Tutorial contents · Applies to: 0.1.65
Visual guide: the route through this chapter
Wait until the R environment is ready. Choose the untargeted workflow, enter a recognizable name, and select a writable parent folder. After importing files, compare the displayed sample count against your sample sheet before advancing to peak detection.
Install on macOS
Open the TidyMass DMG, drag TidyMass to Applications, and open it there. Wait for the R environment check to finish. This guide targets the 0.1.65 Apple Silicon preview. A public installer link has not yet been verified; use the preview installer supplied by the project maintainers and check the version shown in the app. An Intel Mac build is not documented here.
The app includes R and its core packages. You do not need to install R separately for the core workflow. Optional third-party Shiny tools can require additional packages or system libraries.
The preview may be unsigned or unnotarized. If macOS blocks it, verify its source and use the system’s Privacy & Security prompt to allow that app. Do not disable system-wide security checks.
Create a project
- Open Workflows and choose the untargeted metabolomics workflow.
- Enter a project name. Click Choose location & create and choose a parent folder.
- In Data import, select mzML/mzXML files and, preferably, sample information.
- Check sample IDs and groups, then import the files.
- Continue to Raw data processing.
Use a new project folder. Reopen an existing project with Projects or Open project, selecting the folder containing project.json.
Find your way around
| Entry | Purpose |
|---|---|
| Workflows | Run a complete analysis in order |
| Analysis tools | Run an individual analysis or preparation tool |
| Shiny tools | Install and open third-party Shiny apps |
| R environment | Inspect R and manage additional packages |
| Code | Read execution code and records |
| Task center | Inspect the current R task, logs, memory and task history |
| Show settings / Hide settings | Expand or collapse parameters |
A project holds analysis records; a run is one execution; a feature is a detected signal, not automatically an identified compound. Changing parameters affects a new run. Use Settings used for this result to inspect how a saved result was produced.
TidyMass used, Computer used and Computer total report different memory quantities. A high system total is not necessarily caused by this app. After your first run, verify sample counts, missingness, peak shapes and warnings. A completed task confirms execution, not scientific validity.
Walkthrough: Read a saved workflow result
- Read the left-hand stage list first. The selected stage is Data exploration; Data cleaning is marked Stale because its upstream input changed. Blocked stages still lack an eligible input.
- In Displayed dataset, check the run identifier, Samples, Features and Missing values. Here 7 of 24 cells are missing, giving 29.17%; this is a matrix-cell percentage, not the percentage of completely missing samples.
- Select a saved run and expand Settings used for this result. Compare saved results only after checking that their input and parameters answer the same question.
- After checking the result, rerun stale dependent stages in order. If a stage fails, inspect its first error before changing parameters or repeating the task.