<HashMap><database>biostudies-other</database><scores/><additional><omics_type>Unknown</omics_type><submitter/><species>Mus musculus (mouse)</species><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-BSST1928</full_dataset_link><repository>biostudies-other</repository></additional><is_claimable>false</is_claimable><name>Benchmarking scRNA-seq copy number variation callers</name><description>Copy number variations (CNVs), the gain or loss of genomic regions, are associated with different diseases and cancer types, where they are related to tumor progression and treatment outcome. Single cell technologies offer new possibilities to measure CNVs in individual cells, allowing to assess population heterogeneity and to delineate subclonal structures. Single cell whole-genome sequencing is considered the gold-standard for the quantification of CNVs in single cells. However, the majority of existing single cell datasets interrogate gene expression, using scRNA-seq. Consequently, several computational approaches have been developed to identify CNVs from that data modality. Nevertheless, an independent benchmarking of these methods is lacking. We used 15 21 scRNA-seq datasets and evalu</description><dates><release>2025-06-14T00:00:00Z</release><modification>2025-07-18T12:45:50.79Z</modification><creation>2025-03-21T09:54:46.172Z</creation></dates><accession>S-BSST1928</accession><cross_references/></HashMap>