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Comprehensive benchmarking of computational deconvolution of transcriptomics data
View ORCID ProfileFrancisco Avila Cobos, View ORCID ProfileJosé Alquicira-Hernandez, View ORCID ProfileJoseph Powell, View ORCID ProfilePieter Mestdagh, View ORCID ProfileKatleen De Preter
doi: https://doi.org/10.1101/2020.01.10.897116
Francisco Avila Cobos
1Center for Medical Genetics Ghent, Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
2Cancer Research Institute Ghent (CRIG), Ghent, Belgium
3Garvan Weizmann Centre for Cellular Genomics, Garvan Institute of Medical Research, Sydney, Australia
José Alquicira-Hernandez
3Garvan Weizmann Centre for Cellular Genomics, Garvan Institute of Medical Research, Sydney, Australia
4Institute for Molecular Bioscience, University of Queensland, Brisbane, Australia
Joseph Powell
3Garvan Weizmann Centre for Cellular Genomics, Garvan Institute of Medical Research, Sydney, Australia
4Institute for Molecular Bioscience, University of Queensland, Brisbane, Australia
Pieter Mestdagh
1Center for Medical Genetics Ghent, Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
2Cancer Research Institute Ghent (CRIG), Ghent, Belgium
Katleen De Preter
1Center for Medical Genetics Ghent, Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
2Cancer Research Institute Ghent (CRIG), Ghent, Belgium
Posted January 10, 2020.
Comprehensive benchmarking of computational deconvolution of transcriptomics data
Francisco Avila Cobos, José Alquicira-Hernandez, Joseph Powell, Pieter Mestdagh, Katleen De Preter
bioRxiv 2020.01.10.897116; doi: https://doi.org/10.1101/2020.01.10.897116
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