lamindb.core.datasets¶

Test datasets.

Small in-memory datasets.

small_dataset1(format[, with_typo])

Create a mini anndata with cell_type, disease and tissue.

Files.

`file_fcs`()	Example FCS artifact.
`file_fcs_alpert19`([populate_registries])	FCS file from Alpert19.
`file_tsv_rnaseq_nfcore_salmon_merged_gene_counts`([...])	Gene counts table from nf-core RNA-seq pipeline.
`file_jpg_paradisi05`()	Return jpg file example.
`file_tiff_suo22`()	Image file from Suo22.
`file_fastq`([in_storage_root])	Mini mock fastq artifact.
`file_bam`([in_storage_root])	Mini mock bam artifact.
`file_mini_csv`([in_storage_root])	Mini csv artifact.

Directories.

`dir_scrnaseq_cellranger`(sample_name[, ...])	Generate mock cell ranger outputs.
`dir_iris_images`()	Directory with 3 studies of the Iris flower: 405 images & metadata.

Dataframe, AnnData, MuData.

`df_iris`()	The iris collection as in sklearn.
`df_iris_in_meter`()	The iris collection with lengths in meter.
`df_iris_in_meter_study1`()	The iris collection with lengths in meter.
`df_iris_in_meter_study2`()	The iris collection with lengths in meter.
`anndata_mouse_sc_lymph_node`([...])	Mouse lymph node scRNA-seq collection from EBI.
`anndata_human_immune_cells`([populate_registries])	Cross-tissue immune cell analysis reveals tissue-specific features in humans.
`anndata_pbmc68k_reduced`()	Modified from scanpy.collections.pbmc68k_reduced().
`anndata_file_pbmc68k_test`()	Modified from scanpy.collections.pbmc68k_reduced().
`anndata_pbmc3k_processed`()	Modified from scanpy.pbmc3k_processed().
`anndata_with_obs`()	Create a mini anndata with cell_type, disease and tissue.
`anndata_suo22_Visium10X`()	AnnData from Suo22 generated by 10x Visium.
`mudata_papalexi21_subset`()	A subsetted mudata from papalexi21.
`schmidt22_crispra_gws_IFNG`([basedir])	CRISPRi screen collection of Schmidt22.
`schmidt22_perturbseq`([basedir])	Perturb-seq collection of Schmidt22.

Other.

A fake collection of study titles.