Using epigenetic data to estimate immune composition in admixed samples

Ankur Chakravarthy; Daniel D De Carvalho

doi:10.1016/bs.mie.2019.07.004

Using epigenetic data to estimate immune composition in admixed samples

Methods Enzymol. 2020:636:77-92. doi: 10.1016/bs.mie.2019.07.004. Epub 2019 Aug 1.

Authors

Ankur Chakravarthy¹, Daniel D De Carvalho²

Affiliations

¹ UHN Princess Margaret Cancer Centre, Toronto, ON, Canada. Electronic address: ankur.chakravarthy.10@ucl.ac.uk.
² UHN Princess Margaret Cancer Centre, Toronto, ON, Canada; Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada. Electronic address: daniel.decarvalho@uhnresearch.ca.

PMID: 32178828
DOI: 10.1016/bs.mie.2019.07.004

Abstract

Variation in cell-type decomposition can be of interest to changes in biology by themselves, or a confounder in comparing admixed samples with different phenotypes. Here, I present and review various algorithms that may be used for purposes of deconvolving epigenomic data from admixed samples to yield estimates that may be factored into downstream analyses. More specifically, I present a protocol based on an adaptation of the CIBERSORT algorithm, previously developed for gene-expression, to methylation data.

Keywords: DNA methylation; Deconvolution; Epigenetics; Immune composition.

MeSH terms

Algorithms
DNA Methylation*
Epigenesis, Genetic
Epigenomics*
Gene Expression