Manual

Manual

Every manual page, grouped by stage of a post-processing project. Step-by-step worked examples are in the Tutorials, and the full argument reference for every function is in the function reference.

Getting started

• Installation — install mrmhub and load it.
• Key Concepts & Glossary — the data model, core terminology, and where QUANT fits in the MRMhub workflow.

Preparing and running

• Importing Analytical Data — choosing an importer and the file layout each one expects.
• Importing Metadata — attaching sample, feature, and internal-standard annotations.
• Drift and Batch Correction — correcting signal drift within runs and offsets between batches.

Results and downstream use

• Visualisation Functions — RunScatter, PCA, run-sequence, and normalization-QC plots.
• Writing Pipelines with AI Assistants — grounding LLMs (Claude, ChatGPT, local models) in the real API, and verifying what they produce.

Reference

• The MRMhubExperiment Data Object — the tables, identifiers, and feature variables of the central object.
• Design Decisions — why the package is built the way it is.
• Sample Types & QC Roles — every sample-type (qc_type) label and its role in QC.
• Troubleshooting & FAQ — frequent problems and how to resolve them.

See also

• Tutorials — worked, end-to-end examples
• Function reference — full arguments for every function
• INTEGRATOR documentation — upstream peak integration