ArticleJournal of proteomics2015
QPROT: Statistical method for testing differential expression using protein-level intensity data in label-free quantitative proteomics.
Article in Journal of proteomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 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
41 citing papers in PubMed.
- Context-dependent interplay of Swi-Snf and Tup1-Cyc8 influences chromatin and transcription at antagonistically regulated genes.Nature communications · 2026Article
- Integrative Structural Modeling of Intrinsically Disordered Regions in a Human HDAC2 Chromatin Remodeling Complex.bioRxiv : the preprint server for biology · 2026Article
- A proximity labeling approach to identify proteins that associate with synaptonemal complex components inbioRxiv : the preprint server for biology · 2025Article
- RAP proteins regulate apicoplast noncoding RNA processing in Plasmodium falciparum.Cell reports · 2025Article
- Integrative approaches for predicting protein network perturbations through machine learning and structural characterization.Journal of proteomics · 2025Article
- Article
- Article
- Distinct Regions within SAP25 Recruit O-Linked Glycosylation, DNA Demethylation, and Ubiquitin Ligase and Hydrolase Activities to the Sin3/HDAC Complex.Journal of proteome research · 2024Article
- A kalihinol analog disrupts apicoplast function and vesicular trafficking inScience (New York, N.Y.) · 2024Article
- Article
- Proteome-Wide Identification of RNA-dependent proteins and an emerging role for RNAs in Plasmodium falciparum protein complexes.Nature communications · 2024Article
- Statistical normalization methods in microbiome data with application to microbiome cancer research.Gut microbes · 2023Review
- Lineage specific extracellular vesicle-associated protein biomarkers for the early detection of high grade serous ovarian cancer.Scientific reports · 2023Article
- An rRNA fragment in extracellular vesicles secreted by human airway epithelial cells increases the fluoroquinolone sensitivity ofAmerican journal of physiology. Lung cellular and molecular physiology · 2023Article
- Paraspeckles interact with SWI/SNF subunit ARID1B to regulate transcription and splicing.EMBO reports · 2023Article
- Identification of small extracellular vesicle protein biomarkers for pediatric Ewing Sarcoma.Frontiers in molecular biosciences · 2023Article
- Adaptations to high pressure of Nautilia sp. strain PV-1, a piezophilic Campylobacterium (aka Epsilonproteobacterium) isolated from a deep-sea hydrothermal vent.Environmental microbiology · 2022Article
- Structural basis of the interaction between SETD2 methyltransferase and hnRNP L paralogs for governing co-transcriptional splicing.Nature communications · 2021Article
- Subzero, saline incubations of Colwellia psychrerythraea reveal strategies and biomarkers for sustained life in extreme icy environments.Environmental microbiology · 2021Article
- Proteomic Identification ofInternational journal of molecular sciences · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
We introduce QPROT, a statistical framework and computational tool for differential protein expression analysis using protein intensity data. QPROT is an extension of the QSPEC suite, originally developed for spectral count data, adapted for the analysis using continuously measured protein-level intensity data. QPROT offers a new intensity normalization procedure and model-based differential expression analysis, both of which account for missing data. Determination of differential expression of each protein is based on the standardized Z-statistic based on the posterior distribution of the log fold change parameter, guided by the false discovery rate estimated by a well-known Empirical Bayes method. We evaluated the classification performance of QPROT using the quantification calibration data from the clinical proteomic technology assessment for cancer (CPTAC) study and a recently published Escherichia coli benchmark dataset, with evaluation of FDR accuracy in the latter. BIOLOGICAL SIGNIFICANCE: QPROT is a statistical framework with computational software tool for comparative quantitative proteomics analysis. It features various extensions of QSPEC method originally built for spectral count data analysis, including probabilistic treatment of missing values in protein intensity data. With the increasing popularity of label-free quantitative proteomics data, the proposed method and accompanying software suite will be immediately useful for many proteomics laboratories. This article is part of a Special Issue entitled: Computational Proteomics.
Indexed as
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.