Year: 2024
Type: article
Abstract: 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.
Source: Bioinformatics Advances
Institutions: Technical University of Munich, Medizinische Hochschule Hannover, Helmholtz Centre for Infection Research, Centre for Individualised Infection Medicine, Center for Experimental and Clinical Infection Research, Leibniz University Hannover, CAIMed - Niedersächsisches Zentrum für KI und Kausale Methoden in der Medizin, German Center for Infection Research
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,917
OpenAlex ID: W4414084594