https://github.com/biocpy/singlecellexperiment

Container class for single-cell experiments
https://github.com/biocpy/singlecellexperiment

singlecellexperiment

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Container class for single-cell experiments

• Host: GitHub
• URL: https://github.com/biocpy/singlecellexperiment
• Owner: BiocPy
• License: mit
• Created: 2022-06-16T15:03:10.000Z (almost 3 years ago)
• Default Branch: master
• Last Pushed: 2025-04-21T16:28:39.000Z (21 days ago)
• Last Synced: 2025-04-21T17:35:41.279Z (21 days ago)
• Topics: singlecellexperiment
• Language: Python
• Homepage: https://biocpy.github.io/SingleCellExperiment/
• Size: 4.34 MB
• Stars: 7
• Watchers: 1
• Forks: 2
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE.txt
  • Authors: AUTHORS.md

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# SingleCellExperiment

This package provides container class to represent single-cell experimental data as 2-dimensional matrices. In these matrices, the rows typically denote features or genomic regions of interest, while columns represent cells. In addition, a `SingleCellExperiment` (SCE) object may contain low-dimensionality embeddings, alternative experiments performed on same sample or set of cells. Follows Bioconductor's [SingleCellExperiment](https://bioconductor.org/packages/release/bioc/html/SingleCellExperiment.html).

## Install

To get started, install the package from [PyPI](https://pypi.org/project/singlecellexperiment/)

```bash

pip install singlecellexperiment

```

## Usage

The `SingleCellExperiment` extends [RangedSummarizedExperiment](https://github.com/BiocPy/SummarizedExperiment) and contains additional attributes:

- `reduced_dims`: Slot for low-dimensionality embeddings for each cell.

- `alternative_experiments`: Manages multi-modal experiments performed on the same sample or set of cells.

- `row_pairs` or `column_pairs`: Stores relationships between features or cells.

Readers are available to parse h5ad or `AnnData` objects to SCE:

```python

import singlecellexperiment

sce = singlecellexperiment.read_h5ad("tests/data/adata.h5ad")

```

    ## output

    class: SingleCellExperiment

    dimensions: (20, 30)

    assays(3): ['array', 'sparse', 'X']

    row_data columns(5): ['var_cat', 'cat_ordered', 'int64', 'float64', 'uint8']

    row_names(0):

    column_data columns(5): ['obs_cat', 'cat_ordered', 'int64', 'float64', 'uint8']

    column_names(0):

    main_experiment_name:

    reduced_dims(0): []

    alternative_experiments(0): []

    row_pairs(0): []

    column_pairs(0): []

    metadata(2): O_recarray nested

***OR construct one from scratch***

```python

from singlecellexperiment import SingleCellExperiment

tse = SingleCellExperiment(

    assays={"counts": counts}, row_data=df_gr, col_data=col_data,

    reduced_dims={"tsne": ..., "umap": ...}, alternative_experiments={"atac": ...}

)

```

Since `SingleCellExperiment` extends `RangedSummarizedExperiment`, most methods especially slicing and accessors are inherited from the parent classes.

Checkout the [documentation](https://biocpy.github.io/SingleCellExperiment/) for more info.

## Note

This project has been set up using PyScaffold 4.5. For details and usage

information on PyScaffold see https://pyscaffold.org/.