ArticleBioinformatics (Oxford, England)2014
aLFQ: an R-package for estimating absolute protein quantities from label-free LC-MS/MS proteomics data.
Article in Bioinformatics (Oxford, England), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 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
30 citing papers in PubMed.
- PiProteline: An R Package for Integrated Proteomics Data Analysis, from Label-Free Quantitation to Systems Biology.Biology · 2026Article
- LysG-driven transcriptional network rewiring underlies lineage-specific phenotypes in Mycobacterium tuberculosis.Nature communications · 2026Article
- Article
- Median-Based Absolute Quantification of Proteins Using Fully Unlabeled Generic Internal Standard (FUGIS).Journal of proteome research · 2022Article
- Expression Dysregulation as a Mediator of Fitness Costs in Antibiotic Resistance.Antimicrobial agents and chemotherapy · 2021Article
- Diagnostics and correction of batch effects in large-scale proteomic studies: a tutorial.Molecular systems biology · 2021Review
- Data-independent acquisition-based proteome and phosphoproteome profiling across six melanoma cell lines reveals determinants of proteotypes.Molecular omics · 2021Article
- Advanced Fiber Type-Specific Protein Profiles Derived from Adult Murine Skeletal Muscle.Proteomes · 2021Article
- From coarse to fine: the absolute Escherichia coli proteome under diverse growth conditions.Molecular systems biology · 2021Article
- SECAT: Quantifying Protein Complex Dynamics across Cell States by Network-Centric Analysis of SEC-SWATH-MS Profiles.Cell systems · 2020Article
- Characterization of the Blood-Brain Barrier Integrity and the Brain Transport of SN-38 in an Orthotopic Xenograft Rat Model of Diffuse Intrinsic Pontine Glioma.Pharmaceutics · 2020Article
- A Global Screen for Assembly State Changes of the Mitotic Proteome by SEC-SWATH-MS.Cell systems · 2020Article
- Beyond Genes: Re-Identifiability of Proteomic Data and Its Implications for Personalized Medicine.Genes · 2019Review
- Generation of a zebrafish SWATH-MS spectral library to quantify 10,000 proteins.Scientific data · 2019Article
- AP-SWATH Reveals Direct Involvement of VCP/p97 in Integrated Stress Response Signaling Through Facilitating CReP/PPP1R15B Degradation.Molecular & cellular proteomics : MCP · 2018Article
- Systematic proteome and proteostasis profiling in human Trisomy 21 fibroblast cells.Nature communications · 2017Article
- Systems proteomics approaches to study bacterial pathogens: application to Mycobacterium tuberculosis.Current opinion in microbiology · 2017Review
- Multi-laboratory assessment of reproducibility, qualitative and quantitative performance of SWATH-mass spectrometry.Nature communications · 2017Article
- Comprehensive proteome analysis of human skeletal muscle in cachexia and sarcopenia: a pilot study.Journal of cachexia, sarcopenia and muscle · 2017Article
- Algorithms and design strategies towards automated glycoproteomics analysis.Mass spectrometry reviews · 2017Review
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
No grant is acknowledged in the PubMed record.
Abstract
motivationThe determination of absolute quantities of proteins in biological samples is necessary for multiple types of scientific inquiry. While relative quantification has been commonly used in proteomics, few proteomic datasets measuring absolute protein quantities have been reported to date. Various technologies have been applied using different types of input data, e.g. ion intensities or spectral counts, as well as different absolute normalization strategies. To date, a user-friendly and transparent software supporting large-scale absolute protein quantification has been lacking.
resultsWe present a bioinformatics tool, termed aLFQ, which supports the commonly used absolute label-free protein abundance estimation methods (TopN, iBAQ, APEX, NSAF and SCAMPI) for LC-MS/MS proteomics data, together with validation algorithms enabling automated data analysis and error estimation. AVAILABILITY AND IMPLEMENTATION: aLFQ is written in R and freely available under the GPLv3 from CRAN (http://www.cran.r-project.org). Instructions and example data are provided in the R-package. The raw data can be obtained from the PeptideAtlas raw data repository (PASS00321). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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.