Decamps, ClémentineArnaud, AlexisPetitprez, FlorentAyadi, MiraBaurès, AuréliaArmenoult, LucileEscalera Guerrero, SergioGuyon, IsabelleNicolle, RémyTomasini, RichardReyniès, Aurélien deCros, JérômeBlum, YunaRichard, Magali2022-03-142022-03-142021-10-021471-2105https://hdl.handle.net/2445/184089Quantifcation of tumor heterogeneity is essential to better understand cancer progression and to adapt therapeutic treatments to patient specifcities. Bioinformatic tools to assess the diferent 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.application/pdfengcc-by (c) Decamps, Clémentine et al., 2021https://creativecommons.org/licenses/by/4.0/CàncerClassificació de tumorsAlgorismes computacionalsCancerTumors classificationComputer algorithmsinfo:eu-repo/semantics/article7145442022-03-14info:eu-repo/semantics/openAccess