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Cell-type deconvolution in epigenome-wide association studies: a review and recommendations
- Source :
- Epigenomics. 9(5)
- Publication Year :
- 2017
-
Abstract
- A major challenge faced by epigenome-wide association studies (EWAS) is cell-type heterogeneity. As many EWAS have already demonstrated, adjusting for changes in cell-type composition can be critical when analyzing and interpreting findings from such studies. Because of their importance, a great number of different statistical algorithms, which adjust for cell-type composition, have been proposed. Some of the methods are ‘reference based’ in that they require a priori defined reference DNA methylation profiles of cell types that are present in the tissue of interest, while other algorithms are ‘reference free.’ At present, however, it is unclear how best to adjust for cell-type heterogeneity, as this may also largely depend on the type of tissue and phenotype being considered. Here, we provide a critical review of the major existing algorithms for correcting cell-type composition in the context of Illumina Infinium Methylation Beadarrays, with the aim of providing useful recommendations to the EWAS community.
- Subjects :
- 0301 basic medicine
Genetics
Epigenomics
Cancer Research
Genetic Variation
Context (language use)
Epigenome
Computational biology
Biology
DNA Methylation
Epigenesis, Genetic
03 medical and health sciences
030104 developmental biology
Phenotype
DNA methylation
Animals
Humans
Deconvolution
Genetic association
Genome-Wide Association Study
Subjects
Details
- ISSN :
- 1750192X
- Volume :
- 9
- Issue :
- 5
- Database :
- OpenAIRE
- Journal :
- Epigenomics
- Accession number :
- edsair.doi.dedup.....86b39dafe8967d8065cc188ba0e84584