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scrnaseq-cellcomm-pipeline

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

https://github.com/gaitilab/scrnaseq-cellcomm-pipeline

Science Score: 57.0%

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    Found 13 DOI reference(s) in README
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    Academic publication links
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    Scientific vocabulary similarity
    Low similarity (9.7%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

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

Basic Info
  • Host: GitHub
  • Owner: GaitiLab
  • License: mit
  • Language: Nextflow
  • Default Branch: main
  • Size: 5.63 MB
Statistics
  • Stars: 4
  • Watchers: 0
  • Forks: 1
  • Open Issues: 0
  • Releases: 2
Created about 2 years ago · Last pushed 10 months ago
Metadata Files
Readme License Citation

README.md

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:

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

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

bash 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:

bash 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.

Owner

  • Name: GaitiLab
  • Login: GaitiLab
  • Kind: organization
  • Location: Canada

multi -omics research group at the University Health Network (UHN)

Citation (CITATIONS.md) 

# GaitiLab/scrnaseq-cellcomm-pipeline: Citations

## [nf-core](https://pubmed.ncbi.nlm.nih.gov/32055031/)

> Ewels PA, Peltzer A, Fillinger S, Patel H, Alneberg J, Wilm A, Garcia MU, Di Tommaso P, Nahnsen S. The nf-core framework for community-curated bioinformatics pipelines. Nat Biotechnol. 2020 Mar;38(3):276-278. doi: 10.1038/s41587-020-0439-x. PubMed PMID: 32055031.

## [Nextflow](https://pubmed.ncbi.nlm.nih.gov/28398311/)

> Di Tommaso P, Chatzou M, Floden EW, Barja PP, Palumbo E, Notredame C. Nextflow enables reproducible computational workflows. Nat Biotechnol. 2017 Apr 11;35(4):316-319. doi: 10.1038/nbt.3820. PubMed PMID: 28398311.

## Pipeline tools

- [LIANA](https://github.com/saezlab/liana/)
    > Dimitrov, D., Türei, D., Garrido-Rodriguez M., Burmedi P. L., Nagai, J. S., Boys, C., Flores, R. O. R., Kim, H., Szalai, B., Costa, I. G., Valdeolivas, A., Dugourd, A. and Saez-Rodriguez, J. Comparison of methods and resources for cell-cell communication inference from single-cell RNA-Seq data. Nat Commun 13, 3224 (2022). [https://doi.org/10.1038/s41467-022-30755-0](https://doi.org/10.1038/s41467-022-30755-0)
- [CellPhoneDB v5](https://github.com/ventolab/CellphoneDB)
    > Garcia-Alonso, L., Lorenzi, V., Mazzeo, C. I. et al. Single-cell roadmap of human gonadal development. Nature 607, 540–547 (2022). [https://doi.org/10.1038/s41586-022-04918-4](https://doi.org/10.1038/s41586-022-04918-4)
- [cell2cell](https://github.com/earmingol/cell2cell)
    > Armingol E, Ghaddar A, Joshi CJ, Baghdassarian H, Shamie I, et al. (2022) Inferring a spatial code of cell-cell interactions across a whole animal body. PLOS Computational Biology 18(11): e1010715. [https://doi.org/10.1371/journal.pcbi.1010715](https://doi.org/10.1371/journal.pcbi.1010715)
- [CellChat v2](https://github.com/jinworks/CellChat)
    > Jin, S., Plikus, M. V., & Nie, Q. (2023). CellChat for systematic analysis of cell-cell communication from single-cell and spatially resolved transcriptomics (p. 2023.11.05.565674). bioRxiv. [https://doi.org/10.1101/2023.11.05.565674](https://doi.org/10.1101/2023.11.05.565674)

## Software packaging/containerisation tools

- [Anaconda](https://anaconda.com)

  > Anaconda Software Distribution. Computer software. Vers. 2-2.4.0. Anaconda, Nov. 2016. Web.

- [Bioconda](https://pubmed.ncbi.nlm.nih.gov/29967506/)

  > Grüning B, Dale R, Sjödin A, Chapman BA, Rowe J, Tomkins-Tinch CH, Valieris R, Köster J; Bioconda Team. Bioconda: sustainable and comprehensive software distribution for the life sciences. Nat Methods. 2018 Jul;15(7):475-476. doi: 10.1038/s41592-018-0046-7. PubMed PMID: 29967506.

- [BioContainers](https://pubmed.ncbi.nlm.nih.gov/28379341/)

  > da Veiga Leprevost F, Grüning B, Aflitos SA, Röst HL, Uszkoreit J, Barsnes H, Vaudel M, Moreno P, Gatto L, Weber J, Bai M, Jimenez RC, Sachsenberg T, Pfeuffer J, Alvarez RV, Griss J, Nesvizhskii AI, Perez-Riverol Y. BioContainers: an open-source and community-driven framework for software standardization. Bioinformatics. 2017 Aug 15;33(16):2580-2582. doi: 10.1093/bioinformatics/btx192. PubMed PMID: 28379341; PubMed Central PMCID: PMC5870671.

- [Docker](https://dl.acm.org/doi/10.5555/2600239.2600241)

  > Merkel, D. (2014). Docker: lightweight linux containers for consistent development and deployment. Linux Journal, 2014(239), 2. doi: 10.5555/2600239.2600241.

- [Singularity](https://pubmed.ncbi.nlm.nih.gov/28494014/)

  > Kurtzer GM, Sochat V, Bauer MW. Singularity: Scientific containers for mobility of compute. PLoS One. 2017 May 11;12(5):e0177459. doi: 10.1371/journal.pone.0177459. eCollection 2017. PubMed PMID: 28494014; PubMed Central PMCID: PMC5426675.

## Other

Türei, D., Valdeolivas, A., Gul, L., Palacio‐Escat, N., Klein, M., Ivanova, O., Ölbei, M., Gábor, A., Theis, F., Módos, D. and Korcsmáros, T., 2021. Integrated intra‐and intercellular signaling knowledge for multicellular omics analysis. Molecular systems biology, 17(3), p.e9923. <https://doi.org/10.15252/msb.20209923>

Kolde, R., Laur, S., Adler, P., & Vilo, J. (2012). Robust rank aggregation for gene list integration and meta-analysis. Bioinformatics, 28(4), 573–580. <https://doi.org/10.1093/bioinformatics/btr709>

Schröder, M. S., Culhane, A. C., Quackenbush, J., & Haibe-Kains, B. (2011). survcomp: an R/Bioconductor package for performance assessment and comparison of survival models. Bioinformatics (Oxford, England), 27(22), 3206–3208. <https://doi.org/10.1093/bioinformatics/btr511>

Haibe-Kains, B., Desmedt, C., Sotiriou, C., & Bontempi, G. (2008). A comparative study of survival models for breast cancer prognostication based on microarray data: does a single gene beat them all?. Bioinformatics (Oxford, England), 24(19), 2200–2208. <https://doi.org/10.1093/bioinformatics/btn374>

Benjamini, Y., and Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society Series B, 57, 289--300. <http://www.jstor.org/stable/2346101>.

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Dependencies

DESCRIPTION cran
  • BiocManager * imports
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