ArticleScientific reports2017
Enhanced differential expression statistics for data-independent acquisition proteomics.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
What it found
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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.
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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.
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Who cites it
40 citing papers in PubMed.
- Differential protein expression analysis of quantitative mass spectrometry data using DEqMS.Nature protocols · 2026Review
- Interleukin-1α Mediates Pancreatic Fibroblast Activation, Regulates Immune Cell Recruitment and Fibrosis in Acute and Chronic Pancreatitis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- IL-4/STAT6-signaling Influences Local Inflammation and Regeneration Processes During Acute Pancreatitis and Promotes Fibrosis by a Direct Activation of Pancreatic Fibroblasts During Chronic Pancreatitis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Genomic and functional characterization of the L‑sorbose phosphotransferase system in high-riskmSystems · 2026Article
- Streptococcus pneumoniae adaptation to nutrient deprivation and immune modulation drives upper respiratory tract colonization.The ISME journal · 2026Article
- Unraveling proteomic chaos by independent component analysis-ClpX proficiency promotes the iron and oxygen limitation responses ofmSystems · 2025Article
- Sex-Specific Differences in the Secretome of Oligodendrocyte Progenitor Cells Post Hyperoxic Stress.Journal of extracellular biology · 2025Article
- Linking Virulence and Iron Limitation Response inJournal of proteome research · 2025Article
- The ClpXP protease and the ClpX unfoldase control virulence, cell division, and autolysis inMicrobiology spectrum · 2025Article
- A Proteomic Signature for Human Papillomavirus-Associated Oropharyngeal Squamous Cell Carcinoma Predicts Patients at High Risk of Recurrence.Cancer research communications · 2025Article
- SpectroPipeR-a streamlining post Spectronaut® DIA-MS data analysis R package.Bioinformatics (Oxford, England) · 2025Article
- Requirement of ClpX for CtsR dissociation from its operator elements upon heat stress inFrontiers in microbiology · 2025Article
- Global quantitative proteome analysis of a multi-resistantFrontiers in microbiology · 2025Article
- Integrated genomic and proteomic analysis of the mouse-adaptedCurrent research in microbial sciences · 2025Article
- Multi-omics investigation reveals unique markers inFrontiers in microbiology · 2025Article
- The global proteome ofFrontiers in cellular and infection microbiology · 2025Article
- Identification of Protein Networks and Biological Pathways Driving the Progression of Atherosclerosis in Human Carotid Arteries Through Mass Spectrometry-Based Proteomics.International journal of molecular sciences · 2024Article
- Functional and Proteomic Dissection of the Contributions of CodY, SigB and the Hibernation Promoting Factor HPF to Interactions ofJournal of proteome research · 2024Article
- Statistical Testing for Protein Equivalence Identifies Core Functional Modules Conserved across 360 Cancer Cell Lines and Presents a General Approach to Investigating Biological Systems.Journal of proteome research · 2024Article
- Optimizing differential expression analysis for proteomics data via high-performing rules and ensemble inference.Nature communications · 2024Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
We describe a new reproducibility-optimization method ROPECA for statistical analysis of proteomics data with a specific focus on the emerging data-independent acquisition (DIA) mass spectrometry technology. ROPECA optimizes the reproducibility of statistical testing on peptide-level and aggregates the peptide-level changes to determine differential protein-level expression. Using a 'gold standard' spike-in data and a hybrid proteome benchmark data we show the competitive performance of ROPECA over conventional protein-based analysis as well as state-of-the-art peptide-based tools especially in DIA data with consistent peptide measurements. Furthermore, we also demonstrate the improved accuracy of our method in clinical studies using proteomics data from a longitudinal human twin study.
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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.