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MethylCC: technology-independent estimation of cell type composition using differentially methylated regions.


ABSTRACT: A major challenge in the analysis of DNA methylation (DNAm) data is variability introduced from intra-sample cellular heterogeneity, such as whole blood which is a convolution of DNAm profiles across a unique cell type. When this source of variability is confounded with an outcome of interest, if unaccounted for, false positives ensue. Current methods to estimate the cell type proportions in whole blood DNAm samples are only appropriate for one technology and lead to technology-specific biases if applied to data generated from other technologies. Here, we propose the technology-independent alternative: methylCC, which is available at https://github.com/stephaniehicks/methylCC.

SUBMITTER: Hicks SC 

PROVIDER: S-EPMC6883691 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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methylCC: technology-independent estimation of cell type composition using differentially methylated regions.

Hicks Stephanie C SC   Irizarry Rafael A RA  

Genome biology 20191129 1


A major challenge in the analysis of DNA methylation (DNAm) data is variability introduced from intra-sample cellular heterogeneity, such as whole blood which is a convolution of DNAm profiles across a unique cell type. When this source of variability is confounded with an outcome of interest, if unaccounted for, false positives ensue. Current methods to estimate the cell type proportions in whole blood DNAm samples are only appropriate for one technology and lead to technology-specific biases i  ...[more]

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