lc-msms

LC-MS data processing tool for large-scale metabolomics experiments.

The MetaRbolomics book. A review of R packages in BioC, CRAN, gitlab and github.

Fast and Accurate CE-, GC- and LC-MS(/MS) Data Processing

AutoRT: Peptide retention time prediction using deep learning

R-package - Automated Evaluation of Precursor Ion Purity for Mass Spectrometry Based Fragmentation in Metabolomics

LipidHunter is capable to perform bottom up identification of lipids from LC-MS/MS and shotgun lipidomics data by resembling a workflow of manual spectra annotation. LipidHunter generates interactive HTML output with its unique six-panel-image, which provides an easy way to review, store, and share the identification results.

Python module for lipidomics LC MS/MS data analysis

Code, Data and Results of the publication: "Probabilistic Framework for Integration of Tandem-Mass Spectrum and Retention Time Information in Small Molecule Identification" by Bach et al. 2020

BMDMS-NP

High-throughput MS/MS annotation with a in-house database

MFQL files for Natural Products Dereplication

R package for annotation of glycans in MS1 and MS2 data

Python & R scripts collection for AdipoAtlas project

Extracts the features of peptide spectral library for better understanding and its efficient usage in DIA database search