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BioinformaticsNAR Genomics and Bioinformatics
Peer-reviewed journal article

Cell type deconvolution of methylated cell-free DNA atthe resolution of individual reads

Pia KeukeleireiD, Stavros MakrodimitrisiD, Marcel J. T. ReindersiD

Abstract

Cell-free DNA (cfDNA) are DNA fragments originating from dying cells that are detectable in bodily fluids, such as the plasma. Accelerated cell death, for example caused by disease, induces an elevated concentration of cfDNA. As a result, determining the cell type origins of cfDNA molecules can provide information about an individuals health. In this work, we aim to increase the sensitivity of methylation-based cell type deconvolution by adapting an existing method, CelFiE, which uses the methylation beta values of individual CpG sites to estimate cell type proportions. Our new method, CelFEER, instead differentiates cell types by the average methylation values within individual reads. We additionally improved the originally reported performance of CelFiE by using a new approach for finding marker regions that are differentially methylated between cell types. This approach compares the methylation values over 500 bp regions instead of at single CpG sites and solely takes hypomethylated regions into account. We show that CelFEER estimates cell type proportions with a higher correlation (r2 = 0.94{+/-}0.04) than CelFiE (r2 = 0.86{+/-} 0.09) on simulated mixtures of cell types. Moreover, we found that it can find a significant difference between the skeletal muscle cfDNA fraction in four ALS patients and four healthy controls.

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