of-interest (ROI) levels. Based on the voxelwise genome-wide association study (GWAS) results, we used the exhaustive search to find the top SNPs or SNP sets that have the largest voxel-based or ROI-based neuroanatomic coverage. For SNP sets with >2 SNPs, we proposed an efficient genetic algorithm to identify top SNP sets that can cover all ROIs or a specific ROI. RESULTS: We identified an ensemble of top SNPs, SNP-pairs and SNP-sets, whose effects have the largest neuroanatomic coverage. Experimental results on real imaging genetics data show that the proposed genetic algorithm is superior to the exhaustive search in terms of computational time for identifying top SNP-sets. CONCLUSIONS: We proposed and applied an informatics strategy to identify top SNPs, SNP-pairs and SNP-sets that have genetic effects with the largest neuroanatomic coverage. The proposed genetic algorithm offers an efficient solution to accomplish the task, especially for identifying top SNP-sets. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-021-04145-0. BioMed Central 2021-04-30 /pmc/articles/PMC8086096/ /pubmed/33931008 http://dx.doi.org/10.1186/s12859-021-04145-0 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Li, Jin Liu, Wenjie Li, Huang Chen, Feng Luo, Haoran Bao, Peihua Li, Yanzhao Jiang, Hailong Gao, Yue Liang, Hong Fang, Shiaofen Genome-wide variant-based study of genetic effects with the largest neuroanatomic coverage |
title | Genome-wide variant-based study of genetic effects with the largest neuroanatomic coverage |
title_full | Genome-wide variant-based study of genetic effects with the largest neuroanatomic coverage |
title_fullStr | Genome-wide variant-based study of genetic effects with the largest neuroanatomic coverage |
title_full_unstemmed | Genome-wide variant-based study of genetic effects with the largest neuroanatomic coverage |
title_short | Genome-wide variant-based study of genetic effects with the largest neuroanatomic coverage |
title_sort | genome-wide variant-based study of genetic effects with the largest neuroanatomic coverage |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8086096/ https://www.ncbi.nlm.nih.gov/pubmed/33931008 http://dx.doi.org/10.1186/s12859-021-04145-0 |
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