Skip to main content

Cell atlas approximations, Python API

Project description

Documentation Status

Python interface to cell atlas approximations

Cell atlases such as Tabula Muris and Tabula Sapiens are multi-organ single cell omics data sets describing entire organisms. A cell atlas approximation is a lossy and lightweight compression of a cell atlas that can be streamed via the internet.

This project enables biologists, doctors, and data scientist to quickly find answers for questions such as:

  • What is the expression of a specific gene in human lung?
  • What are the marker genes of a specific cell type in mouse pancreas?
  • What fraction of cells (of a specific type) express a gene of interest?

In addition to this interface, these questions can be asked in R or in a language agnostic manner using the REST API. See the documentation for more info.

Documentation: https://atlasapprox.readthedocs.io/en/latest/python/index.html

Development: https://github.com/fabilab/cell_atlas_approximations_API

Project details


Download files

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

Source Distribution

atlasapprox-0.2.3.tar.gz (10.3 kB view details)

Uploaded Source

Built Distribution

atlasapprox-0.2.3-py3-none-any.whl (9.3 kB view details)

Uploaded Python 3

File details

Details for the file atlasapprox-0.2.3.tar.gz.

File metadata

  • Download URL: atlasapprox-0.2.3.tar.gz
  • Upload date:
  • Size: 10.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.5

File hashes

Hashes for atlasapprox-0.2.3.tar.gz
Algorithm Hash digest
SHA256 544f2f3d5ee9946b1105f2ada4be9973065e0730c58a97a98ea8f1510dd9efad
MD5 732960be2610d238ce4546eedb28d501
BLAKE2b-256 d18a803865e908ccf25edc68d0eed8a1b0a2ae75d3f28c3cecc1782c796d4f67

See more details on using hashes here.

File details

Details for the file atlasapprox-0.2.3-py3-none-any.whl.

File metadata

  • Download URL: atlasapprox-0.2.3-py3-none-any.whl
  • Upload date:
  • Size: 9.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.5

File hashes

Hashes for atlasapprox-0.2.3-py3-none-any.whl
Algorithm Hash digest
SHA256 a89605a42a093fd7deb88661e44d9b998d5e1c3200c3f18fe578d79cff653990
MD5 746816710cff78ab74ad715b1f40b539
BLAKE2b-256 47bb46c3faa61664e190cabcd69af627fa136be3ef35078f81e2efbac80bebdd

See more details on using hashes here.

Supported by

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