Calculating detection limits and uncertainty of reference-based deconvolution of whole-blood DNA methylation data

Author:

Bell-Glenn Shelby1,Salas Lucas A2,Molinaro Annette M3,Butler Rondi A4,Christensen Brock C256,Kelsey Karl T4,Wiencke John K37,Koestler Devin C1ORCID

Affiliation:

1. Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS 66160, USA

2. Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Hanover, NH 03756, USA

3. Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA

4. Departments of Epidemiology & Pathology & Laboratory Medicine, Brown University, Providence, RI 02912, USA

5. Department of Molecular & Systems Biology, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03756, USA

6. Department of Community & Family Medicine, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03756, USA

7. Institute for Human Genetics, University of California San Francisco, San Francisco, CA 94143, USA

Abstract

DNA methylation (DNAm)-based cell mixture deconvolution (CMD) has become a quintessential part of epigenome-wide association studies where DNAm is profiled in heterogeneous tissue types. Despite being introduced over a decade ago, detection limits, which represent the smallest fraction of a cell type in a mixed biospecimen that can be reliably detected, have yet to be determined in the context of DNAm-based CMD. Moreover, there has been little attention given to approaches for quantifying the uncertainty associated with DNAm-based CMD. Here, analytical frameworks for determining both cell-specific limits of detection and quantification of uncertainty associated with DNAm-based CMD are described. This work may contribute to improved rigor, reproducibility and replicability of epigenome-wide association studies involving CMD.

Funder

National Cancer Institute

National Institute of General Medical Sciences

Publisher

Future Medicine Ltd

Subject

Cancer Research,Genetics

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