Evidence map›Paper›PMID 42878753›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2027

Standardized Annotation of Quantitative Proteomics Datasets Using SDRF-Proteomics.

Lev Levitsky, Tine Claeys, Veit Schwämmle

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2027. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Lev LevitskyDepartment of Biochemistry and Molecular Biology, University of Southern Denmark, Odense M, Denmark.
Tine ClaeysVIB-UGent Center for Medical Biotechnology, VIB, Ghent, Belgium.
Veit SchwämmleDepartment of Biochemistry and Molecular Biology, University of Southern Denmark, Odense M, Denmark. veits@bmb.sdu.dk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Proteomics datasets require detailed and standardized metadata annotation to ensure reproducibility, reusability, and alignment with FAIR (Findable, Accessible, Interoperable, Reusable) principles. This chapter presents a practical, hands-on workflow for annotating a label-free proteomics dataset using the Sample and Data Relationship Format for Proteomics (SDRF-Proteomics), a HUPO-PSI and EuBIC-MS standard that has been adopted by major proteomics data repositories. We demonstrate the process on a COVID-19 nasal-swab dataset (PXD020394), showing how to derive sample and assay metadata from the study files, encode them in SDRF with the lesSDRF web application, and validate the result. Although the worked example is label-free, the approach can be generalized to other quantification strategies.

Indexed as

COVID-19ProteomicsDatabases, ProteinHumansMass SpectrometryMetadataSARS-CoV-2SoftwareWorkflowAnnotationCOVID-19FAIRlesSDRFMass spectrometryProteomicsSample metadataSDRF

Identifiers

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

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.