ArticleBioinformatics advances2025
LipidSigR: a R-based solution for integrated lipidomics data analysis and visualization.
Article in Bioinformatics advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- Article
- Exosomal Profiling Reveals Mechanisms of Hibernation-Associated Neuroprotection.bioRxiv : the preprint server for biology · 2026Article
- A Structured Computational Roadmap for Lipidomics in R: Reproducible Workflows from Raw Data to Functional Insight.Metabolites · 2026Review
- Integrated multiomics profiling of amniotic fluid exosomes reveals dysregulated lipid and protein signatures in fetal 22q11.2 deletion syndrome.Human genomics · 2026Article
- Article
- Plasma lipidomics and 15-year risk of incident diabetes: a coronary artery risk development in young adults study.Journal of lipid research · 2026Article
- Unlocking the power of extracellular vesicles: multi-omics integration for cancer biomarker discovery.Biomarker research · 2026Review
- Ether-lipids accumulation promotes hepatocellular carcinoma progression linked to PPARα deficiency.Journal of biomedical science · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Motivation: Lipidomics is a rapidly expanding field focused on studying lipid species and classes within biological systems. As the field evolves, there is an increasing demand for user-friendly, open-source software tools capable of handling large and complex datasets while keeping pace with technological advancements. LipidSig, a widely used web-based platform, has been instrumental in data analysis and visualization of lipidomics. However, its limitations become evident when users want to build customized workflows. To address the limitation, we developed a companion R package, LipidSigR, based on the R code of the LipidSig web platform. Results: LipidSigR offers greater flexibility, allowing researchers with basic R programming skills to modify and adapt workflows according to their needs. It has been rigorously tested following CRAN guidelines to ensure compatibility and reproducibility. In demonstrating its functionality, we analyze the case with commonly used experimental design, case versus control, in lipidomics studies. Researchers can follow the use case to explore the key capabilities and build customized lipidomics data analysis workflows using LipidSigR. Availability and implementation: LipidSigR is freely available from https://lipidsig.bioinfomics.org/lipidsigr/index.html and https://github.com/BioinfOMICS/LipidSigR.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.