论文库首页  论文库
 
论文编号:
论文题目: A comparison of reference-based algorithms for correcting cell-type heterogeneity in Epigenome-Wide Association Studies
英文论文题目: A comparison of reference-based algorithms for correcting cell-type heterogeneity in Epigenome-Wide Association Studies
第一作者: Teschendorff, AE; Breeze, CE; Zheng, SJC; Beck, S
英文第一作者: Teschendorff, AE; Breeze, CE; Zheng, SJC; Beck, S
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.
外单位作者单位:
英文外单位作者单位:
发表年度: 2017
卷: 18
期:
页码: 105
摘要: Background: Intra-sample cellular heterogeneity presents numerous challenges to the identification of biomarkers in large Epigenome-Wide Association Studies (EWAS). While a number of reference-based deconvolution algorithms have emerged, their potential remains underexplored and a comparative evaluation of these algorithms beyond tissues such as blood is still lacking. Results: Here we present a novel framework for reference-based inference, which leverages cell-type specific DNAse Hypersensitive Site (DHS) information from the NIH Epigenomics Roadmap to construct an improved reference DNA methylation database. We show that this leads to a marginal but statistically significant improvement of cell-count estimates in whole blood as well as in mixtures involving epithelial cell-types. Using this framework we compare a widely used state-of-the-art reference-based algorithm (called constrained projection) to two non-constrained approaches including CIBERSORT and a method based on robust partial correlations. We conclude that the widely-used constrained projection technique may not always be optimal. Instead, we find that the method based on robust partial correlations is generally more robust across a range of different tissue types and for realistic noise levels. We call the combined algorithm which uses DHS data and robust partial correlations for inference, EpiDISH (Epigenetic Dissection of Intra-Sample Heterogeneity). Finally, we demonstrate the added value of EpiDISH in an EWAS of smoking. Conclusions: Estimating cell-type fractions and subsequent inference in EWAS may benefit from the use of nonconstrained reference-based cell-type deconvolution methods.
英文摘要: Background: Intra-sample cellular heterogeneity presents numerous challenges to the identification of biomarkers in large Epigenome-Wide Association Studies (EWAS). While a number of reference-based deconvolution algorithms have emerged, their potential remains underexplored and a comparative evaluation of these algorithms beyond tissues such as blood is still lacking. Results: Here we present a novel framework for reference-based inference, which leverages cell-type specific DNAse Hypersensitive Site (DHS) information from the NIH Epigenomics Roadmap to construct an improved reference DNA methylation database. We show that this leads to a marginal but statistically significant improvement of cell-count estimates in whole blood as well as in mixtures involving epithelial cell-types. Using this framework we compare a widely used state-of-the-art reference-based algorithm (called constrained projection) to two non-constrained approaches including CIBERSORT and a method based on robust partial correlations. We conclude that the widely-used constrained projection technique may not always be optimal. Instead, we find that the method based on robust partial correlations is generally more robust across a range of different tissue types and for realistic noise levels. We call the combined algorithm which uses DHS data and robust partial correlations for inference, EpiDISH (Epigenetic Dissection of Intra-Sample Heterogeneity). Finally, we demonstrate the added value of EpiDISH in an EWAS of smoking. Conclusions: Estimating cell-type fractions and subsequent inference in EWAS may benefit from the use of nonconstrained reference-based cell-type deconvolution methods.
刊物名称: BMC BIOINFORMATICS
英文刊物名称: BMC BIOINFORMATICS
论文全文:
英文论文全文:
全文链接:
其它备注:
英文其它备注:
学科: Biochemical Research Methods; Biotechnology & Applied Microbiology; Mathematical & Computational Biology
英文学科: Biochemical Research Methods; Biotechnology & Applied Microbiology; Mathematical & Computational Biology
影响因子: 2.448
第一作者所在部门:
英文第一作者所在部门:
论文出处:
英文论文出处:
论文类别: Article
英文论文类别: Article
参与作者:
英文参与作者:
 
2014 中国科学院上海生命科学研究院 版权所有