Correcting for cell-type heterogeneity in epigenome-wide association studies: revisiting previous analyses.
作者信息
Zheng Shijie C, Beck Stephan, Jaffe Andrew E, Koestler Devin C, Hansen Kasper D, Houseman Andres E, Irizarry Rafael A, Teschendorff Andrew E
机构信息
CAS Key Lab of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai, China.
University of Chinese Academy of Sciences, Beijing, China.
出版信息
Nat Methods. 2017 Feb 28;14(3):216-217. doi: 10.1038/nmeth.4187.
Abstract
摘要
相似文献
1
Correcting for cell-type heterogeneity in epigenome-wide association studies: revisiting previous analyses.在全表观基因组关联研究中校正细胞类型异质性：重新审视以往分析。
Nat Methods. 2017 Feb 28;14(3):216-217. doi: 10.1038/nmeth.4187.
2
Detection of cell-type-specific risk-CpG sites in epigenome-wide association studies.在全基因组关联研究中检测细胞类型特异性风险-CpG 位点。
Nat Commun. 2019 Jul 15;10(1):3113. doi: 10.1038/s41467-019-10864-z.
3
Epigenome-wide association study of incident type 2 diabetes: a meta-analysis of five prospective European cohorts.全基因组表观遗传关联研究分析 2 型糖尿病发病风险：五个欧洲前瞻性队列的荟萃分析。
Diabetologia. 2022 May;65(5):763-776. doi: 10.1007/s00125-022-05652-2. Epub 2022 Feb 15.
4
CpG island mapping by epigenome prediction.通过表观基因组预测进行CpG岛定位
PLoS Comput Biol. 2007 Jun;3(6):e110. doi: 10.1371/journal.pcbi.0030110. Epub 2007 May 2.
5
Sparse PCA corrects for cell type heterogeneity in epigenome-wide association studies.稀疏主成分分析在全表观基因组关联研究中校正细胞类型异质性。
Nat Methods. 2016 May;13(5):443-5. doi: 10.1038/nmeth.3809. Epub 2016 Mar 28.
6
Computationally inferred cell-type specific epigenome-wide DNA methylation analysis unveils distinct methylation patterns among immune cells for HIV infection in three cohorts.计算推断的细胞类型特异性表观基因组范围的 DNA 甲基化分析揭示了三个队列中 HIV 感染免疫细胞之间的不同甲基化模式。
PLoS Pathog. 2024 Mar 11;20(3):e1012063. doi: 10.1371/journal.ppat.1012063. eCollection 2024 Mar.
7
Blood-based epigenome-wide analyses of 19 common disease states: A longitudinal, population-based linked cohort study of 18,413 Scottish individuals.基于血液的 19 种常见疾病状态的表观基因组全基因组分析：对 18413 名苏格兰个体进行的纵向、基于人群的关联队列研究。
PLoS Med. 2023 Jul 6;20(7):e1004247. doi: 10.1371/journal.pmed.1004247. eCollection 2023 Jul.
8
Epigenome-Wide DNA Methylation Association Analysis Identified Novel Loci in Peripheral Cells for Alcohol Consumption Among European American Male Veterans.基于外周血细胞的全基因组 DNA 甲基化关联分析鉴定出欧洲裔美国男性退伍军人饮酒行为的新关联位点
Alcohol Clin Exp Res. 2019 Oct;43(10):2111-2121. doi: 10.1111/acer.14168. Epub 2019 Aug 30.
9
DNA methylation in childhood asthma: an epigenome-wide meta-analysis.儿童哮喘中的 DNA 甲基化：全基因组甲基化元分析。
Lancet Respir Med. 2018 May;6(5):379-388. doi: 10.1016/S2213-2600(18)30052-3. Epub 2018 Feb 26.
10
Epigenome-Wide Association Study Reveals CpG Sites Associated with Thyroid Function and Regulatory Effects on .全基因组关联研究揭示了与甲状腺功能相关的 CpG 位点，并揭示了其对. 的调控作用。
Thyroid. 2023 Mar;33(3):301-311. doi: 10.1089/thy.2022.0373. Epub 2023 Mar 1.
引用本文的文献
1
Accounting for differences between Infinium MethylationEPIC v2 and v1 in DNA methylation-based tools.在基于DNA甲基化的工具中考虑Infinium甲基化EPIC v2和v1之间的差异。
Life Sci Alliance. 2025 Jul 8;8(9). doi: 10.26508/lsa.202403155. Print 2025 Sep.
2
Reference-free deconvolution of complex samples based on cross-cell-type differential analysis: Systematic evaluations with various feature selection options.基于跨细胞类型差异分析的复杂样本无参考去卷积：使用各种特征选择选项的系统评估
Front Genet. 2025 May 30;16:1570781. doi: 10.3389/fgene.2025.1570781. eCollection 2025.
3
Unified high-resolution immune cell fraction estimation in blood tissue from birth to old age.从出生到老年血液组织中统一的高分辨率免疫细胞分数估计。
Genome Med. 2025 May 27;17(1):63. doi: 10.1186/s13073-025-01489-7.
