Published March 24, 2022
| Version v1
Dataset
Open
SEACells: Inference of transcriptional and epigenomic cellular states from single-cell genomics data
Creators
- 1. Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY
- 2. Basic Sciences Division and Translational Data Science IRC, Fred Hutchinson Cancer Research Center, Seattle, WA
- 3. Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York NY
- 4. Department of Computer Science, Fu Foundation School of Engineering & Applied Science, Columbia University, New York, NY
Description
Processed data for the manuscript "" available on bioRxiv at ""
Data is available for the following samples
- CD34+ Multiome data : 2 replicates
- T-cell depleted bone marrow Multiome data: 2 replicates
The following counts and fragments files are available for each replicate
- <sample>_filtered_feature_bc_matrix.h5: Feature counts from CellRanger ARC
- <sample>_atac_fragments.tsv.gz: ATAC fragments file from Cellranger ARC
- <sample>_atac_fragments.tsv.gz.tbi: Index files for ATAC fragments file from Cellranger ARC
The following scanpy anndata objects are also available
- cd34_multiome_rna.h5ad: Anndata object with normalized data, cell type annotations and clusters for the RNA modality of CD34+ hematopoietic stem and progenitor cells
- cd34_multiome_atac.h5ad: Anndata object with peak counts, cell type annotations and clusters for the ATAC modality of of CD34+ hematopoietic stem and progenitor cells.
- cd34_multiome_rna.h5ad: Anndata object with normalized data, cell type annotations and clusters for the RNA modality of T-cell depleted bone marrow dataset.
- bm_multiome_atac.h5ad: Anndata object with peak counts, cell type annotations and clusters for the ATAC modality of T-cell depleted bone marrow dataset.
Files
Files
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