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Accession: PRJNA1041875 ID: 1041875

Modeling the next-generation of rhabdomyosarcoma organoids to predict effective drug combinations

This SuperSeries is composed of the SubSeries listed below. Overall design: Refer to individual Series
AccessionPRJNA1041875; GEO: GSE248183
TypeUmbrella project
PublicationsSavary C et al., "Fusion-negative rhabdomyosarcoma 3D organoids to predict effective drug combinations: A proof-of-concept on cell death inducers.", Cell Rep Med, 2023 Dec 19;4(12):101339
SubmissionRegistration date: 17-Nov-2023
Cancer Research Center of Lyon
RelevanceSuperseries
Project Data:
Resource NameNumber
of Links
Sequence data
SRA Experiments46
Publications
PubMed1
PMC1
Other datasets
BioSample46
GEO DataSets5
GEO Data Details
ParameterValue
Data volume, Spots19710375
Data volume, Processed Mbytes642
Data volume, Supplementary Mbytes573
SRA Data Details
ParameterValue
Data volume, Gbases359
Data volume, Tbytes0.11
Modeling the next-generation of rhabdomyosarcoma organoids to predict effective drug combinations encompasses the following 4 sub-projects:
Project TypeNumber of Projects
Epigenomics1
BioProject
accession
OrganismTitle
PRJNA1041882Homo sapiensModeling the next-generation of rhabdomyosarcoma organoids to predict effective drug combinations [methylation] (Cancer Research Center of...)
Other1
BioProject
accession
OrganismTitle
PRJNA1041881Homo sapiensModeling the next-generation of rhabdomyosarcoma organoids to predict effective drug combinations [Exome panel] (Cancer Research Center of...)
Transcriptome or Gene expression2
BioProject
accession
OrganismTitle
PRJNA1041880Homo sapiensModeling the next-generation of rhabdomyosarcoma organoids to predict effective drug combinations [RNAseq] (Cancer Research Center of...)
PRJNA1041883Homo sapiensModeling the next-generation of rhabdomyosarcoma organoids to predict effective drug combinations [scRNAseq] (Cancer Research Center of...)

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