Background: Recent interest in reference-free deconvolution of DNA methylation data has led to several supervised methods, but these methods do not easily permit the interpretation of underlying cell types.
Results: We propose a simple method for reference-free deconvolution that provides both proportions of putative cell types defined by their underlying...
Background: Recent interest in reference-free deconvolution of DNA methylation data has led to several supervised methods, but these methods do not easily permit the interpretation of underlying cell types.
Results: We propose a simple method for reference-free deconvolution that provides both proportions of putative cell types defined by their underlying...
Background: Recent interest in reference-free deconvolution of DNA methylation data has led to several supervised methods, but these methods do not easily permit the interpretation of underlying cell types.
Results: We propose a simple method for reference-free deconvolution that provides both proportions of putative cell types defined by their underlying...
Background: Recent interest in reference-free deconvolution of DNA methylation data has led to several supervised methods, but these methods do not easily permit the interpretation of underlying cell types.
Results: We propose a simple method for reference-free deconvolution that provides both proportions of putative cell types defined by their underlying...
BACKGROUND: The 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...
BACKGROUND: The 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...
BACKGROUND: Cell lineage-specific DNA methylation patterns distinguish normal human leukocyte subsets and can
be used to detect and quantify these subsets in peripheral blood. We have developed an approach that uses DNA
methylation to simultaneously quantify multiple leukocyte subsets, enabling investigation of immune modulations
in virtually any blood sample including...
BACKGROUND: Cell lineage-specific DNA methylation patterns distinguish normal human leukocyte subsets and can
be used to detect and quantify these subsets in peripheral blood. We have developed an approach that uses DNA
methylation to simultaneously quantify multiple leukocyte subsets, enabling investigation of immune modulations
in virtually any blood sample including...
Background: Recent interest in reference-free deconvolution of DNA methylation data has led to several supervised methods, but these methods do not easily permit the interpretation of underlying cell types.
Results: We propose a simple method for reference-free deconvolution that provides both proportions of putative cell types defined by their underlying...
Understanding the precise role of the immune system in cancer has been hindered by the complexity of the immune response and challenges in measuring immune cell types in health and disease in the context of large epidemiologic studies. In this review, we present the rationale to study immunity in cancer...