huseyincavus/flexynesis-datasets

Flexynesis Benchmark Datasets

Dataset key	Biology	Modalities	Samples	Task types available
dataset1	Cancer drug response (CCLE/GDSC cell lines)	gex, cnv	~950 / 240	Regression (drug IC50 per compound)
dataset2	Microsatellite instability (MSI)	gex, meth	~380 / 95	Binary classification (MSI-H vs MSS)
lgggbm_tcga_pub_processed	Brain tumours: LGG + GBM (TCGA)	mut, cna	556 / 238	Classification, survival, regression
brca_metabric	Breast cancer (METABRIC)	gex, cna	~1390 / 595	Classification, survival, regression
singlecell_bonemarrow	Bone marrow single-cell RNA	gex	~7500 / 2500	Classification, unsupervised

Note on single-cell data: flexynesis was designed for bulk multi-omics data (patient cohorts, cell lines) — not single-cell RNA-seq. It has no built-in handling for the sparsity, scale, or batch structure typical of scRNA-seq. The singlecell_bonemarrow dataset is included as a benchmark curiosity and works well for supervised cell type classification (where cell type labels are available), but flexynesis is not the right tool for unsupervised single-cell analysis, trajectory inference, or integration of large scRNA-seq atlases. For those tasks, use Scanpy/Seurat/scVI instead. If the user's question is specifically about supervised classification of single-cell data with known labels, it is worth trying.

All datasets hosted at https://bimsbstatic.mdc-berlin.de/akalin/buyar/flexynesis-benchmark-datasets/

Reference: Uyar et al., Nature Communications 2025 — https://doi.org/10.1038/s41467-025-63688-5