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论文题目: Cell-type deconvolution in epigenome-wide association studies: a review and recommendations
英文论文题目: Cell-type deconvolution in epigenome-wide association studies: a review and recommendations
第一作者: Teschendorff, AE; Zheng, SC
英文第一作者: Teschendorff, AE; Zheng, SC
联系作者: Teschendorff, AE (reprint author), Chinese Acad Sci, Shanghai Inst Biol Sci, CAS MPG Partner Inst Computat Biol, CAS Key Lab Computat Biol, Shanghai 200031, Peoples R China.
英文联系作者: Teschendorff, AE (reprint author), Chinese Acad Sci, Shanghai Inst Biol Sci, CAS MPG Partner Inst Computat Biol, CAS Key Lab Computat Biol, Shanghai 200031, Peoples R China.
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发表年度: 2017
卷: 9
期: 5
页码: 757-768
摘要: A major challenge faced by epigenome-wide association studies (EWAS) is cell-type heterogeneity. As many EWAS have already demonstrated, adjusting for changes in cell-type composition can be critical when analyzing and interpreting findings from such studies. Because of their importance, a great number of different statistical algorithms, which adjust for cell-type composition, have been proposed. Some of the methods are 'reference based' in that they require a priori defined reference DNA methylation profiles of cell types that are present in the tissue of interest, while other algorithms are reference free.' At present, however, it is unclear how best to adjust for cell-type heterogeneity, as this may also largely depend on the type of tissue and phenotype being considered. Here, we provide a critical review of the major existing algorithms for correcting cell-type composition in the context of Illumina Infinium Methylation Beadarrays, with the aim of providing useful recommendations to the EWAS community.
英文摘要: A major challenge faced by epigenome-wide association studies (EWAS) is cell-type heterogeneity. As many EWAS have already demonstrated, adjusting for changes in cell-type composition can be critical when analyzing and interpreting findings from such studies. Because of their importance, a great number of different statistical algorithms, which adjust for cell-type composition, have been proposed. Some of the methods are 'reference based' in that they require a priori defined reference DNA methylation profiles of cell types that are present in the tissue of interest, while other algorithms are reference free.' At present, however, it is unclear how best to adjust for cell-type heterogeneity, as this may also largely depend on the type of tissue and phenotype being considered. Here, we provide a critical review of the major existing algorithms for correcting cell-type composition in the context of Illumina Infinium Methylation Beadarrays, with the aim of providing useful recommendations to the EWAS community.
刊物名称: EPIGENOMICS
英文刊物名称: EPIGENOMICS
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学科: Genetics & Heredity
英文学科: Genetics & Heredity
影响因子: 4.541
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论文类别: Article
英文论文类别: Article
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