ArticleBioinformatics (Oxford, England)2011
Improved quality control processing of peptide-centric LC-MS proteomics data.
Article in Bioinformatics (Oxford, England), 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 78 papers, 1 of them a synthesis that pooled it.
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Who cites it
78 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- Persistent urinary metabolic signatures in children with type 1 diabetes.Next research · 2025Article
- Islet-intrinsic sex differences in inflammatory signaling contribute to autoimmune diabetes susceptibility.bioRxiv : the preprint server for biology · 2025Article
- QSample: An Automated System for Rapid Monitoring of Quality Indicators in Proteomics Samples.Journal of proteome research · 2025Article
- Multi-Omic Profiling Identifies Conserved Metabolic Pathways Critical for SARS-CoV-2 Variants Infection.bioRxiv : the preprint server for biology · 2025Article
- Proteomic characterization ofmSystems · 2025Article
- Lipidomics Reveals Cell Specific Changes During Pluripotent Differentiation to Neural and Mesodermal Lineages.bioRxiv : the preprint server for biology · 2025Article
- Multi-platform omics analysis of Nipah virus infection reveals viral glycoprotein modulation of mitochondria.Cell reports · 2025Article
- Advanced multi-modal mass spectrometry imaging reveals functional differences of placental villous compartments at microscale resolution.Nature communications · 2025Article
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- iDIA-QC: AI-empowered data-independent acquisition mass spectrometry-based quality control.Nature communications · 2025Article
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- Conditional knockout of C/EBPβ in epidermis results in dysregulated lipid biosynthesis and a defect in skin barrier function.PloS one · 2025Article
- Deciphering ApoE Genotype-Driven Proteomic and Lipidomic Alterations in Alzheimer's Disease Across Distinct Brain Regions.Journal of proteome research · 2024Article
- A compendium of multi-omics data illuminating host responses to lethal human virus infections.Scientific data · 2024Article
- The spatially resolved transcriptome signatures of glomeruli in chronic kidney disease.JCI insight · 2024Article
- New Pathophysiological Insights from Serum Proteome Profiling in Equine Atypical Myopathy.ACS omega · 2024Article
18 more citing papers are in PubMed but not listed here.
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8 authors.
Funding
Abstract
motivationIn the analysis of differential peptide peak intensities (i.e. abundance measures), LC-MS analyses with poor quality peptide abundance data can bias downstream statistical analyses and hence the biological interpretation for an otherwise high-quality dataset. Although considerable effort has been placed on assuring the quality of the peptide identification with respect to spectral processing, to date quality assessment of the subsequent peptide abundance data matrix has been limited to a subjective visual inspection of run-by-run correlation or individual peptide components. Identifying statistical outliers is a critical step in the processing of proteomics data as many of the downstream statistical analyses [e.g. analysis of variance (ANOVA)] rely upon accurate estimates of sample variance, and their results are influenced by extreme values.
resultsWe describe a novel multivariate statistical strategy for the identification of LC-MS runs with extreme peptide abundance distributions. Comparison with current method (run-by-run correlation) demonstrates a significantly better rate of identification of outlier runs by the multivariate strategy. Simulation studies also suggest that this strategy significantly outperforms correlation alone in the identification of statistically extreme liquid chromatography-mass spectrometry (LC-MS) runs. AVAILABILITY: https://www.biopilot.org/docs/Software/RMD.php CONTACT: bj@pnl.gov SUPPLEMENTARY INFORMATION: Supplementary material is available at Bioinformatics online.
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