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本文引用的文献

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Quantifying the mapping precision of genome-wide association studies using whole-genome sequencing data.利用全基因组测序数据量化全基因组关联研究的定位精度
Genome Biol. 2017 May 16;18(1):86. doi: 10.1186/s13059-017-1216-0.
2
The OncoArray Consortium: A Network for Understanding the Genetic Architecture of Common Cancers.肿瘤阵列联盟：一个用于理解常见癌症遗传结构的网络。
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A reference panel of 64,976 haplotypes for genotype imputation.用于基因型插补的64976个单倍型参考面板。
Nat Genet. 2016 Oct;48(10):1279-83. doi: 10.1038/ng.3643. Epub 2016 Aug 22.
4
Genome-wide association analyses identify new risk variants and the genetic architecture of amyotrophic lateral sclerosis.全基因组关联分析确定了肌萎缩侧索硬化症的新风险变异和遗传结构。
Nat Genet. 2016 Sep;48(9):1043-8. doi: 10.1038/ng.3622. Epub 2016 Jul 25.
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The genetic architecture of type 2 diabetes.2型糖尿病的遗传结构
Nature. 2016 Aug 4;536(7614):41-47. doi: 10.1038/nature18642. Epub 2016 Jul 11.
6
Weighting sequence variants based on their annotation increases power of whole-genome association studies.基于注释对序列变异进行加权可提高全基因组关联研究的效能。
Nat Genet. 2016 Mar;48(3):314-7. doi: 10.1038/ng.3507. Epub 2016 Feb 8.
7
Imputation and subset-based association analysis across different cancer types identifies multiple independent risk loci in the TERT-CLPTM1L region on chromosome 5p15.33.跨不同癌症类型的插补和基于子集的关联分析在5号染色体p15.33区域的TERT-CLPTM1L基因座中鉴定出多个独立风险位点。
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8
Rare variants of large effect in BRCA2 and CHEK2 affect risk of lung cancer.BRCA2和CHEK2中具有大效应的罕见变异会影响肺癌风险。
Nat Genet. 2014 Jul;46(7):736-41. doi: 10.1038/ng.3002. Epub 2014 Jun 1.
9
Rare variants create synthetic genome-wide associations.罕见变异导致全基因组关联合成。
PLoS Biol. 2010 Jan 26;8(1):e1000294. doi: 10.1371/journal.pbio.1000294.

提高全基因组关联研究的定位精度：进行基因分型和推算、测序，还是两者兼而有之？

Increasing mapping precision of genome-wide association studies: to genotype and impute, sequence, or both?

作者信息

Wang Zhaoming, Chatterjee Nilanjan

机构信息

Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee, USA.

Department of Biostatistics, Bloomberg School of Public Health and Department of Oncology, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA.

出版信息

Genome Biol. 2017 Jun 19;18(1):118. doi: 10.1186/s13059-017-1255-6.

DOI:10.1186/s13059-017-1255-6
PMID:28629446
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5474869/
Abstract

Fine-mapping to identify causal variants in genome-wide association studies remains challenging. A recent study provides guidance for future research.

摘要

在全基因组关联研究中进行精细定位以识别因果变异仍然具有挑战性。最近的一项研究为未来的研究提供了指导。