DECONbench: a benchmarking platform dedicated to deconvolution methods for tumor heterogeneity quantification

dc.contributor.authorDecamps, Clémentine
dc.contributor.authorArnaud, Alexis
dc.contributor.authorPetitprez, Florent
dc.contributor.authorAyadi, Mira
dc.contributor.authorBaurès, Aurélia
dc.contributor.authorArmenoult, Lucile
dc.contributor.authorEscalera Guerrero, Sergio
dc.contributor.authorGuyon, Isabelle
dc.contributor.authorNicolle, Rémy
dc.contributor.authorTomasini, Richard
dc.contributor.authorReyniès, Aurélien de
dc.contributor.authorCros, Jérôme
dc.contributor.authorBlum, Yuna
dc.contributor.authorRichard, Magali
dc.date.accessioned2022-03-14T09:36:21Z
dc.date.available2022-03-14T09:36:21Z
dc.date.issued2021-10-02
dc.date.updated2022-03-14T09:36:22Z
dc.description.abstractQuantifcation 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.
dc.format.mimetypeapplication/pdf
dc.identifier.idgrec714544
dc.identifier.issn1471-2105
dc.identifier.urihttps://hdl.handle.net/2445/184089
dc.language.isoeng
dc.publisherBioMed Central
dc.relation.isformatofReproducció del document publicat a: https://doi.org/10.1186/s12859-021-04381-4
dc.relation.ispartofBMC Bioinformatics, 2021, vol. 2021, num. 22
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/826121/EU//iPC
dc.relation.urihttps://doi.org/10.1186/s12859-021-04381-4
dc.rightscc-by (c) Decamps, Clémentine et al., 2021
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.sourceArticles publicats en revistes (Matemàtiques i Informàtica)
dc.subject.classificationCàncer
dc.subject.classificationClassificació de tumors
dc.subject.classificationAlgorismes computacionals
dc.subject.otherCancer
dc.subject.otherTumors classification
dc.subject.otherComputer algorithms
dc.titleDECONbench: a benchmarking platform dedicated to deconvolution methods for tumor heterogeneity quantification
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion

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