Info
zenodo_
Wang et al. (2018)
1.53 MiB
21-08-2024
2764 × 28
Three-dimensional intact-tissue sequencing of single-cell transcriptional states
zenodo_
Wang et al. (2018)
1.53 MiB
21-08-2024
2764 × 28
DATASET ID
zenodo_spatial/mouse_brain_2d_zstep10_0_starmap
REFERENCE
Wang et al. (2018)
SIZE
1.53 MiB
CREATED
21-08-2024
DIMENSIONS
2764 × 28
3D architecture of cell types in visual cortex volumes.
dataset
is an AnnData object with n_obs × n_vars = 2764 × 28 with slots:
feature_name
counts
dataset_description
, dataset_id
, dataset_name
, dataset_organism
, dataset_reference
, dataset_summary
, dataset_url
Name | Description | Type | Data type | Size |
---|---|---|---|---|
var | ||||
feature_
|
A human-readable name for the feature, usually a gene symbol. |
vector
|
object
|
28 |
layers | ||||
counts
|
Raw counts |
sparsematrix
|
float32
|
2764 × 28 |
uns | ||||
dataset_
|
Long description of the dataset. |
atomic
|
str
|
1 |
dataset_
|
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_
|
A human-readable name for the dataset. |
atomic
|
str
|
1 |
dataset_
|
The organism of the sample in the dataset. |
atomic
|
str
|
1 |
dataset_
|
Bibtex reference of the paper in which the dataset was published. |
atomic
|
str
|
1 |
dataset_
|
Short description of the dataset. |
atomic
|
str
|
1 |
dataset_
|
Link to the original source of the dataset. |
atomic
|
str
|
1 |
dataset.layers['counts']
In R: dataset$layers[["counts"]]
Type: sparsematrix
, data type: float32
, shape: 2764 × 28
Raw counts
dataset.uns['dataset_description']
In R: dataset$uns[["dataset_description"]]
Type: atomic
, data type: str
, shape: 1
Long description of the dataset.
dataset.uns['dataset_id']
In R: dataset$uns[["dataset_id"]]
Type: atomic
, data type: str
, shape: 1
A unique identifier for the dataset. This is different from the obs.dataset_id
field, which is the identifier for the dataset from which the cell data is derived.
dataset.uns['dataset_name']
In R: dataset$uns[["dataset_name"]]
Type: atomic
, data type: str
, shape: 1
A human-readable name for the dataset.
dataset.uns['dataset_organism']
In R: dataset$uns[["dataset_organism"]]
Type: atomic
, data type: str
, shape: 1
The organism of the sample in the dataset.
dataset.uns['dataset_reference']
In R: dataset$uns[["dataset_reference"]]
Type: atomic
, data type: str
, shape: 1
Bibtex reference of the paper in which the dataset was published.
dataset.uns['dataset_summary']
In R: dataset$uns[["dataset_summary"]]
Type: atomic
, data type: str
, shape: 1
Short description of the dataset.
dataset.uns['dataset_url']
In R: dataset$uns[["dataset_url"]]
Type: atomic
, data type: str
, shape: 1
Link to the original source of the dataset.
dataset.var['feature_name']
In R: dataset$var[["feature_name"]]
Type: vector
, data type: object
, shape: 28
A human-readable name for the feature, usually a gene symbol.