Skip to main content

running single cell analysis on Nvidia GPUs

Project description

Stars PyPI Downloads Documentation Status CI-Pass codecov Chat

rapids-singlecell: GPU-Accelerated Single-Cell Analysis within scverse®

rapids-singlecell provides GPU-accelerated single-cell analysis with an AnnData-first API. It is largely compatible with Scanpy and includes selected functionality from Squidpy, decoupler, and pertpy. Computations use CuPy and NVIDIA RAPIDS for performance on large datasets.

  • GPU acceleration: Common single-cell workflows on AnnData run on the GPU.
  • Ecosystem compatibility: Works with Scanpy APIs; includes pieces from Squidpy, decoupler, and pertpy.
  • Simple installation: Available via Conda and PyPI.

Documentation

For more information please have a look through the documentation

Citation

If you use this tool, please cite: arXiv

Please cite the relevant tools if used: decoupler for decoupler functions, squidpy for spatial analysis, and pertpy for perturbation analysis.

rapids-singlecell is part of the scverse® project (website, governance) and is fiscally sponsored by NumFOCUS. If you like scverse® and want to support our mission, please consider making a tax-deductible donation to help the project pay for developer time, professional services, travel, workshops, and a variety of other needs.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

rapids_singlecell_cu13-0.15.0rc7-cp312-abi3-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl (5.8 MB view details)

Uploaded CPython 3.12+manylinux: glibc 2.24+ x86-64manylinux: glibc 2.28+ x86-64

rapids_singlecell_cu13-0.15.0rc7-cp312-abi3-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl (5.7 MB view details)

Uploaded CPython 3.12+manylinux: glibc 2.24+ ARM64manylinux: glibc 2.28+ ARM64

File details

Details for the file rapids_singlecell_cu13-0.15.0rc7-cp312-abi3-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for rapids_singlecell_cu13-0.15.0rc7-cp312-abi3-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 a92d19e28be1e122b8469a0c92487f1441dc9f4e5d92206e5f6d0e051459c044
MD5 9eebe334cfecb42e5d70f820248a8013
BLAKE2b-256 cdebb2809f7d7ce00c19e98038a91974efc902849d3ee7f423d68d7b20770d44

See more details on using hashes here.

Provenance

The following attestation bundles were made for rapids_singlecell_cu13-0.15.0rc7-cp312-abi3-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl:

Publisher: publish.yml on scverse/rapids-singlecell

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file rapids_singlecell_cu13-0.15.0rc7-cp312-abi3-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for rapids_singlecell_cu13-0.15.0rc7-cp312-abi3-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 2237f9e87543d570084d4228a191fa3237a082587303e09ac14a681083403918
MD5 7febe066c7c1c3e9a479938cac872af1
BLAKE2b-256 1c5c3c95036c0b7631ea8b05db9320939e5d60e8f3e6ff947477e19067d39880

See more details on using hashes here.

Provenance

The following attestation bundles were made for rapids_singlecell_cu13-0.15.0rc7-cp312-abi3-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl:

Publisher: publish.yml on scverse/rapids-singlecell

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page