Last updated: 2023-07-23

Checks: 2 0

Knit directory: mi_spatialomics/

This reproducible R Markdown analysis was created with workflowr (version 1.7.0). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.

R Markdown file: up-to-date

Great! Since the R Markdown file has been committed to the Git repository, you know the exact version of the code that produced these results.

Repository version: d6085a2

Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility.

The results in this page were generated with repository version d6085a2. See the Past versions tab to see a history of the changes made to the R Markdown and HTML files.

Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use wflow_publish or wflow_git_commit). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated:


Ignored files:
    Ignored:    .DS_Store
    Ignored:    .Rhistory
    Ignored:    .Rproj.user/
    Ignored:    analysis/.DS_Store
    Ignored:    data/.DS_Store
    Ignored:    data/.Rapp.history
    Ignored:    data/140623.calcagno_et_al.seurat_object.rds
    Ignored:    omnipathr-log/
    Ignored:    plots/
    Ignored:    references/.DS_Store
    Ignored:    renv/.DS_Store
    Ignored:    renv/library/
    Ignored:    renv/staging/

Untracked files:
    Untracked:  data/cells_per_region.tsv
    Untracked:  figures.supplementary_figure_3.Rmd
    Untracked:  figures/Supplementary_figure_5.segmentation_metrics.poster.eps

Unstaged changes:
    Deleted:    analysis/figures.supplementary_Figure_3.Rmd
    Modified:   code/functions.R
    Modified:   figures/Figure_5.eps
    Modified:   figures/Figure_5.pdf
    Modified:   figures/Figure_5.png
    Modified:   figures/Figure_5.svg
    Modified:   figures/Supplementary_figure_5.segmentation_metrics.eps
    Modified:   figures/Supplementary_figure_5.segmentation_metrics.png

Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.

These are the previous versions of the repository in which changes were made to the R Markdown (analysis/index.Rmd) and HTML (docs/index.html) files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.

File	Version	Author	Date	Message
html	3b5ca40	FloWuenne	2023-06-12	Added code for supplementary Figures.
html	51754b9	FloWuenne	2023-06-12	Build site.
html	09358ac	FloWuenne	2023-06-12	Build site.
Rmd	576e518	FloWuenne	2023-06-12	wflow_publish("analysis/index.Rmd")
html	8ef6779	FloWuenne	2023-06-12	Build site.
Rmd	0c01112	FloWuenne	2023-06-12	wflow_publish(c("analysis/about.Rmd", "analysis/index.Rmd", "analysis/license.Rmd"))
Rmd	9e88e37	FloWuenne	2023-06-12	Start workflowr project.

Introduction

Data setup

All scripts in this repository assume that this repository is in the same folder as the /data directory, containing all the data on Synapse. Data directory structure can be set up using the Synapse command-line interace with the following command

`synapse get -r syn51449054 `

For more options to download the data within Synapse, you can select Download Options in the Synapse project and check out Programmatic options. This will allow to also download the data directly using R and Python.

You can then clone this repository alongside the data repository from Synapse:

git clone https://github.com/SchapiroLabor/MI_infiltration_imaging.git

Data processing

Pipelines used to process the imaging data

Imaging data in this study was processed using nextflow based pipelines designed for the specific data type. Links to the original pipeline repositories is provided below. Config files and specifications for running each pipeline to process the data is provided in this repository under : ./

Processing of Molecular Cartography was done using nf-MolCart.
Processing of SeqIF (Lunaphore COMET) data was done using MCMICRO.

For more details on data processing, go to Data processing.

Data availability

All raw images and processed data is available from Synapse: Highly-multiplexed imaging of immune cell infiltration routes in myocardial infarction.

Citation

Please cite our preprint if using any of the data used in study: