Published March 24, 2022 | Version v1
Dataset Open

SEACells: Inference of transcriptional and epigenomic cellular states from single-cell genomics data

  • 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

  1. CD34+ Multiome data : 2 replicates 
  2. T-cell depleted bone marrow Multiome data: 2 replicates 

 

The following counts and fragments files are available for each replicate 

  1. <sample>_filtered_feature_bc_matrix.h5: Feature counts from CellRanger ARC
  2. <sample>_atac_fragments.tsv.gz: ATAC fragments file from Cellranger ARC
  3. <sample>_atac_fragments.tsv.gz.tbi: Index files for ATAC fragments file from Cellranger ARC

 

The following scanpy anndata objects are also available

  1. 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 
  2. 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.
  3. 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.
  4. 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

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