Statistical analysis

LipidSigR

Analyze lipid abundance changes and lipid characteristics in R.

LC-MSLipidomicsR packageOpen source

Overview

LipidSigR supports lipid profiling, differential analysis, enrichment, correlation and selected network or machine-learning workflows using processed lipidomics data.

What can this tool do?

Univariate statisticsMultivariate statisticsPathway enrichment

Common uses

  • Analyze lipid abundance changes and lipid characteristics in R.

Scientific fit

Primary function

Statistical analysis

Analysis types

Lipidomics

Data compatibility

Inputs

Feature or peak table, Sample metadata

Outputs

Statistical results, Human-readable report

Input formats

Processed lipid abundance and sample information in package input objects

Output formats

R analysis objects, result tables and visualizations

Scope and considerations

Designed for

  • LipidSigR supports lipid profiling, differential analysis, enrichment, correlation and selected network or machine-learning workflows using processed lipidomics data.

Not designed for

  • Raw LC-MS preprocessing or independent validation of lipid identities.

Important requirements

  • R 4.3 or later, package dependencies, lipid identifiers and a suitable study design.

Considerations

  • The documented network and machine-learning workflows are restricted to two-group data.
  • Results depend on lipid naming, preprocessing and study design; predictive models require appropriate validation.

Access and documentation

License checked against official repository/package metadata. Installation and execution were not tested.

License: MIT

Evidence and review

Enveda intake candidate checked against official documentation, license information and primary publication on 2026-10-21. Editorial review only; no execution or independent benchmark.

Core publications

Resource papers, direct updates and tool-specific methods. Selection policy.

  1. LipidSigR: a R-based solution for integrated lipidomics data analysis and visualization. Bioinformatics Advances (2025). doi:10.1093/bioadv/vbaf047

Related tools

Entry history

Changes to this catalogue entry, not the tool's software release history. Acceptance and editorial review are separate.

  1. 2026-10-21 · First committed entry

    Add nine reviewed Enveda tools and reconcile intake coverage

    View change · Entry at this revision

Full GitHub history