Last updated: 2024-01-09

Checks: 1 1

Knit directory: mi_spatialomics/

This reproducible R Markdown analysis was created with workflowr (version 1.7.1). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.


The R Markdown file has unstaged changes. To know which version of the R Markdown file created these results, you’ll want to first commit it to the Git repo. If you’re still working on the analysis, you can ignore this warning. When you’re finished, you can run wflow_publish to commit the R Markdown file and build the HTML.

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 60d835c. 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:    analysis/.Rhistory
    Ignored:    analysis/deprecated/.DS_Store
    Ignored:    analysis/molecular_cartography_python/.DS_Store
    Ignored:    analysis/molecular_cartography_python/figures/
    Ignored:    analysis/seqIF_python/.DS_Store
    Ignored:    data/.DS_Store
    Ignored:    data/140623.calcagno_et_al.seurat_object.rds
    Ignored:    data/Calcagno2022_int_logNorm_annot.h5Seurat
    Ignored:    data/mol_cart.heart_regions/
    Ignored:    data/pixie.cell_table_size_normalized_cell_labels.csv
    Ignored:    data/results_cts_100.sqm
    Ignored:    data/seqIF_regions_annotations/
    Ignored:    data/seurat/
    Ignored:    figures/.DS_Store
    Ignored:    figures/Figure_5.pathway_plot.pdf
    Ignored:    figures/Figure_5.pca_plot.pdf
    Ignored:    figures/Figure_5.pca_plot.png
    Ignored:    figures/Figure_5.volcano_plot.pdf
    Ignored:    figures/Figure_5.vwf_expression_plot.pdf
    Ignored:    figures/Figure_5.vwf_specificity_plot.pdf
    Ignored:    figures/Supplementary_figure_3.segmentation_metrics.eps
    Ignored:    figures/Supplementary_figure_3.segmentation_metrics.png
    Ignored:    figures/figures.supplementary_figure4.png
    Ignored:    figures/mol_cart.Figure_2.gains.pdf
    Ignored:    figures/mol_cart.Figure_2.misty_gains.pdf
    Ignored:    figures/mol_cart.Myeloid_distribution.png
    Ignored:    figures/mol_cart.Nppa_distribution.eps
    Ignored:    figures/mol_cart.Nppa_distribution.pdf
    Ignored:    figures/mol_cart.Nppa_distribution.png
    Ignored:    figures/supplementary_figure4.cell_type_distributions.eps
    Ignored:    figures/supplementary_figure4.cell_type_distributions.png
    Ignored:    output/.DS_Store
    Ignored:    output/mol_cart.harmony_object.h5Seurat
    Ignored:    output/molkart/
    Ignored:    output/proteomics/
    Ignored:    output/seqIF/
    Ignored:    output/tx_abundances_per_slide.tsv
    Ignored:    pipeline_configs/mcmicro/
    Ignored:    plots/.DS_Store
    Ignored:    plots/Figure1.umap_plot.pdf
    Ignored:    plots/Figure3.ccr2_monomacro_regions.pdf
    Ignored:    plots/Figure3.cell_types_overtimes.pdf
    Ignored:    plots/Figure3.pixel_clusters_overtimes.pdf
    Ignored:    plots/mol_cart.Figure_2.ct_percentage.pdf
    Ignored:    plots/molkart.squidpy.co_occurrence_plot.CMs_Nppa.sample_2d_r1_s1.png
    Ignored:    plots/molkart.squidpy.co_occurrence_plot.CMs_Nppa.sample_2d_r2_s1.png
    Ignored:    plots/molkart.squidpy.co_occurrence_plot.CMs_Nppa.sample_control_r1_s1.png
    Ignored:    plots/molkart.squidpy.co_occurrence_plot.CMs_Nppa.sample_control_r2_s1.png
    Ignored:    plots/molkart.squidpy.co_occurrence_plot.Endocardial_cells.sample_2d_r1_s1.png
    Ignored:    plots/molkart.squidpy.co_occurrence_plot.Endocardial_cells.sample_2d_r2_s1.png
    Ignored:    plots/molkart.squidpy.co_occurrence_plot.Endocardial_cells.sample_control_r1_s1.png
    Ignored:    plots/molkart.squidpy.co_occurrence_plot.Endocardial_cells.sample_control_r2_s1.png
    Ignored:    plots/molkart.squidpy.co_occurrence_plot.Myeloid_cells.sample_2d_r1_s1.png
    Ignored:    plots/molkart.squidpy.co_occurrence_plot.Myeloid_cells.sample_2d_r2_s1.png
    Ignored:    plots/molkart.squidpy.co_occurrence_plot.Myeloid_cells.sample_control_r1_s1.png
    Ignored:    plots/molkart.squidpy.co_occurrence_plot.Myeloid_cells.sample_control_r2_s1.png
    Ignored:    plots/molkart.squidpy.nhood_enrichment_plot.sample_2d_r1_s1.png
    Ignored:    plots/molkart.squidpy.nhood_enrichment_plot.sample_2d_r2_s1.png
    Ignored:    plots/molkart.squidpy.nhood_enrichment_plot.sample_control_r1_s1.png
    Ignored:    plots/molkart.squidpy.nhood_enrichment_plot.sample_control_r2_s1.png
    Ignored:    references/.DS_Store
    Ignored:    renv/library/
    Ignored:    renv/staging/

Untracked files:
    Untracked:  pipeline_configs/nfcore_molkart/

Unstaged changes:
    Modified:   analysis/data_analysis.Rmd
    Modified:   analysis/data_processing.Rmd
    Modified:   analysis/figures.supplementary_figure_2.Rmd
    Modified:   analysis/mol_cart.QC_spots.Rmd
    Deleted:    analysis/molecular_cartography_python/kuppe_heart19.h5ad
    Modified:   analysis/molecular_cartography_python/molkart.local_analysis_lianaplus.ipynb
    Modified:   analysis/molkart.seurat_analysis.Rmd
    Modified:   code/functions.R
    Deleted:    pipeline_configs/samplesheet.nf-molkart.csv
    Modified:   plots/molkart.umap_time.png
    Modified:   renv.lock

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/data_processing.Rmd) and HTML (docs/data_processing.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 b267494 FloWuenne 2023-12-06 Build site.
Rmd 2dcd178 FloWuenne 2023-12-06 wflow_publish("*")
html 2dcd178 FloWuenne 2023-12-06 wflow_publish("*")
Rmd 5dee03d FloWuenne 2023-09-04 Latest code update.
html 5dee03d FloWuenne 2023-09-04 Latest code update.
html 67e546d FloWuenne 2023-07-23 Build site.
html 3b5ca40 FloWuenne 2023-06-12 Added code for supplementary Figures.
html 51754b9 FloWuenne 2023-06-12 Build site.
html d764fa8 FloWuenne 2023-06-12 Build site.
Rmd 62020bf FloWuenne 2023-06-12 Configure site header.

Molecular Cartography

Processing of raw data

The raw Molecular Cartography data was processed using the nf-core/molkart pipeline (revision: 81eafe9f9993d4daf16371ba3804ce9ae08053ad). The configurations, parameters and models used to reproduce the processing can be found in Synapse in the following location:

/Molecular_Cartography/nfcore_molkart

All downstream processing after nf-core/molkart was performed in R and python using scripts provided and documented in this repository. See Data processing for details.

Lunaphore

Raw Lunaphore images were processed using MCMICRO. The configurations, parameters and commands used can be found in the following files: