Skip to main content

Panpipes - multimodal single cell pipelines

Project description

Panpipes - multimodal single cell pipelines

Created and Maintained by Charlotte Rich-Griffin and Fabiola Curion
Additional contributors: Sarah Ouologuem, Devika Agarwal and Tom Thomas

See out documentation and our preprint:
Panpipes: a pipeline for multiomic single-cell data analysis
Charlotte Rich-Griffin*, Fabiola Curion*, Tom Thomas, Devika Agarwal, Fabian J. Theis, Calliope A. Dendrou.
bioRxiv 2023.03.11.532085;
doi: https://doi.org/10.1101/2023.03.11.532085

Introduction

These pipelines use cgat-core pipeline software

Available pipelines:

  1. "ingest" : for the ingestion of data and computation of QC metrics'
  2. "preprocess" : for filtering and normalising of each modality
  3. "integration" : integrate and batch correction using single and multimodal methods
  4. "clustering" : cell clustering on single modalities
  5. "refmap" : transfer scvi-tools models from published data to your data
  6. "vis" : visualise metrics from other pipelines in context of experiment metadata
  7. "qc_spatial": for the ingestion of Spatial Transcriptomics data (vizgen, visium) and computation of QC metrics
  8. "preprocess_spatial" : for filtering and normalising of ST data
  9. "deconvolution": for the cell type deconvolution of ST slides

Installation and configuration

See installation instructions here

Oxford BMRC Rescomp users find additional advice in docs/installation_rescomp

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

panpipes-0.3.0.tar.gz (160.6 kB view details)

Uploaded Source

Built Distribution

panpipes-0.3.0-py3-none-any.whl (223.7 kB view details)

Uploaded Python 3

File details

Details for the file panpipes-0.3.0.tar.gz.

File metadata

  • Download URL: panpipes-0.3.0.tar.gz
  • Upload date:
  • Size: 160.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.18

File hashes

Hashes for panpipes-0.3.0.tar.gz
Algorithm Hash digest
SHA256 e67dc38c9665fa0e6b7d9aceb4e8aaaa16eaeb00e5f0e9378667e1409f06f196
MD5 9aba700ebdec08abd18fb0205bfe4689
BLAKE2b-256 14eb8a21f9376c0b3be269fb9136d57c8906fa54b6bb6239f145aa98b648f979

See more details on using hashes here.

Provenance

File details

Details for the file panpipes-0.3.0-py3-none-any.whl.

File metadata

  • Download URL: panpipes-0.3.0-py3-none-any.whl
  • Upload date:
  • Size: 223.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.18

File hashes

Hashes for panpipes-0.3.0-py3-none-any.whl
Algorithm Hash digest
SHA256 5f52f68b22efb6205c48f0834c72f666948f0cc90e7541768a0a17f9943ec525
MD5 abe417821ed436360748df16b105b35e
BLAKE2b-256 3c91d83c2fba6174bb3e0dbce9c830bfaa4fb5f61e0f8ad25693d61023d509b6

See more details on using hashes here.

Provenance

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