Title |
An optimized library for reference-based deconvolution of whole-blood biospecimens assayed using the Illumina HumanMethylationEPIC BeadArray
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Published in |
Genome Biology, May 2018
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DOI | 10.1186/s13059-018-1448-7 |
Pubmed ID | |
Authors |
Lucas A. Salas, Devin C. Koestler, Rondi A. Butler, Helen M. Hansen, John K. Wiencke, Karl T. Kelsey, Brock C. Christensen |
Abstract |
Genome-wide methylation arrays are powerful tools for assessing cell composition of complex mixtures. We compare three approaches to select reference libraries for deconvoluting neutrophil, monocyte, B-lymphocyte, natural killer, and CD4+ and CD8+ T-cell fractions based on blood-derived DNA methylation signatures assayed using the Illumina HumanMethylationEPIC array. The IDOL algorithm identifies a library of 450 CpGs, resulting in an average R2 = 99.2 across cell types when applied to EPIC methylation data collected on artificial mixtures constructed from the above cell types. Of the 450 CpGs, 69% are unique to EPIC. This library has the potential to reduce unintended technical differences across array platforms. |
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Geographical breakdown
Country | Count | As % |
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United States | 7 | 47% |
Germany | 2 | 13% |
Canada | 1 | 7% |
Netherlands | 1 | 7% |
Switzerland | 1 | 7% |
United Kingdom | 1 | 7% |
Unknown | 2 | 13% |
Demographic breakdown
Type | Count | As % |
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Scientists | 10 | 67% |
Members of the public | 4 | 27% |
Science communicators (journalists, bloggers, editors) | 1 | 7% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 147 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 38 | 26% |
Student > Ph. D. Student | 27 | 18% |
Student > Master | 12 | 8% |
Student > Bachelor | 8 | 5% |
Other | 8 | 5% |
Other | 18 | 12% |
Unknown | 36 | 24% |
Readers by discipline | Count | As % |
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Biochemistry, Genetics and Molecular Biology | 32 | 22% |
Agricultural and Biological Sciences | 20 | 14% |
Medicine and Dentistry | 14 | 10% |
Business, Management and Accounting | 4 | 3% |
Computer Science | 4 | 3% |
Other | 27 | 18% |
Unknown | 46 | 31% |