Imaging Data Workspace Integration

imaging-data-workspace-integration

License: restricted — no clear open-source license detected for the underlying tool; verify licensing before commercial use or redistribution.

Summary

Load and integrate mass spectrometry imaging (MSI) data from NetCDF files with their corresponding Matlab workspaces to enable reproducible linear-axis analysis in the DIMPLE computational pipeline. This skill bridges raw instrument output (cdf) with pre-computed analysis metadata (Matlab workspace variables) to ensure consistent per-root metric computation.

When to use

You have paired cdf files (raw mass spectrometry imaging data) and Matlab workspace (.mat) files for the same root sample, and you need to reproduce published linear-axis imaging analysis results (e.g., per-root mass spectrometry imaging metrics along a developmental or spatial axis). Typical trigger: repository provides both data types and a published result to validate against.

When NOT to use

• Input cdf and workspace files are from different root samples or genotypes — integration will produce misaligned axis mappings and invalid metrics.
• Workspace file is missing or corrupted — you cannot restore the analysis configuration; reload from raw parameters or skip workspace integration.
• Raw imaging data is already pre-processed into a feature table or summary matrix — use direct metric computation instead of re-integrating raw cdf data.

Inputs

• NetCDF (cdf) file containing raw mass spectrometry imaging pixel data (m/z values and intensities)
• Matlab workspace (.mat) file containing pre-computed axis definitions, masks, calibration metadata, or prior analysis parameters for the same root
• DIMPLE pipeline codebase (Matlab functions and scripts)

Outputs

• Integrated Matlab workspace with raw imaging data and metadata unified in memory
• Per-root linear-axis mass spectrometry imaging metrics (composition, intensity, or metabolite abundance along the root axis)
• Validation report confirming outputs match published genotype-specific results

How to apply

Access and download the paired cdf and Matlab workspace files from the DIMPLE repository for your target root dataset (e.g., OG1 cdf + OG1-workspace-2.mat). Load both into Matlab using the DIMPLE pipeline environment: read the cdf file (likely using the batchcdfread function) to obtain raw m/z and intensity matrices, then load the workspace file to restore pre-computed axis definitions, ROI masks, or calibration parameters. Execute the DIMPLE linear-axis analysis workflow on the integrated data to compute per-root metrics. Validate outputs by comparing computed values against published results for that genotype and root ID; mismatches indicate either incomplete data integration or pipeline configuration drift.

Related tools

• DIMPLE (Developmental Imaging Mass Spectrometry Pipeline for Linear Evaluation) (Orchestrates cdf file loading, workspace integration, and per-root linear-axis analysis workflow) — https://github.com/dickinsonlab/DIMPLE-code
• Matlab (Runtime environment for loading cdf files via batchcdfread and executing workspace-integrated analysis functions)
• batchcdfread function (Reads NetCDF (cdf) files to extract raw m/z and intensity matrices for imaging data)

Evaluation signals

• Both cdf and workspace files load without errors; Matlab session contains expected variables (raw imaging matrix, axis vectors, ROI masks).
• Per-root metric outputs (intensity profiles, composition along axis) are numerically identical or within expected floating-point tolerance to published Sama et al. 2025 results for the matching genotype and root ID.
• Root ID, genotype, and axis definition from workspace metadata match the cdf file provenance and article supplementary documentation.
• No NaN or inf values appear in per-root metrics; pixel counts and axis lengths are consistent between cdf dimensions and workspace definitions.
• Aggregated outputs from all three Oaxacan Green roots (OG1, OG5, OG2-P11-0) can be compared side-by-side without schema or dimension mismatches.

Limitations

• Workspace file structure and variable names are pipeline-specific; incorrect or outdated workspace files will silently produce misaligned analysis.
• No built-in version control for workspace metadata; if workspace was created with a different DIMPLE version, results may diverge from published outputs.
• README does not document workspace variable schema or provide checksums; manual inspection of loaded data is required to confirm integrity.
• Third Oaxacan Green root (OG2-P11-0) workspace file not explicitly mentioned in README — may not be available or may require separate acquisition.

Evidence

• [readme] cdf files and available Matlab workspaces are provided for the roots that were analyzed in Sama et al. 2025.: "cdf files and available Matlab workspaces are provided for the roots that were analyzed in Sama et al. 2025."
• [other] Load the cdf files and workspace data into Matlab using the DIMPLE pipeline environment.: "Load the cdf files and workspace data into Matlab using the DIMPLE pipeline environment."
• [other] Execute the DIMPLE linear-axis analysis workflow on each root dataset to compute per-root mass spectrometry imaging metrics along the linear axis.: "Execute the DIMPLE linear-axis analysis workflow on each root dataset to compute per-root mass spectrometry imaging metrics along the linear axis."
• [other] Aggregate and validate the three per-root outputs to confirm they match the reported Oaxacan Green genotype results.: "Aggregate and validate the three per-root outputs to confirm they match the reported Oaxacan Green genotype results."
• [readme] batchcdfread function developed by Yifan Meng in Dr. Richard N. Zare's lab at Stanford University: "batchcdfread function developed by Yifan Meng in Dr. Richard N. Zare's lab at Stanford University"