Exploring the Signature Matrix Creation Process for Cell Type Deconvolution Using Proteomics Data
Cell type deconvolution - the computational estimation of cellular composition in bulk tissue samples - is a valuable tool in cancer research for understanding immune infiltration and tissue heterogeneity. Most deconvolution algorithms infer the composition of cell types in bulk samples by modeling the observed expression data as a linear combination of reference expression profiles from each cell
