ArticleBMC bioinformatics2021
OmicLoupe: facilitating biological discovery by interactive exploration of multiple omic datasets and statistical comparisons.
Article in BMC bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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Who cites it
12 citing papers in PubMed, 20 citations in OpenAlex.
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- The CHCHD2-CHCHD10 protein complex is modulated by mitochondrial dysfunction and alters lipid homeostasis in the mouse brain.Cell death & disease · 2025Article
- The Carba Mix-In Vitro Investigations of Potential Cocktail Effects in Patch Tests With Rubber Allergens.Contact dermatitis · 2025Article
- Sexual dimorphism in zebrafish liver proteins and implications for hepatic regeneration and diseases.Scientific reports · 2025Article
- In vitro characterisation of a novel rubber contact allergen in protective gloves.Contact dermatitis · 2025Article
- The quantification of zebrafish ocular-associated proteins provides hints for sex-biased visual impairments and perception.Heliyon · 2024Article
- Linear epitopes of bony fish β-parvalbumins.Frontiers in immunology · 2024Article
- A proteomics dataset capturing myeloid cell responses upon cellular exposure to fungicides, adjuvants and fungicide formulations.Data in brief · 2023Article
- OmicLoupe: facilitating biological discovery by interactive exploration of multiple omic datasets and statistical comparisons.BMC bioinformatics · 2021Article
- ggVolcanoR: A Shiny app for customizable visualization of differential expression datasets.Computational and structural biotechnology journal · 2021Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
backgroundVisual exploration of gene product behavior across multiple omic datasets can pinpoint technical limitations in data and reveal biological trends. Still, such exploration is challenging as there is a need for visualizations that are tailored for the purpose.
resultsThe OmicLoupe software was developed to facilitate visual data exploration and provides more than 15 interactive cross-dataset visualizations for omics data. It expands visualizations to multiple datasets for quality control, statistical comparisons and overlap and correlation analyses, while allowing for rapid inspection and downloading of selected features. The usage of OmicLoupe is demonstrated in three different studies, where it allowed for detection of both technical data limitations and biological trends across different omic layers. An example is an analysis of SARS-CoV-2 infection based on two previously published studies, where OmicLoupe facilitated the identification of gene products with consistent expression changes across datasets at both the transcript and protein levels.
conclusionsOmicLoupe provides fast exploration of omics data with tailored visualizations for comparisons within and across data layers. The interactive visualizations are highly informative and are expected to be useful in various analyses of both newly generated and previously published data. OmicLoupe is available at quantitativeproteomics.org/omicloupe.
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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.