LIPID MAPS Statistical Analysis Tools logo

LIPID MAPS Statistical Analysis Tools

Statistical Analysis Tools for User-Uploaded Data

Description

A set of online tools to enable users to perform data processing, normalization, statistical analysis and functional analysis, meta-analysis on user-supplied datasets. The input format is a table of lipid annotations and sample measurements, including a row/column which groups the samples based on experimental criteria (control, disease, treated, timepoint, etc.) The objective is to enable user-friendly high-throughput analysis for both targeted and untargeted lipidomics in order to gain biological insights. Analysis options include: sample normalization, analyte scaling, plotting, univariate analysis (Volcano plots and ANOVA analysis),clustering and correlation, multivariate analysis (PCA, LDA), classification/feature analysis (Random-Forest, OPLS-DA). Metabolite names are automatically standardized to RefMet equivalents enabling metabolite class enrichment analysis approaches.

Technical Information

Reference:
None
Documentation and user guide:
None
Download / Web-service link:
Yes
Source code repository:
Standard R packages
Programming languages:
R,
PHP,
JavaScript
Platforms:
Windows,
Linux,
MacOS
Output formats:
HTML,
PDF
Input formats:
Text
Web platform:
Yes
Desktop client:
No
CLI:
No
GUI:
Yes
License:
GPL (Academic)

Tasks

6) Analysis and visualization of lipidomics data
Direct connection to identification results:
Yes
Classification and feature selection:
Random Forest
Clustering and correlation analysis methods:
Cim_network.R,
Hclust
Feature identification:
No
Supervised multivariate statistical analysis methods:
LDA,
O-PLS-DA/VIP analysis
Unsupervised multivariate statistical analysis methods:
PCA
Univariate statistical analysis methods:
ANOVA,
Fold-change analysis
Missing data handling:
R-based methods
Data pre-treatments:
Normalization,
Scaling