ArticleJournal of proteomics & bioinformatics2019
Standardizing Proteomics Workflow for Liquid Chromatography-Mass Spectrometry: Technical and Statistical Considerations.
Article in Journal of proteomics & bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Protein biomarkers in pulmonary arterial hypertension: advances, clinical relevance, and translational challenges.Journal of translational medicine · 2025Review
- Proteomic Analysis of the Extracellular Matrix in the Porcine Adrenal Cortex.Journal of proteome research · 2025Article
- Proteomic profiling of the extracellular matrix in the human adrenal cortex.Matrix biology plus · 2024Article
- Novel FFPE proteomics method suggests prolactin induced protein as hormone induced cytoskeleton remodeling spatial biomarker.Communications biology · 2024Article
- A Fast-Tracking Sample Preparation Protocol for Proteomics of Formalin-Fixed Paraffin-Embedded Tumor Tissues.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Type 3 secretion system induced leukotriene B4 synthesis by leukocytes is actively inhibited by Yersinia pestis to evade early immune recognition.PLoS pathogens · 2024Article
- Increased expression of phosphodiesterase 4 in activated hepatic stellate cells promotes cytoskeleton remodeling and cell migration.The Journal of pathology · 2023Article
- Disruption of the mouse liver epitranscriptome by long-term aroclor 1260 exposure.Environmental toxicology and pharmacology · 2023Article
- Multiomics analysis of the impact of polychlorinated biphenyls on environmental liver disease in a mouse model.Environmental toxicology and pharmacology · 2022Article
- Proteomics and metabolic phenotyping define principal roles for the aryl hydrocarbon receptor in mouse liver.Acta pharmaceutica Sinica. B · 2021Article
- RawBeans: A Simple, Vendor-Independent, Raw-Data Quality-Control Tool.Journal of proteome research · 2021Article
- Microbiome data analysis with applications to pre-clinical studies using QIIME2: Statistical considerations.Genes & diseases · 2021Article
- Combined exposure to polychlorinated biphenyls and high-fat diet modifies the global epitranscriptomic landscape in mouse liver.Environmental epigenetics · 2021Article
- Protein Extraction From FFPE Kidney Tissue Samples: A Review of the Literature and Characterization of Techniques.Frontiers in medicine · 2021Article
- Proteomic Analysis Identifies Distinct Glomerular Extracellular Matrix in Collapsing Focal Segmental Glomerulosclerosis.Journal of the American Society of Nephrology : JASN · 2020Article
- Dioxin-like and non-dioxin-like PCBs differentially regulate the hepatic proteome and modify diet-induced nonalcoholic fatty liver disease severity.Medicinal chemistry research : an international journal for rapid communications on design and mechanisms of action of biologically active agents · 2020Article
- Interactive Web Tool for Standardizing Proteomics Workflow for Liquid Chromatography-Mass Spectrometry Data.Journal of proteomics & bioinformatics · 2019Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
introductionThe quantitative measurements based on liquid chromatography (LC) coupled with mass spectrometry (MS) often suffer from the problem of missing values and data heterogeneity from technical variability. We considered a proteomics data set generated from human kidney biopsy material to investigate the technical effects of sample preparation and the quantitative MS.
methodsWe studied the effect of tissue storage methods (TSMs) and tissue extraction methods (TEMs) on data analysis. There are two TSMs: frozen (FR) and FFPE (formalin-fixed paraffin embedded); and three TEMs: MAX, TX followed by MAX and SDS followed by MAX. We assessed the impact of different strategies to analyze the data while considering heterogeneity and MVs. We have used analysis of variance (ANOVA) model to study the effects due to various sources of variability. RESULTS AND
conclusionWe found that the FFPE TSM is better than the FR TSM. We also found that the one-step TEM (MAX) is better than those of two-steps TEMs. Furthermore, we found the imputation method is a better approach than excluding the proteins with MVs or using unbalanced design.
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