CITE-Seq CBMC

CITE-seq profiles of 8k Cord Blood Mononuclear Cells

openproblems_v1_multimodal

Info

openproblems_v1_multimodal/citeseq_cbmc
Stoeckius et al. (2017)
191.3 MiB
02-02-2024
8617 cells × 36280 genes

Used in

No related benchmarks found.

Description

8k cord blood mononuclear cells profiled by CITEsequsing a panel of 13 antibodies.

Preview

dataset_mod1 is an AnnData object with n_obs × n_vars = 8617 × 36280 with slots:

dataset_mod2 is an AnnData object with n_obs × n_vars = 8617 × 13 with slots:

Reference

Dataset mod1

Name Description Type Data type Size
obs
size_factors The size factors created by the normalisation method, if any. vector float32 8617
var
feature_name A human-readable name for the feature, usually a gene symbol. vector object 36280
hvg Whether or not the feature is considered to be a ‘highly variable gene’ vector bool 36280
hvg_score A ranking of the features by hvg. vector float64 36280
obsm
X_svd The resulting SVD embedding. densematrix float32 8617 × 12
layers
counts Raw counts sparsematrix float32 8617 × 36280
normalized Normalised expression values sparsematrix float32 8617 × 36280
uns
dataset_description Long description of the dataset. atomic str 1
dataset_id A unique identifier for the dataset. This is different from the obs.dataset_id field, which is the identifier for the dataset from which the cell data is derived. atomic str 1
dataset_name A human-readable name for the dataset. atomic str 1
dataset_organism The organism of the sample in the dataset. atomic str 1
dataset_reference Bibtex reference of the paper in which the dataset was published. atomic str 1
dataset_summary Short description of the dataset. atomic str 1
dataset_url Link to the original source of the dataset. atomic str 1
normalization_id Which normalization was used atomic str 1

Dataset mod2

Name Description Type Data type Size
obs
size_factors The size factors created by the normalisation method, if any. vector float64 8617
var
feature_name A human-readable name for the feature, usually a gene symbol. vector object 13
hvg Whether or not the feature is considered to be a ‘highly variable gene’ vector bool 13
hvg_score A ranking of the features by hvg. vector float64 13
obsm
X_svd The resulting SVD embedding. densematrix float64 8617 × 12
layers
counts Raw counts sparsematrix float64 8617 × 13
normalized Normalised expression values sparsematrix float64 8617 × 13
uns
dataset_description Long description of the dataset. atomic str 1
dataset_id A unique identifier for the dataset. This is different from the obs.dataset_id field, which is the identifier for the dataset from which the cell data is derived. atomic str 1
dataset_name A human-readable name for the dataset. atomic str 1
dataset_organism The organism of the sample in the dataset. atomic str 1
dataset_reference Bibtex reference of the paper in which the dataset was published. atomic str 1
dataset_summary Short description of the dataset. atomic str 1
dataset_url Link to the original source of the dataset. atomic str 1
normalization_id Which normalization was used atomic str 1

References

Stoeckius, Marlon, Christoph Hafemeister, William Stephenson, Brian Houck-Loomis, Pratip K Chattopadhyay, Harold Swerdlow, Rahul Satija, and Peter Smibert. 2017. “Simultaneous Epitope and Transcriptome Measurement in Single Cells.” Nature Methods 14 (9): 865–68. https://doi.org/10.1038/nmeth.4380.