ArticleBioinformatics (Oxford, England)2022
ADViSELipidomics: a workflow for analyzing lipidomics data.
Article in Bioinformatics (Oxford, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed.
- LipidCruncher: an open-source platform for processing, visualizing, and analyzing lipidomic data.BMC bioinformatics · 2026Article
- Lipidomics in Melanoma: Insights into Disease Progression and Therapeutical Targets.International journal of molecular sciences · 2026Review
- Best practices and tools in R and Python for statistical processing and visualization of lipidomics and metabolomics data.Nature communications · 2025Review
- TEMI: tissue-expansion mass-spectrometry imaging.Nature methods · 2025Article
- Review
- From Lipid Signatures to Cellular Responses: Unraveling the Complexity of Melanoma and Furthering Its Diagnosis and Treatment.Medicina (Kaunas, Lithuania) · 2024Review
- Chemical and Pharmacological Prospection of the AscidianMarine drugs · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
summaryADViSELipidomics is a novel Shiny app for preprocessing, analyzing and visualizing lipidomics data. It handles the outputs from LipidSearch and LIQUID for lipid identification and quantification and the data from the Metabolomics Workbench. ADViSELipidomics extracts information by parsing lipid species (using LIPID MAPS classification) and, together with information available on the samples, performs several exploratory and statistical analyses. When the experiment includes internal lipid standards, ADViSELipidomics can normalize the data matrix, providing normalized concentration values per lipids and samples. Moreover, it identifies differentially abundant lipids in simple and complex experimental designs, dealing with batch effect correction. Finally, ADViSELipidomics has a user-friendly graphical user interface and supports an extensive series of interactive graphics. AVAILABILITY AND IMPLEMENTATION: ADViSELipidomics is freely available at https://github.com/ShinyFabio/ADViSELipidomics. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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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.