2015
DOI: 10.1186/s12859-015-0527-y
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Cell-composition effects in the analysis of DNA methylation array data: a mathematical perspective

Abstract: BackgroundThe impact of cell-composition effects in analysis of DNA methylation data is now widely appreciated. With the availability of a reference data set consisting of DNA methylation measurements on isolated cell types, it is possible to impute cell proportions and adjust for them, but there is increasing interest in methods that adjust for cell composition effects when reference sets are incomplete or unavailable.ResultsIn this article we present a theoretical basis for one such method, showing that the … Show more

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Cited by 102 publications
(80 citation statements)
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“…of adjustment for cell composition in placenta/cord blood (24), the influence of maternal genetics on placental gene expression, the potential underrepresentation of differential methylation in CpG islands (25), and the inability to obtain-for ethical reasons-target tissues for the assessment of tissue-specific DNA methylation/expression. The strengths include the strict inclusion criteria (leading to distinct AGA and SGA populations and avoiding perinatal confounders) and the parallel assessments of placenta/cord blood pairs.…”
Section: Discussionmentioning
confidence: 99%
“…of adjustment for cell composition in placenta/cord blood (24), the influence of maternal genetics on placental gene expression, the potential underrepresentation of differential methylation in CpG islands (25), and the inability to obtain-for ethical reasons-target tissues for the assessment of tissue-specific DNA methylation/expression. The strengths include the strict inclusion criteria (leading to distinct AGA and SGA populations and avoiding perinatal confounders) and the parallel assessments of placenta/cord blood pairs.…”
Section: Discussionmentioning
confidence: 99%
“…After filtering, 167,384 probes remained for downstream analysis. The package RefFreeEWAS was utilized to estimate cell proportion 53 , and function lm was used to correct for the cellular heterogeneity.…”
Section: Data Quality Control and Pre-processingmentioning
confidence: 99%
“…The epigenome can be highly variable across different cell types as evident from epigenomewide association studies 42 . These cell-type-specific effects can be useful for the quantification of TILs and has been already harnessed by recent approaches 43 . Although the current availability of the reference methy lation patterns from purified cell types is still limi ted, these methods hold promise for determining TIL composition from bulk tumour tissue.…”
Section: High-dimensional Datamentioning
confidence: 98%