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Pipeline for inferring cell-cell interactions from scRNAseq data using multiple publicly available tools.

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GaitiLab/scrnaseq-cellcomm-pipeline

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GaitiLab/scrnaseq-cellcomm-pipeline

Nextflow run with singularity

Introduction

GaitiLab/scrnaseq-cellcomm-pipeline is a bioinformatics pipeline that infers cell-cell interactions from scRNAseq data using various publicly available tools.

Usage

Note

If you are new to Nextflow and nf-core, please refer to this page on how to set-up Nextflow.

Requirements

  • Unix-like operating system (Linux, macOS, etc)
  • Java 18
  • Nextflow 24.10.5

Disclaimer: pipeline has been only been tested the abovementioned versions.

First, clone this GitHub repository:

git clone https://github.com/GaitiLab/scrnaseq-cellcomm-pipeline.git

If you run the pipeline offline, then please install the required plugin.

nextflow plugin install nf-schema@2.3.0

Then specify the parameters in params.yml, which contains the minimal parameters that need to be set:

  • input_file, a Seurat object containing multiple samples.
  • annot, column in Seurat object's metadata containing the annotation labels.
  • sample_var, column in Seurat object's metadata containing the sample IDs.

NOTE: ensure that the metadata of your Seurat object, does not have a column cell_type if annot is not "cell_type".

Now, you can run the pipeline using:

nextflow run scrnaseq-cellcomm-pipeline \
   -profile <docker/singularity/.../institute> \
   --outdir <OUTDIR> -params-file "params.yml" 

Warning

Please provide pipeline parameters via the CLI or Nextflow -params-file option. Custom config files including those provided by the -c Nextflow option can be used to provide any configuration except for parameters; see docs.

Citations

An extensive list of references for the tools used by the pipeline can be found in the CITATIONS.md file.

This pipeline uses code and infrastructure developed and maintained by the nf-core community, reused here under the MIT license.

The nf-core framework for community-curated bioinformatics pipelines.

Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.

Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x.

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Pipeline for inferring cell-cell interactions from scRNAseq data using multiple publicly available tools.

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