
MS-DIAL
Data processing pipeline for untargeted lipidomics
Description
MS-DIAL is an open source software for untargeted metabolomics and lipidomics data. The current version 4 series supports GC-MS, GC-MS/MS, LC-MS (Full MS), LC-DDA, LC-DIA (SWATH & all ion fragmentation), LC-Ion mobility (IM)-DDA, and LC-IM-DIA. Lipid annotation is based on retention time (optional), CCS (optional), m/z, and MS/MS (recommended) using a hybrid scoring system of classical spectral matching algorithm and defined fragmentation rules for each lipid subclass. The program provides an all-in-one solution from data import of MS raw data until lipidome table export (such as mztab-M) and statistical analyses.
Technical Information
License:
LGPL v3 (code) / CC-BY-SA (software)
GUI:
Yes
CLI:
Yes
Desktop client:
Yes
Web platform:
No
Input formats:
.raw(Waters),
.raw(Thermo),
.wiff2(SCIEX),
.wiff(SCIEX),
.d(Bruker),
.d(Agilent),
ibf,
abf,
netCDF,
mzML
Output formats:
TSV
Platforms:
MacOS,
Linux,
Windows
Programming languages:
C#
Download / Web-service link:
Documentation and user guide:
Training datasets:
Publications:
PMID:32541957
Tasks
6)
Analysis and visualization of lipidomics data
Data pre-treatments:
Scaling,
Total ion count based (for relative intensity-based sample comparison),
Quality control sample’s profiles based (for LOWESS method),
An internal standard based (for relative intensity-based sample comparison),
Filtering by blank’s peaks
Missing data handling:
Yes
Univariate statistical analysis methods:
Fold-change analysis,
ANOVA
Unsupervised multivariate statistical analysis methods:
PCA
Supervised multivariate statistical analysis methods:
O-PLS-DA,
O-PLS,
PLS-DA,
PLS
Feature identification:
No
Clustering and correlation analysis methods:
HCA
Classification and feature selection:
OPLS-DA,
PLS-DA
Direct connection to identification results:
Yes
4.1)
Full MS (HRAM LC-MS)
4.2)
Data dependent acquisition (DDA)
4.3)
Data independent acquisition (DIA)
4.4)
Tools considering ion mobility separation
4.5)
Identification of oxidized lipids
5)
Lipid quantification from untargeted lipidomics datasets (HRAM MS, DDA, DIA)