MeDeCom: discovery and quantification of latent components of heterogeneous methylomes.
It is important for large-scale epigenomic studies to determine and explore the nature of hidden confounding variation, most importantly cell composition. We developed MeDeCom as a novel reference-free computational framework that allows the decomposition of complex DNA methylomes into latent methylation components and their proportions in each sample. MeDeCom is based on constrained non-negative matrix factorization with a new biologically motivated regularization function. It accurately recovers cell-type-specific latent methylation components and their proportions. MeDeCom is a new unsupervised tool for the exploratory study of the major sources of methylation variation, which should lead to a deeper understanding and better biological interpretation.
Department of EpiGenetics, Saarland University, Campus A2.4, Saarbrücken, 66123, Germany.|Present address: Division of Cancer Epigenetics, German Cancer Research Center, Im Neuenheimerfeld 280, Heidelberg, 69120, Germany.
Pavlo
P
Lutsik
Machine Learning Group, Saarland University, Campus E1.1, Saarbrücken66123, Germany.|Department of Statistics and Biostatistics, Department of Computer Science, Rutgers University, 110 Frelinghuysen Rd, Piscataway, 08854, NJ, USA.|Present address: Department of Statistics, Volgenau School of Engineering, George Mason University, 4400 University Drive, MS 4A7 Fairfax, Fairfax, VA 22030-4444, USA.
Martin
M
Slawski
Department of EpiGenetics, Saarland University, Campus A2.4, Saarbrücken, 66123, Germany.
Gilles
G
Gasparoni
Machine Learning Group, Saarland University, Campus E1.1, Saarbrücken66123, Germany.
Nikita
N
Vedeneev
Machine Learning Group, Saarland University, Campus E1.1, Saarbrücken66123, Germany. hein@cs.uni-saarland.de.
Matthias
M
Hein
Department of EpiGenetics, Saarland University, Campus A2.4, Saarbrücken, 66123, Germany. j.walter@mx.uni-saarland.de.
Jörn
http://orcid.org/0000-0003-0563-7417
J
Walter
D001921:Brain / Q000378:metabolism; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D019175:DNA Methylation; D044127:Epigenesis, Genetic; D057890:Epigenomics / Q000379:methods*; D020869:Gene Expression Profiling / Q000379:methods; D056726:Genetic Association Studies; D006801:Humans; D010641:Phenotype; D012984:Software
Cell heterogeneity; DNA methylation; DNA methylome; Deconvolution; Epigenetics; Matrix factorization