Cite this repository:
Debabrata Acharya. (2020, July 28). kalyaniuniversity/scRNA-seq-datasets: Publicly available Single-Cell RNA Sequencing Datasets (Version 0.1). Zenodo. http://doi.org/10.5281/zenodo.3964240
A list of publicly available Single Cell RNA Sequencing datasets with proper attribution and associated toolkits.
Please note that even though this repository is free to use and modify under MIT License, but the individual datasets referenced here may be conducted under their own licencing terms.
If we are keeping a copy of the dataset with this repository, it shall be available in the datasets folder within the named repository. Please check the reference table below to find whether we keep a copy of the dataset under the Dataset tab.
If we have written a toolset for a certain dataset, it shall be available under the toolkit folder within the named repository. Please check the reference table below to find whether a certain dataset has any associated toolset under the Tools tab. Note that some of the preprocessing has also been done using our own preprocessing library pytoolkit available at kalyaniuniversity/pytoolkit.
| scRNA-seq Dataset Reference Table | |||||
|---|---|---|---|---|---|
| Sl. No. | Name | Reference | Dataset | Tools | Notes |
| 1 | BMMC-AML | Zheng, G. X., Terry, J. M., ... Gregory, M. T. (2017). Massively parallel digital transcriptional profiling of single cells. Nature communications, 8, 14049. | BMMC-AML | kalyaniuniversity/pytoolkit |
Bone marrow mononuclear cells with AML (2017), from 10x Genomics
Gene expressions in bone marrow mononuclear cells from a patient with acute myeloid leukemia (AML) and two healthy donors used as controls. The data includes over 8000 cells and 1000 genes with the highest dispersion. This is a data that comes with Loupe Cell Browser, and includes cells from three separate experiments with data sets published on 10x Genomics single-cell data sets page: AML027 Pre-transplant BMMCs, Frozen BMMCs (Healthy Control 1), and Frozen BMMCs (Healthy Control 2). |
| 2 | PBMC3k-processed | Zheng, G. X., Terry, J. M., ... Gregory, M. T. (2017). Massively parallel digital transcriptional profiling of single cells. Nature communications, 8, 14049. | PBMC3k-processed | scanpy.datasets.pbmc3k_processed | The data consist in 3k PBMCs from a Healthy Donor and are freely available from 10x Genomics. |