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MeDeCom: discovery and quantification of latent components of heterogeneous methylomes.

Pavlo LutsikMartin SlawskiGilles GasparoniNikita VedeneevMatthias HeinJörn Walter
Published in: Genome biology (2017)
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.
Keyphrases
  • genome wide
  • dna methylation
  • machine learning
  • cell therapy
  • circulating tumor
  • high throughput
  • cell free
  • single molecule
  • stem cells
  • gene expression
  • case control
  • mesenchymal stem cells