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Cell composition correction software tools | DNA methylation microarray data analysis

Cell composition correction software tools | DNA methylation microarray data analysis

Whole blood is frequently utilized in genome-wide association studies of DNA methylation patterns in relation to environmental exposures or clinical outcomes. However, for DNA methylation assessed from whole blood, the association between DNA methylation and an exposure of interest could be confounded by cellular heterogeneity (Adalsteinsson et al., 2012; Talens et al., 2010). In larger epidemiological studies, it is not feasible to isolate and profile every individual cell subset. Thus, several algorithms have been developed to measure and adjust for cellular heterogeneity in whole blood.

References:
(Adalsteinsson et al., 2012) Heterogeneity in white blood cells has potential to confound DNA methylation measurements. PLoS One.
(Talens et al., 2010) Variation, patterns, and temporal stability of DNA methylation: considerations for epigenetic epidemiology. FASEB J.

Source text:
(Kaushal et al., 2017) Comparison of different cell type correction methods for genome-scale epigenetics studies. BMC Bioinformatics.

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