Expanding the proteomics and metabolomics toolkit with methods for differential expression analysis from transcriptomics

Simple item page
dc.contributor.authorDohm-Hansen, Sebastianen
dc.contributor.authorCaruso, Maria Giovannaen
dc.contributor.authorNicolas, Sarahen
dc.contributor.authorScaife, Caitrionaen
dc.contributor.authorO’Leary, Olivia F.en
dc.contributor.authorLavelle, Aonghusen
dc.contributor.authorEnglish, Jane A.en
dc.contributor.funderScience Foundation Irelanden
dc.contributor.funderHealth Research Boarden
dc.date.accessioned2026-03-23T14:45:12Z
dc.date.available2026-03-23T14:45:12Z
dc.date.issued2026-02-06
dc.description.abstractWith the increasing adoption of discovery -omics in the life sciences, a large number of analysis tools for differential expression analysis (DEA) have been introduced over the years. While such tools tend to be developed with one particular -omics modality in mind, they can often be applied across technologies to solve common issues. This is particularly the case when -omics data share statistical and distributional properties. Herein, we showcase how tools originally developed for transcriptomics analysis are especially well-suited to solving problems in discovery proteomics and metabolomics. Using data from our own experimental work as examples of real-world implementation, we demonstrate how these methods can be used to tackle common DEA issues, such as variable sample quality, hidden batch effects, normalization, and small sample size. We believe this can be useful to novices and seasoned practitioners alike by expanding their toolkits. As multiomic and integrative analyses become commonplace, it is especially useful to capitalize on the similarities of otherwise different -omics.en
dc.description.sponsorshipHealth Research Board (Grant no. HRB EIA-2017-023)en
dc.description.statusPeer revieweden
dc.description.versionAccepted Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationDohm-Hansen, S., Caruso, M.G., Nicolas, S., Scaife, C., O’Leary, O.F., Nolan, Y.M., Lavelle, A. and English, J.A. (2026) 'Expanding the proteomics and metabolomics toolkit with methods for differential expression analysis from transcriptomics', Journal of Proteome Research, 25(3), pp. 1253–1264. https://doi.org/10.1021/acs.jproteome.5c00719en
dc.identifier.doi10.1021/acs.jproteome.5c00719en
dc.identifier.eissn1535-3907en
dc.identifier.endpage1264en
dc.identifier.issn1535-3893en
dc.identifier.issued3en
dc.identifier.journaltitleJournal of Proteome Researchen
dc.identifier.startpage1253en
dc.identifier.urihttps://hdl.handle.net/10468/18643
dc.identifier.volume25en
dc.language.isoen
dc.publisherAmerican Chemical Society
dc.relation.projectinfo:eu-repo/grantAgreement/SFI/Frontiers for the Futureen
dc.rights© 2026, the Authors. Published by American Chemical Society.en
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subjectDifferential expression analysisen
dc.subjectBioinformaticsen
dc.subjectProteomicsen
dc.subjectMetabolomicsen
dc.subjectTranscriptomicsen
dc.subjectMultiomicsen
dc.subjectNormalizationen
dc.subjectSample qualityen
dc.subjectBatch effectsen
dc.subject~Anatomy and Neuroscience - Journal Articles~en
dc.titleExpanding the proteomics and metabolomics toolkit with methods for differential expression analysis from transcriptomicsen
dc.typeArticle (peer-reviewed)en
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
dohmhansen et al jopr 2025 main manuscript resubmission.pdf
Size:
2 MB
Format:
Adobe Portable Document Format
Description:
Accepted Version
Download
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
2.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
School of Medicine