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Updated: Jan 18, 2026

Immunostaining for DNA Modifications: Computational Analysis of Confocal Images
Published on: September 7, 2017
Unifying DNA methylation-based in silico cell-type deconvolution with deconvMe
Alexander Dietrich1, Lina-Liv Willruth1, Korbinian Pürckhauer2
1Data Science in Systems Biology, TUM School of Life Sciences, Technical University of Munich, Freising, 85354, Germany.
Summary:
Cell-type deconvolution is widely applied to gene expression and DNA methylation data, but access to methods for the latter remains limited. We introduce deconvMe, a new R package that simplifies access to DNA methylation-based deconvolution methods predominantly for blood data, and we additionally compare their estimates to those from gene expression and experimental ground truth data using a unique matched blood dataset.
Availability And Implementation:
DevonMe is available at https://github.com/omnideconv/deconvMe, the processed blood data is available at https://figshare.com/articles/dataset/methyldeconv_data/28563854/3.

