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

# metadata.dc.description.abstract[].value
Quantifcation 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.

# metadata.dc.relation.ispartof[].value
BMC Bioinformatics, 2021, vol. 2021, num. 22

# metadata.dc.rights[].value
cc-by (c) Decamps, Clémentine et al., 2021

# metadata.dc.source[].value
Articles publicats en revistes (Matemàtiques i Informàtica)

# metadata.dc.title[].value
DECONbench: a benchmarking platform dedicated to deconvolution methods for tumor heterogeneity quantification