4
Examining cellular heterogeneity in human DNA methylation studies: Overview and recommendations.人类DNA甲基化研究中的细胞异质性检测：综述与建议
STAR Protoc. 2025 Mar 21;6(1):103638. doi: 10.1016/j.xpro.2025.103638. Epub 2025 Feb 12.
5
Epigenetic ageing clocks: statistical methods and emerging computational challenges.表观遗传衰老时钟：统计方法与新出现的计算挑战
Nat Rev Genet. 2025 May;26(5):350-368. doi: 10.1038/s41576-024-00807-w. Epub 2025 Jan 13.
6
Deconvolution from bulk gene expression by leveraging sample-wise and gene-wise similarities and single-cell RNA-Seq data.通过利用样本和基因之间的相似性以及单细胞 RNA-Seq 数据进行批量基因表达的反卷积。
BMC Genomics. 2024 Sep 18;25(1):875. doi: 10.1186/s12864-024-10728-x.
7
Discrepancies in readouts between Infinium MethylationEPIC v2.0 and v1.0 reflected in DNA methylation-based tools: implications and considerations for human population epigenetic studies.基于DNA甲基化的工具所反映的Infinium甲基化EPIC v2.0和v1.0之间读数差异：对人类群体表观遗传学研究的影响与考量
bioRxiv. 2024 Sep 28:2024.07.02.600461. doi: 10.1101/2024.07.02.600461.
8
An improved epigenetic counter to track mitotic age in normal and precancerous tissues.一种改良的表观遗传计数器，用于追踪正常和癌前组织中的有丝分裂年龄。
Nat Commun. 2024 May 17;15(1):4211. doi: 10.1038/s41467-024-48649-8.
9
A meta-analysis of immune-cell fractions at high resolution reveals novel associations with common phenotypes and health outcomes.高分辨率免疫细胞分数的荟萃分析揭示了与常见表型和健康结果的新关联。
Genome Med. 2023 Jul 31;15(1):59. doi: 10.1186/s13073-023-01211-5.
10
Cell-Type Deconvolution of Bulk DNA Methylation Data with EpiSCORE.使用 EpiSCORE 对批量 DNA 甲基化数据进行细胞类型去卷积。
Methods Mol Biol. 2023;2629:23-42. doi: 10.1007/978-1-0716-2986-4_3.
本文引用的文献
1
Sparse PCA corrects for cell type heterogeneity in epigenome-wide association studies.稀疏主成分分析在全表观基因组关联研究中校正细胞类型异质性。
Nat Methods. 2016 May;13(5):443-5. doi: 10.1038/nmeth.3809. Epub 2016 Mar 28.
2
Accounting for cellular heterogeneity is critical in epigenome-wide association studies.在全表观基因组关联研究中，考虑细胞异质性至关重要。
Genome Biol. 2014 Feb 4;15(2):R31. doi: 10.1186/gb-2014-15-2-r31.
3
Epigenome-wide association studies without the need for cell-type composition.无需细胞类型组成的全基因组关联研究。
Nat Methods. 2014 Mar;11(3):309-11. doi: 10.1038/nmeth.2815. Epub 2014 Jan 26.
4
Reference-free cell mixture adjustments in analysis of DNA methylation data.无参考细胞混合物调整在 DNA 甲基化数据分析中的应用。
Bioinformatics. 2014 May 15;30(10):1431-9. doi: 10.1093/bioinformatics/btu029. Epub 2014 Jan 21.
5
Epigenome-wide association data implicate DNA methylation as an intermediary of genetic risk in rheumatoid arthritis.全基因组关联数据表明 DNA 甲基化是类风湿关节炎遗传风险的中介。
Nat Biotechnol. 2013 Feb;31(2):142-7. doi: 10.1038/nbt.2487. Epub 2013 Jan 20.
6
DNA methylation arrays as surrogate measures of cell mixture distribution.DNA 甲基化芯片作为细胞混合物分布的替代测量指标。
BMC Bioinformatics. 2012 May 8;13:86. doi: 10.1186/1471-2105-13-86.
7
Using control genes to correct for unwanted variation in microarray data.利用对照基因纠正微阵列数据中的非期望变异。
Biostatistics. 2012 Jul;13(3):539-52. doi: 10.1093/biostatistics/kxr034. Epub 2011 Nov 17.
8
Independent surrogate variable analysis to deconvolve confounding factors in large-scale microarray profiling studies.独立的替代变量分析可在大规模微阵列分析研究中去卷积混杂因素。
Bioinformatics. 2011 Jun 1;27(11):1496-505. doi: 10.1093/bioinformatics/btr171. Epub 2011 Apr 6.
9
Capturing heterogeneity in gene expression studies by surrogate variable analysis.通过替代变量分析在基因表达研究中捕捉异质性。
PLoS Genet. 2007 Sep;3(9):1724-35. doi: 10.1371/journal.pgen.0030161. Epub 2007 Aug 1.
Zotero 插件