Skip to main content

Project generated with PyScaffold PyPI-Server Unit tests

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.

Install

To get started, install the package from PyPI

pip install singlecellexperiment

Usage

The SingleCellExperiment extends RangedSummarizedExperiment 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:

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

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 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/.

Metadata

Release files for singlecellexperiment 0.6.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for singlecellexperiment 0.6.3
File Size Uploaded
singlecellexperiment-0.6.3.tar.gz 1.1 MB Details

Built distribution (wheel)

Table of built distributions (wheels) for singlecellexperiment 0.6.3
File Interpreter ABI Platform
singlecellexperiment-0.6.3-py3-none-any.whl Python 3 none any Details

Total release size: 1.1 MB

Release files / singlecellexperiment-0.6.3.tar.gz

Download URL singlecellexperiment-0.6.3.tar.gz
Size 1.1 MB
Tags Source
SHA-256 checksum
How to use checksums
e1365e17222af1d0c0116da30e353eb3e46d8d01b218e9efbf4e3a7a1a59528f
BLAKE2b-256 checksum
How to use checksums
616d45a2df6492d68edc03a476efda6c5abbab3001f95fc848c0bea77d877597
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.1.0 CPython/3.13.12

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Jun 24, 2026.

Transparency log

Release files / singlecellexperiment-0.6.3-py3-none-any.whl

Download URL singlecellexperiment-0.6.3-py3-none-any.whl
Size 17.5 kB
Tags Python 3
SHA-256 checksum
How to use checksums
3c0a9e24c1caa70cc7f68a3ce0218f64baef20950cad86c4e05bb0d26ab33f3a
BLAKE2b-256 checksum
How to use checksums
284488a589a6a0df101b95ed3bfea6b97201ace6ef7ad7b3c7cbd0d44f33a898
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.1.0 CPython/3.13.12

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Jun 24, 2026.

Transparency log

Release history Release notifications | RSS feed

0.7.0

2 release files

0.6.4

2 release files

This release

0.6.3 This release

2 release files

0.6.2

2 release files

0.6.1

2 release files

0.6.0

2 release files

0.5.9

2 release files

0.5.8

2 release files

0.5.7

2 release files

0.5.6

2 release files

0.5.5

2 release files

0.5.4

2 release files

0.5.3

2 release files

0.5.2

2 release files

0.5.1

2 release files

0.5.0

2 release files

0.4.7

2 release files

0.4.6

2 release files

0.4.5

2 release files

0.4.4

2 release files

0.4.3

2 release files

0.4.2

2 release files

0.4.1

2 release files

0.4.0

2 release files

0.3.3

2 release files

0.3.2

2 release files

0.3.1

2 release files

0.3.0

2 release files

0.2.6

2 release files

0.2.5

2 release files

0.2.4

2 release files

0.2.3

2 release files

0.2.2

2 release files

0.2.1

2 release files

0.2

2 release files

0.1

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page