An optimized library for reference-based deconvolution of whole-blood biospecimens assayed using the Illumina HumanMethylationEPIC BedArray

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Authors Lucas A. Salas, Devin C. Koestler, Rondi A. Butler, Helen M.Hansen, John K. Wiencke, Karl T. Kelsey, Brock C. Christensen
Journal/Conference Name Genome Biology
Paper Category , ,
Paper 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.
Date of publication 2018
Code Programming Language R
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