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Updated: Jun 21, 2025
Immunostaining for DNA Modifications: Computational Analysis of Confocal Images
Published on: September 7, 2017
Transcriptome- and DNA methylation-based cell-type deconvolutions produce similar estimates of differential gene
Emily R Hannon1,2, Carmen J Marsit3, Arlene E Dent4,5
1Center for Global Health and Diseases, Case Western Reserve University, 10900 Euclid Avenue LC:4983, Cleveland, OH, 44106, USA. erh90@case.edu.
Background:
Changing cell-type proportions can confound studies of differential gene expression or DNA methylation (DNAm) from peripheral blood mononuclear cells (PBMCs). We examined how cell-type proportions derived from the transcriptome versus the methylome (DNAm) influence estimates of differentially expressed genes (DEGs) and differentially methylated positions (DMPs).
Methods:
Transcriptome and DNAm data were obtained from PBMC RNA and DNA of Kenyan children (n = 8) before, during, and 6 weeks following uncomplicated malaria. DEGs and DMPs between time points were detected using cell-type adjusted modeling with Cibersortx or IDOL, respectively.
Results:
Most major cell types and principal components had moderate to high correlation between the two deconvolution methods (r = 0.60-0.96). Estimates of cell-type proportions and DEGs or DMPs were largely unaffected by the method, with the greatest discrepancy in the estimation of neutrophils.
Conclusion:
Variation in cell-type proportions is captured similarly by both transcriptomic and methylome deconvolution methods for most major cell types.
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