Introduction

btc/spatial is a bioinformatics pipeline for 10X Visium and Visium HD spatial data. Being a simple preprocessing-deconvolution-interaction pipeline it features multiple tools, including reference-based deconvolution. In case of reference-based deconvolution, atlas may be specified as an URL on an S3 location (e.g. CellxGene), or matched-scRNAmade made available in the sample folder.

Usage

[!note] If you are new to Nextflow and nf-core, please refer to this page on how to set-up Nextflow. Make sure to test your setup with -profile test before running the workflow on actual data.

First, prepare a samplesheet with your input data that looks as follows: samplesheet.csv:

Each row represents a spatial transcriptomics sample and configuration parameters specific to that sample.

sample: A unique identifier for the sample.

data_directory: The path to the directory containing the output of the spaceranger pipeline.

n_cell_types: This parameter controls how many cell types to deconvolve into. If you pass expression_profile this value will be ignored, we will determine number of cell types from the matched scRNA data.

bleeding_correction: set to true if you want to enable bleeding correction for that sample.

expression_profile: Optional reference expression profiles (leave blank if not using) if you have known cell types in your Visium data (perhaps from matched scRNA). See more info about how to generate this file here: https://bayestme.readthedocs.io/en/latest/finemappingworkflow.html

run_bayestme: boolean, whether to run BayesTME deconvolution.

run_cogaps: boolean, whether to run BayesTME deconvolution.

run_spacemarkers: boolean, whether to run SpaceMarkers

find_annotations: boolean, if true, CODA annotations will be sought by *tissue_positions_cellular_compositions.csv string and the data will be fed to SpaceMarkers. This has potential to run any external annotation from a csv.

[!IMPORTANT] export NXF_SINGULARITY_HOME_MOUNT=true in order to allow matplotlib to write its logs (and avoid related error) if using singularity.

Simple run without reference deconvolution:

bash nextflow run break-through-cancer/btc-spatial-pipelines \ -profile <docker/singularity/.../institute> \ --input samplesheet.csv \ --outdir <OUTDIR>

Run with Visium HD support and reference atlas annotation nextflow run break-through-cancer/btc-spatial-pipelines -profile docker --input samplesheet.csv --outdir out --hd 'square_016um' --reference_scrna https://datasets.cellxgene.cziscience.com/d1d90d18-2109-412f-8dc0-e014e8abb338.h5ad --type_col_scrna Clusters -resume

[!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.

Contributions and Support

If you would like to contribute to this pipeline, please see the contributing guidelines.

Citations

Zhang H, Hunter MV, Chou J, Quinn JF, Zhou M, White RM, Tansey W. BayesTME: An end-to-end method for multiscale spatial transcriptional profiling of the tissue microenvironment. Cell Syst. 2023 Jul 19;14(7):605-619.e7. doi: 10.1016/j.cels.2023.06.003. PMID: 37473731; PMCID: PMC10368078.

Deshpande A, Loth M, Sidiropoulos DN, Zhang S, Yuan L, Bell ATF, Zhu Q, Ho WJ, Santa-Maria C, Gilkes DM, Williams SR, Uytingco CR, Chew J, Hartnett A, Bent ZW, Favorov AV, Popel AS, Yarchoan M, Kiemen A, Wu PH, Fujikura K, Wirtz D, Wood LD, Zheng L, Jaffee EM, Anders RA, Danilova L, Stein-O'Brien G, Kagohara LT, Fertig EJ. Uncovering the spatial landscape of molecular interactions within the tumor microenvironment through latent spaces. Cell Syst. 2023 Apr 19;14(4):285-301.e4. doi: 10.1016/j.cels.2023.03.004. Erratum in: Cell Syst. 2023 Aug 16;14(8):722. PMID: 37080163; PMCID: PMC10236356.

Sherman TD, Gao T, Fertig EJ. CoGAPS 3: Bayesian non-negative matrix factorization for single-cell analysis with asynchronous updates and sparse data structures. BMC Bioinformatics. 2020 Oct 14;21(1):453. doi: 10.1186/s12859-020-03796-9. PMID: 33054706; PMCID: PMC7556974.

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.