Nature Communications (Mar 2022)

Comprehensive evaluation of deconvolution methods for human brain gene expression

  • Gavin J. Sutton,
  • Daniel Poppe,
  • Rebecca K. Simmons,
  • Kieran Walsh,
  • Urwah Nawaz,
  • Ryan Lister,
  • Johann A. Gagnon-Bartsch,
  • Irina Voineagu

DOI
https://doi.org/10.1038/s41467-022-28655-4
Journal volume & issue
Vol. 13, no. 1
pp. 1 – 18

Abstract

Read online

Transcriptome deconvolution aims to estimate cellular composition based on gene expression data. Here the authors evaluate deconvolution methods for human brain transcriptome and conclude that partial deconvolution algorithms work best, but that appropriate cell-type signatures are also important.