A comparison of reference-based algorithms for correcting cell-type heterogeneity in epigenome-wide association studies
文献类型：期刊论文
| 作者 | Teschendorff,Andrew E.1,2,3; Breeze,Charles E.4; Zheng,Shijie C.1,5; Beck,Stephan4 |
| 刊名 | Bmc bioinformatics
 |
| 出版日期 | 2017-02-13 |
| 卷号 | 18期号:1 |
| 关键词 | Cellular heterogeneity Dna methylation Ewas |
| ISSN号 | 1471-2105 |
| DOI | 10.1186/s12859-017-1511-5 |
| 通讯作者 | Teschendorff,andrew e.(a.teschendorff@ucl.ac.uk) |
| 英文摘要 | Abstractbackgroundintra-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.resultshere 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.conclusionsestimating cell-type fractions and subsequent inference in ewas may benefit from the use of non-constrained reference-based cell-type deconvolution methods. |
| 语种 | 英语 |
| WOS记录号 | BMC:10.1186/S12859-017-1511-5 |
| 出版者 | BioMed Central |
| URI标识 | http://www.irgrid.ac.cn/handle/1471x/2374340 |
| 专题 | 中国科学院大学 |
| 通讯作者 | Teschendorff,Andrew E. |
| 作者单位 | 1.Chinese Academy of Sciences; CAS Key Lab of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute for Biological Sciences 2.University College London; Department of Women’s Cancer 3.University College London; Statistical Cancer Genomics, Paul O’Gorman Building, UCL Cancer Institute 4.University College London; Medical Genomics, Paul O’Gorman Building, UCL Cancer Institute 5.University of Chinese Academy of Sciences |
| 推荐引用方式 GB/T 7714 | Teschendorff,Andrew E.,Breeze,Charles E.,Zheng,Shijie C.,et al. A comparison of reference-based algorithms for correcting cell-type heterogeneity in epigenome-wide association studies[J]. Bmc bioinformatics,2017,18(1). |
| APA | Teschendorff,Andrew E.,Breeze,Charles E.,Zheng,Shijie C.,&Beck,Stephan.(2017).A comparison of reference-based algorithms for correcting cell-type heterogeneity in epigenome-wide association studies.Bmc bioinformatics,18(1). |
| MLA | Teschendorff,Andrew E.,et al."A comparison of reference-based algorithms for correcting cell-type heterogeneity in epigenome-wide association studies".Bmc bioinformatics 18.1(2017). |
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来源：中国科学院大学
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