Triple-Negative Breast Cancer

1535 cells from six fresh triple-negative breast cancer tumors.

openproblems_v1

Info

openproblems_v1/tnbc_wu2021
Wu et al. (2021)
1.18 GiB
02-02-2024
42512 cells × 28200 genes

Used in

Description

1535 cells from six TNBC donors by (Wu et al., 2021). This dataset includes cytokine activities, inferred using a multivariate linear model with cytokine-focused signatures, as assumed true cell-cell communication (Dimitrov et al., 2022).

Preview

dataset is an AnnData object with n_obs × n_vars = 42512 × 28200 with slots:

Reference

Name Description Type Data type Size
obs
cell_type Classification of the cell type based on its characteristics and function within the tissue or organism. vector category 42512
size_factors The size factors created by the normalisation method, if any. vector float32 42512
var
feature_name A human-readable name for the feature, usually a gene symbol. vector object 28200
hvg Whether or not the feature is considered to be a ‘highly variable gene’ vector bool 28200
hvg_score A ranking of the features by hvg. vector float64 28200
obsp
knn_connectivities K nearest neighbors connectivities matrix. sparsematrix float32 42512 × 42512
knn_distances K nearest neighbors distance matrix. sparsematrix float64 42512 × 42512
obsm
X_pca The resulting PCA embedding. densematrix float32 42512 × 50
varm
pca_loadings The PCA loadings matrix. densematrix float32 28200 × 50
layers
counts Raw counts sparsematrix float32 42512 × 28200
normalized Normalised expression values sparsematrix float32 42512 × 28200
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
knn Supplementary K nearest neighbors data. dict 3
normalization_id Which normalization was used atomic str 1
pca_variance The PCA variance objects. dict 2

References

Wu, Sunny Z., Ghamdan Al-Eryani, Daniel Lee Roden, Simon Junankar, Kate Harvey, Alma Andersson, Aatish Thennavan, et al. 2021. “A Single-Cell and Spatially Resolved Atlas of Human Breast Cancers.” Nature Genetics 53 (9): 1334–47. https://doi.org/10.1038/s41588-021-00911-1.