Spatial Methods Workbench v0.3.1

Spatial Methods Workbench v0.3.1

This patch release adds visible, exportable figures across all 12 analysis pipelines and corrects the GitHub Actions build configuration.

Changes

• Every successful Shiny analysis now displays its figure in the Figure tab and identifies the analysis that generated it.
• Conditional-network, ISPAT, and ISPAT-3D workflows now generate network diagrams.
• GP-GHS network edge widths are computed from posterior mean coefficient-field RMS values; kappa values are not used as visual weights.
• Deterministic, ready-to-analyze synthetic datasets are included for demonstrations and advisor review.
• Figure rendering, network construction, release contents, and all existing workflows have expanded automated coverage.
• The GitHub Actions dependency list now installs igraph, allowing the complete tests and vignette build to compile successfully.

Validation

• 74 automated tests passed.
• Release-content audit passed.
• All five vignettes built successfully.
• R CMD check completed with Status: OK.

Funding acknowledgement

Research reported in this software was supported by the National Cancer Institute of the National Institutes of Health under Award Number R37CA214955-01A1. The content is solely the responsibility of the author and does not necessarily represent the official views of the National Institutes of Health.

Users should cite the versioned Workbench DOI and each method-specific publication or software source applicable to the workflow used.

Spatial Methods Workbench v0.3.0 — complete public source distribution

Spatial Methods Workbench v0.3.0 - complete public source distribution

This v0.3.0 release is the reproducible public Workbench distribution.

Included

• Functional R Shiny application and installable R package
• 12 guided analysis paths spanning spatial autocorrelation, conditional networks, spatially adjusted 2D/3D networks, prediction, clustering, image regression, mediation, and statistical shape analysis
• Exact bundled public source for ISPAT, GP-GHS, and ISPAT-3D
• Curated, license-preserving public source for the related AI/ML, neural, SV-NN, STCAR, and SBLF workflows documented by the Workbench
• Five executable vignettes, four small simulated datasets, full function/pipeline guidance, method citations, and provenance manifest
• 51 automated tests plus a release-content audit

Install the complete distribution

1. Download and extract SpatialMethodsWorkbench-v0.3.0-source.zip below.
2. Run Rscript install-complete.R in the extracted folder.
3. Run Rscript verify-installation.R.
4. Launch locally with shiny::runApp().

See README.md for prerequisites, Windows/macOS/Linux instructions, optional related-engine installation, Docker, privacy restrictions, and troubleshooting. CRAN dependencies may still be downloaded; the three direct method repositories do not need to be cloned separately.

Attribution

Please cite Spatial Methods Workbench and the method-specific publications/software relevant to the workflow used. See REFERENCES.md, CITATION.cff, and vendor/manifest.json.

Only public, release-scoped software and documentation are included. The Workbench computes and exports reproducibility artifacts but does not provide automated scientific interpretation; contact Sagnik Bhadury for interpretation support or collaboration.

Funding acknowledgement

Research reported in this software was supported by the National Cancer Institute of the National Institutes of Health under Award Number R37CA214955-01A1. The content is solely the responsibility of the author and does not necessarily represent the official views of the National Institutes of Health.

Spatial Methods Workbench v0.2.1

Complete public toolkit documentation and advanced-engine release.\n\nHighlights:\n- Function-by-function reference for all 12 executable workflows and their programmatic interfaces\n- Complete usage, restrictions, real-data preparation, local installation, Docker, and deployment guide\n- Live integration support for public ISPAT, GP-GHS, and ISPAT-3D engines\n- Citation and reproducibility artifacts in every result bundle\n- Explicit no-interpretation policy: the software reports statistical outputs without assigning scientific meaning\n- 30 automated checks passing\n\nResearchers should cite this software release and every method-specific reference included in the exported result bundle.

Funding acknowledgement

Research reported in this software was supported by the National Cancer Institute of the National Institutes of Health under Award Number R37CA214955-01A1. The content is solely the responsibility of the author and does not necessarily represent the official views of the National Institutes of Health.

Spatial Methods Workbench v0.2.0

Expands the public workbench from eight to twelve executable analysis paths. Adds spatially weighted phenotype clustering, shallow-neural spatial prediction, wide-image scalar regression screening, and latent image-to-image regression. Includes upstream curriculum/software/publication attribution, explicit screening-versus-Bayesian-engine labels, no automated result explanation, 29 passing tests, and the existing citation/provenance controls.

Funding acknowledgement

Research reported in this software was supported by the National Cancer Institute of the National Institutes of Health under Award Number R37CA214955-01A1. The content is solely the responsibility of the author and does not necessarily represent the official views of the National Institutes of Health.

Spatial Methods Workbench v0.1.1

Zenodo-enabled software release. This release preserves the citation acknowledgement, method-specific citation bundles, non-disclosure safeguards, and the policy that the application does not interpret results. Researchers are directed to Sagnik Bhadury for scientific interpretation and collaboration.

Funding acknowledgement

Research reported in this software was supported by the National Cancer Institute of the National Institutes of Health under Award Number R37CA214955-01A1. The content is solely the responsibility of the author and does not necessarily represent the official views of the National Institutes of Health.

Spatial Methods Workbench v0.1.0

Initial public release of the guided Shiny workbench. Includes validated upload workflows, compatibility-gated spatial and network analyses, public advanced-engine adapters, mandatory citation acknowledgement, method-specific citation bundles, disclosure safeguards, Docker configuration, and automated tests. The application deliberately does not interpret results; users are directed to contact Sagnik Bhadury for scientific interpretation or collaboration.

Funding acknowledgement

Research reported in this software was supported by the National Cancer Institute of the National Institutes of Health under Award Number R37CA214955-01A1. The content is solely the responsibility of the author and does not necessarily represent the official views of the National Institutes of Health.