Nature Communications (Nov 2020)

Benchmarking of cell type deconvolution pipelines for transcriptomics data

  • Francisco Avila Cobos,
  • José Alquicira-Hernandez,
  • Joseph E. Powell,
  • Pieter Mestdagh,
  • Katleen De Preter

DOI
https://doi.org/10.1038/s41467-020-19015-1
Journal volume & issue
Vol. 11, no. 1
pp. 1 – 14

Abstract

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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.