Benchmarking of cell type deconvolution pipelines for transcriptomics data - Francisco Avila Cobos; José Alquicira-Hernandez; Joseph E. Powell; Pieter Mestdagh; Katleen De Preter (Nature Communications, 2020)
Inferring cell type proportions from transcriptomics data is affected by data transformation, normalization, choice of method and the markers used. Here, the authors use single-cell RNAseq datasets to evaluate the impact of these factors and propose guidelines to maximise deconvolution performance.