Spectrus: Best practices for importing large xC/UV/MS datasets without crashes

Description
Very large datasets (for example, long xC/UV/MS sequences, or folders with hundreds of raw data files) can stress memory and I/O when imported naively into Spectrus. Adopting a structured import strategy reduces the risk of application instability.

Solution

1. Plan your import:
   • Decide which runs you actually need to analyze in detail (e.g., only standards and key samples).
   • Avoid importing unnecessary blanks, failed runs, or test injections unless needed.
2. Use the Open Data panel and filter:
   • Navigate to the vendor data folder and select only a realistic subset of files.
   • Start with key standards and a few representative samples.
3. Configure import dialog:
   • Turn off options that greatly multiply the number of traces (e.g., detailed MSn splitting) if not needed.
   • Avoid enabling “Don’t show me again” for complex import options until you confirm suitable settings.
4. Import stepwise:
   • Import a subset, process and save, then close unneeded documents before adding the next subset.
5. If you reach resource limits:
   • Spectrus should ideally warn or refuse to open additional files; if your version shows low‑level errors instead, restart the session and reduce the batch size.
6. For long‑term workflows:
   • Standardize an internal guideline: for example, “Do not import more than X xC/UV/MS runs in a single Spectrus session,” adjusted based on RAM and dataset size.