Feature Annotation & Library Matching (MZmine/MS-DIAL/GNPS) — Hands-on

Move beyond anonymous m/z features and start naming chemistry with confidence. This module focuses on practical feature annotation strategies, spectral library matching in MZmine/MS-DIAL, and GNPS molecular networking so that your untargeted metabolomics datasets yield interpretable metabolite IDs with documented confidence levels.

Feature Annotation & Library Matching (MZmine/MS-DIAL/GNPS)

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Session Index

Session 1 — Annotation Concepts & Confidence Levels (MSI) Session 2 — Library Matching in MZmine / MS-DIAL Session 3 — GNPS, Molecular Networking & Library Workflows Session 4 — Mini Capstone: Annotation Workflow & ID Table

Session 1

Fee: Rs 8800

Annotation Concepts & Confidence Levels (MSI)

From feature tables to putative IDs — the annotation problem

m/z & RT to candidate lists MS/MS evidence in-silico vs experimental spectra

Metabolomics Standards Initiative (MSI) levels of identification

Level 1: confirmed ID Levels 2–3: putative ID / class Level 4: unknown features

Evidence types: accurate mass, RT, MS/MS, isotopes & adducts

mass error and ppm windows RT matching to standards fragmentation pattern similarity

Session 2

Fee: Rs 11800

Library Matching in MZmine / MS-DIAL

Preparing feature lists and MS/MS spectra for matching

export from peak picking pipelines linking MS1 features to MS/MS scans data formats for MZmine/MS-DIAL

Spectral library search settings and score interpretation

mass tolerances (MS1/MS2) similarity scores (dot product, cosine) minimum matched peaks / intensity

Working with public and in-house libraries (concepts)

MassBank / HMDB / MoNA (overview) importing custom libraries curating and updating reference sets

Session 3

Fee: Rs 14800

GNPS, Molecular Networking & Library Workflows

Preparing and submitting data to GNPS (concepts & workflow)

MS/MS spectra export metadata tables choosing GNPS workflows

Classical and feature-based molecular networking interpretation

cosine score & network edges cluster and subnetwork exploration propagating annotations to neighbors

GNPS library matches and chemical class-level insights

viewing library hits on networks chemical class/ontology layers unknown clusters and follow-ups

Session 4

Fee: Rs 18800

Mini Capstone: Annotation Workflow & ID Table

Running an end-to-end annotation workflow on example data

Theory + Practical

Consolidating MZmine/MS-DIAL/GNPS hits into a single ID table

merging feature IDs choosing best candidate per feature flagging conflicts and unknowns

Deliverables: annotation table with MSI levels & evidence columns

feature-to-metabolite table (CSV/TSV) MSI level & evidence documentation short methods and limitations note

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Feature Annotation & Library Matching (MZmine/MS-DIAL/GNPS) Training | Metabolite ID & MSI Confidence

Feature Annotation & Library Matching (MZmine/MS-DIAL/GNPS) — Hands-on