Panpipes - multimodal single cell pipelines

Overview

Panpipes is a set of computational workflows designed to automate multimodal single-cell and spatial transcriptomic analyses by incorporating widely-used Python-based tools to perform quality control, preprocessing, integration, clustering, and reference mapping at scale. Panpipes allows reliable and customisable analysis and evaluation of individual and integrated modalities, thereby empowering decision-making before downstream investigations.

See our documentation

Panpipes is on Genome Biology!

These workflows make use of cgat-core

Available workflows:

1. "ingest" : Ingest data and compute quality control metrics
2. "preprocess" : Filter and normalize per modality
3. "integration" : Integrate and batch correct using single and multimodal methods
4. "clustering" : Cluster cells per modality
5. "refmap" : Map queries against reference datasets
6. "vis" : Visualize metrics from other pipelines in the context of experiment metadata
7. "qc_spatial" : Ingest spatial transcriptomics data (Vizgen, Visium) and compute quality control metrics
8. "preprocess_spatial" : Filtering and normalize spatial transcriptomics data
9. "deconvolution_spatial" : Deconvolve cell types of spatial transcriptomics slides

Installation and configuration

For detailed installation instructions (including those for Apple Silicon machines), refer to the installation instructions here.

We recommend installing panpipes in a conda environment. For that, we provide a minimal conda config file in pipeline_env.yaml. First, clone this repository and navigate to the root directory of the repository:

git clone https://github.com/DendrouLab/panpipes.git
cd panpipes

Then, create the conda environment and install the nightly version of panpipes using the following command:

conda env create --file=pipeline_env.yaml 
conda activate pipeline_env
pip install -e .

Oxford BMRC Rescomp users find additional advice on the installation here.

Releases

Since panpipes v0.4.0, the ingest workflow expects different headers for the RNA and Protein modalities from the previous releases. Check the example submission file and the documentation for more detailed instructions.

Citation

Curion, F., Rich-Griffin, C., Agarwal, D. et al. Panpipes: a pipeline for multiomic single-cell and spatial transcriptomic data analysis. Genome Biol 25, 181 (2024). doi: https://doi.org/10.1186/s13059-024-03322-7

Contributors

Created and Maintained by Charlotte Rich-Griffin and Fabiola Curion. Additional contributors: Sarah Ouologuem, Devika Agarwal, Lilly May, Kevin Rue-Albrecht, Giulia Garcia, Lukas Heumos.