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三种 Illumina 芯片在炎症和免疫相关通路方面的全球、通路和基因覆盖度。

Global, pathway and gene coverage of three Illumina arrays with respect to inflammatory and immune-related pathways.

机构信息

Department of Genetic Epidemiology, University Medical Centre, Georg-August-University, 37075, Göttingen, Germany.

Department of Haematology and Oncology, University Medical Centre, Georg-August-University, 37075, Göttingen, Germany.

出版信息

Eur J Hum Genet. 2019 Nov;27(11):1716-1723. doi: 10.1038/s41431-019-0441-2. Epub 2019 Jun 21.

DOI:10.1038/s41431-019-0441-2
PMID:31227809
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6871524/
Abstract

Genome-wide association studies have led in the past to the discovery of susceptibility genes for many diseases including cancer and inflammatory conditions. However, a number of these studies did not realise their full potential. A first critical step in developing such large-scale studies is the choice of genotyping array with respect to the study goal. Coverage is the central criterion for array evaluation. We distinguish between estimates of global coverage across the genome, coverage for each chromosome, coverage for selected pathways and the coverage for genes of interest. Here, we focus on inflammatory and immunological pathways and genes relevant for haematopoietic stem cell transplantation. We compared three arrays: the Infinium Global Screening Array-24 v1.0, the Infinium OncoArray-500 K BeadChip and the Infinium PsychArray-24 v1.2 BeadChip. We employed the European population from the 1000 Genomes Project as reference genome. Global coverage was found to range between 12.2 and 14.2% whereas coverage for a selected pathway ranged from 6.2 to 13.2% and gene coverage ranged from 0 to 54.1%. The Global Screening Array outperformed both other arrays in terms of global coverage, for most chromosomes, most considered pathways and most genes. When selecting suitable arrays for a new study, the coverage of pathways or genes of interest should be considered in addition to global coverage. Local coverage should be regarded when discussing association findings inconsistent across studies and can be useful in data analysis and decision making for additional genotyping.

摘要

全基因组关联研究过去已经导致了许多疾病(包括癌症和炎症性疾病)的易感基因的发现。然而,其中一些研究并没有充分发挥其潜力。开发此类大规模研究的关键步骤之一是根据研究目标选择基因分型阵列。覆盖范围是阵列评估的核心标准。我们区分了基因组中总体覆盖范围、每条染色体的覆盖范围、选定途径的覆盖范围和感兴趣基因的覆盖范围。在这里,我们重点关注炎症和免疫途径以及与造血干细胞移植相关的基因。我们比较了三种阵列:Infinium Global Screening Array-24 v1.0、Infinium OncoArray-500K BeadChip 和 Infinium PsychArray-24 v1.2 BeadChip。我们使用 1000 基因组计划中的欧洲人群作为参考基因组。全球覆盖率范围在 12.2%至 14.2%之间,而选定途径的覆盖率范围在 6.2%至 13.2%之间,基因覆盖率范围在 0%至 54.1%之间。在全球覆盖方面,Global Screening Array 在大多数染色体、大多数考虑的途径和大多数基因方面均优于其他两种阵列。在为新研究选择合适的阵列时,除了全球覆盖范围之外,还应考虑感兴趣的途径或基因的覆盖范围。在讨论不一致的研究中的关联发现时,应考虑局部覆盖范围,并且在数据分析和额外基因分型的决策中可能很有用。

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