Literature DB >> 32227882

MSqRob Takes the Missing Hurdle: Uniting Intensity- and Count-Based Proteomics.

Ludger J E Goeminne1,2,3,4, Adriaan Sticker1,2,3,4, Lennart Martens2,3,4, Kris Gevaert2,3, Lieven Clement1,4.   

Abstract

Missing values are a major issue in quantitative data-dependent mass spectrometry-based proteomics. We therefore present an innovative solution to this key issue by introducing a hurdle model, which is a mixture between a binomial peptide count and a peptide intensity-based model component. It enables dramatically enhanced quantification of proteins with many missing values without having to resort to harmful assumptions for missingness. We demonstrate the superior performance of our method by comparing it with state-of-the-art methods in the field.

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Year:  2020        PMID: 32227882     DOI: 10.1021/acs.analchem.9b04375

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  5 in total

Review 1.  Challenges and Opportunities for Bayesian Statistics in Proteomics.

Authors:  Oliver M Crook; Chun-Wa Chung; Charlotte M Deane
Journal:  J Proteome Res       Date:  2022-03-08       Impact factor: 4.466

2.  Proteomic Assessment of C57BL/6 Hippocampi after Non-Selective Pharmacological Inhibition of Nitric Oxide Synthase Activity: Implications of Seizure-like Neuronal Hyperexcitability Followed by Tauopathy.

Authors:  Jhana O Hendrickx; Charlotte Adams; Anne Sieben; Kris Laukens; Debby Van Dam; Guido R Y De Meyer
Journal:  Biomedicines       Date:  2022-07-22

3.  A combined test for feature selection on sparse metaproteomics data-an alternative to missing value imputation.

Authors:  Sandra Plancade; Magali Berland; Mélisande Blein-Nicolas; Olivier Langella; Ariane Bassignani; Catherine Juste
Journal:  PeerJ       Date:  2022-06-24       Impact factor: 3.061

4.  Accounting for multiple imputation-induced variability for differential analysis in mass spectrometry-based label-free quantitative proteomics.

Authors:  Marie Chion; Christine Carapito; Frédéric Bertrand
Journal:  PLoS Comput Biol       Date:  2022-08-29       Impact factor: 4.779

5.  Comparative assessment and novel strategy on methods for imputing proteomics data.

Authors:  Minjie Shen; Yi-Tan Chang; Chiung-Ting Wu; