Last updated: 2025-04-13
Checks: 7 0
Knit directory: KODAMA-Analysis/
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.
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.
Great job! The global environment was empty. Objects defined in the global environment can affect the analysis in your R Markdown file in unknown ways. For reproduciblity it’s best to always run the code in an empty environment.
The command set.seed(20240618) was run prior to running
the code in the R Markdown file. Setting a seed ensures that any results
that rely on randomness, e.g. subsampling or permutations, are
reproducible.
Great job! Recording the operating system, R version, and package versions is critical for reproducibility.
Nice! There were no cached chunks for this analysis, so you can be confident that you successfully produced the results during this run.
Great job! Using relative paths to the files within your workflowr project makes it easier to run your code on other machines.
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 5f5ac63. 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: .RData
Ignored: .Rhistory
Ignored: .Rproj.user/
Untracked files:
Untracked: KODAMA.svg
Untracked: analysis/singlecell_datamatrix.Rmd
Untracked: analysis/singlecell_seurat.Rmd
Untracked: code/Acinar_Cell_Carcinoma.ipynb
Untracked: code/Adenocarcinoma.ipynb
Untracked: code/Adjacent_normal_section.ipynb
Untracked: code/DLFPC_preprocessing.R
Untracked: code/DLPFC - BANKSY.R
Untracked: code/DLPFC - BASS.R
Untracked: code/DLPFC - BAYESPACE.R
Untracked: code/DLPFC - Nonspatial.R
Untracked: code/DLPFC - PRECAST.R
Untracked: code/DLPFC_comparison.R
Untracked: code/DLPFC_results_analysis.R
Untracked: code/MERFISH - BANKSY.R
Untracked: code/MERFISH - BASS.R
Untracked: code/MERFISH - BAYESPACE.R
Untracked: code/MERFISH - Nonspatial.R
Untracked: code/MERFISH - PRECAST.R
Untracked: code/MERFISH_comparison.R
Untracked: code/MERFISH_results_analysis.R
Untracked: code/VisiumHD-CRC.ipynb
Untracked: code/VisiumHDassignment.py
Untracked: code/deep learning code DLPFC.R
Untracked: code/save tiles.py
Untracked: data/Adenocarcinoma.csv
Untracked: data/Annotations/
Untracked: data/DLFPC-Br5292-input.RData
Untracked: data/DLFPC-Br5595-input.RData
Untracked: data/DLFPC-Br8100-input.RData
Untracked: data/DLPFC-general.RData
Untracked: data/MERFISH-input.RData
Untracked: data/spots_classification_ALL.csv
Untracked: data/spots_classification_Acinar_Cell_Carcinoma.csv
Untracked: data/spots_classification_IF.csv
Untracked: data/spots_classification_Normal_prostate.csv
Untracked: data/trajectories.RData
Untracked: data/trajectories_VISIUMHD.RData
Untracked: output/BANSKY-results.RData
Untracked: output/BASS-results.RData
Untracked: output/BayesSpace-results.RData
Untracked: output/CRC-image.RData
Untracked: output/CRC-image2.RData
Untracked: output/CRC.png
Untracked: output/CRC2.png
Untracked: output/CRC7.png
Untracked: output/CRC8.png
Untracked: output/CRC_boxplot.png
Untracked: output/CRC_boxplot.svg
Untracked: output/CRC_boxplot2.svg
Untracked: output/CRC_linee.svg
Untracked: output/DL.RData
Untracked: output/DLFPC-All-2.RData
Untracked: output/DLFPC-All.RData
Untracked: output/DLFPC-Br5292.RData
Untracked: output/DLFPC-Br5595.RData
Untracked: output/DLFPC-Br8100.RData
Untracked: output/DLFPC-variablesXdeeplearning.RData
Untracked: output/DLPFC-BANSKY-results.RData
Untracked: output/DLPFC-BASS-results.RData
Untracked: output/DLPFC-BayesSpace-results.RData
Untracked: output/DLPFC-Nonspatial-results.RData
Untracked: output/DLPFC-PRECAST-results.RData
Untracked: output/DLPFC_all_cluster.svg
Untracked: output/DLPFCpathway.RData
Untracked: output/Figure 1 - boxplot.pdf
Untracked: output/Figure 2 - DLPFC 10.pdf
Untracked: output/Figures/
Untracked: output/KODAMA-results.RData
Untracked: output/KODAMA_DLPFC_All_original.svg
Untracked: output/KODAMA_DLPFC_Br5595.svg
Untracked: output/KODAMA_DLPFC_Br5595_slide.svg
Untracked: output/Loupe.csv
Untracked: output/MERFISH-BANSKY-results.RData
Untracked: output/MERFISH-BASS-results.RData
Untracked: output/MERFISH-BayesSpace-results.RData
Untracked: output/MERFISH-KODAMA-results.RData
Untracked: output/MERFISH-Nonspatial-results.RData
Untracked: output/MERFISH-PRECAST-results.RData
Untracked: output/MERFISH.RData
Untracked: output/Nonspatial-results.RData
Untracked: output/Prostate.RData
Untracked: output/VisiumHD-RNA.RData
Untracked: output/VisiumHD-genes.pdf
Untracked: output/VisiumHD.RData
Untracked: output/boh.svg
Untracked: output/desmoplastic_distance_carcinoma.csv
Untracked: output/image.RData
Untracked: output/pp.RData
Untracked: output/pp2.RData
Untracked: output/pp3.RData
Untracked: output/pp4.RData
Untracked: output/pp5.RData
Untracked: output/prostate1.svg
Untracked: output/prostate2.svg
Untracked: output/prostate3.svg
Untracked: output/prostate4.svg
Untracked: output/prostate5.svg
Untracked: output/prostate6.svg
Untracked: output/prostate7.svg
Untracked: output/subclusters1.csv
Untracked: output/subclusters2.csv
Untracked: output/subclusters3.csv
Untracked: output/tight_boundary.geojson
Untracked: output/trajectory.csv
Unstaged changes:
Deleted: analysis/D1.Rmd
Deleted: analysis/DLPFC-12.Rmd
Deleted: analysis/DLPFC-4.Rmd
Modified: analysis/DLPFC.Rmd
Deleted: analysis/DLPFC1.Rmd
Deleted: analysis/DLPFC10.Rmd
Deleted: analysis/DLPFC2.Rmd
Deleted: analysis/DLPFC3.Rmd
Deleted: analysis/DLPFC4.Rmd
Deleted: analysis/DLPFC5.Rmd
Deleted: analysis/DLPFC6.Rmd
Deleted: analysis/DLPFC7.Rmd
Deleted: analysis/DLPFC8.Rmd
Deleted: analysis/DLPFC9.Rmd
Deleted: analysis/Du1.Rmd
Deleted: analysis/Du10.Rmd
Deleted: analysis/Du11.Rmd
Deleted: analysis/Du12.Rmd
Deleted: analysis/Du13.Rmd
Deleted: analysis/Du14.Rmd
Deleted: analysis/Du15.Rmd
Deleted: analysis/Du16.Rmd
Deleted: analysis/Du17.Rmd
Deleted: analysis/Du18.Rmd
Deleted: analysis/Du19.Rmd
Deleted: analysis/Du2.Rmd
Deleted: analysis/Du20.Rmd
Deleted: analysis/Du3.Rmd
Deleted: analysis/Du4.Rmd
Deleted: analysis/Du5.Rmd
Deleted: analysis/Du6.Rmd
Deleted: analysis/Du7.Rmd
Deleted: analysis/Du8.Rmd
Deleted: analysis/Du9.Rmd
Modified: analysis/Giotto.Rmd
Modified: analysis/MERFISH.Rmd
Deleted: analysis/MERFISH1a (copy).Rmd
Deleted: analysis/MERFISH1a.Rmd
Deleted: analysis/MERFISH1b (copy).Rmd
Deleted: analysis/MERFISH1b.Rmd
Deleted: analysis/MERFISH2a (copy).Rmd
Deleted: analysis/MERFISH2a.Rmd
Deleted: analysis/MERFISH2b (copy).Rmd
Deleted: analysis/MERFISH2b.Rmd
Deleted: analysis/MERFISH3a (copy).Rmd
Deleted: analysis/MERFISH3a.Rmd
Deleted: analysis/MERFISH3b (copy).Rmd
Deleted: analysis/MERFISH3b.Rmd
Deleted: analysis/MERFISH4a (copy).Rmd
Deleted: analysis/MERFISH4a.Rmd
Deleted: analysis/MERFISH4b (copy).Rmd
Deleted: analysis/MERFISH4b.Rmd
Modified: analysis/Prostate.Rmd
Deleted: analysis/STARmap.Rmd
Modified: analysis/Seurat.Rmd
Deleted: analysis/Simulation.Rmd
Deleted: analysis/Single-cell.Rmd
Modified: analysis/SpatialExperiment.Rmd
Modified: analysis/VisiumHD.Rmd
Modified: code/VisiumHD_CRC_download.sh
Deleted: data/Pathology.csv
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/Installation.Rmd) and HTML
(docs/Installation.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 | d1192e9 | Stefano Cacciatore | 2024-08-12 | Build site. |
| html | 3374e66 | Stefano Cacciatore | 2024-08-06 | Build site. |
| html | 35ce733 | Stefano Cacciatore | 2024-08-03 | Build site. |
| html | 82fe167 | Stefano Cacciatore | 2024-07-24 | Build site. |
| html | 6f7daac | Stefano Cacciatore | 2024-07-19 | Build site. |
| html | 7be8f59 | tkcaccia | 2024-07-15 | updates |
| Rmd | f8ca54a | tkcaccia | 2024-07-14 | update |
| html | f8ca54a | tkcaccia | 2024-07-14 | update |
| html | 51acb3a | GitHub | 2024-07-08 | Update Installation.html |
| Rmd | fb9ca6e | GitHub | 2024-07-08 | Update Installation.Rmd |
| html | bfeb48a | GitHub | 2024-07-08 | Update Installation.html |
| html | 03a652c | GitHub | 2024-07-04 | Add files via upload |
| Rmd | 05f27af | GitHub | 2024-07-04 | Add files via upload |
Welcome to the KODAMA software installation tutorial page. This guide will walk you through the steps to install and set up KODAMA, a powerful tool for metabolomics data analysis.
Before installing KODAMA, ensure you have the following:
R (>= 4.0.3): Make sure you have R installed on your system. You can download it from CRAN.
RStudio (Optional): While not required, RStudio provides a convenient interface for working with R projects. You can download it from RStudio’s official site.
Use the following commands to install KODAMA from GitHub using the
devtools package:
if (!require(devtools)) {
install.packages("devtools")
}
devtools::install_github("tkcaccia/KODAMA")
devtools::install_github("tkcaccia/KODAMAextra")Once installed, load the KODAMA package into your R session:
library(KODAMA)To verify that KODAMA has been installed correctly, you can check its version:
packageVersion("KODAMA")For any issues or questions related to KODAMA, please open an issue on the GitHub repository.
sessionInfo()R version 4.4.3 (2025-02-28)
Platform: x86_64-pc-linux-gnu
Running under: Ubuntu 20.04.6 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
time zone: Etc/UTC
tzcode source: system (glibc)
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] workflowr_1.7.1
loaded via a namespace (and not attached):
[1] vctrs_0.6.5 httr_1.4.7 cli_3.6.4 knitr_1.50
[5] rlang_1.1.5 xfun_0.51 stringi_1.8.7 processx_3.8.6
[9] promises_1.3.2 jsonlite_2.0.0 glue_1.8.0 rprojroot_2.0.4
[13] git2r_0.33.0 htmltools_0.5.8.1 httpuv_1.6.15 ps_1.9.0
[17] sass_0.4.9 rmarkdown_2.29 jquerylib_0.1.4 tibble_3.2.1
[21] evaluate_1.0.3 fastmap_1.2.0 yaml_2.3.10 lifecycle_1.0.4
[25] whisker_0.4.1 stringr_1.5.1 compiler_4.4.3 fs_1.6.5
[29] pkgconfig_2.0.3 Rcpp_1.0.14 rstudioapi_0.17.1 later_1.4.1
[33] digest_0.6.37 R6_2.6.1 pillar_1.10.1 callr_3.7.6
[37] magrittr_2.0.3 bslib_0.9.0 tools_4.4.3 cachem_1.1.0
[41] getPass_0.2-4