PT Journal
AU Clementine Decamps
   Alexis Arnaud
   Florent Petitprez
   Mira Ayadi
   Aurelia Baures
   Lucile Armenoult
   Sergio Escalera
   Isabelle Guyon
   Remy Nicolle
   Richard Tomasini
   Aurelien de Reynies
   Jerome Cros
   Yuna Blum
   Magali Richard
TI DECONbench: a benchmarking platform dedicated to deconvolution methods for tumor heterogeneity quantification
SO BMC Bioinformatics
PY 2021
BP 473
VL 22
AB Quantification of tumor heterogeneity is essential to better understand cancer progression and to adapt therapeutic treatments to patient specificities. Bioinformatic tools to assess the different cell populations from single-omic datasets as bulk transcriptome or methylome samples have been recently developed, including reference-based and reference-free methods. Improved methods using multi-omic datasets are yet to be developed in the future and the community would need systematic tools to perform a comparative evaluation of these algorithms on controlled data.
ER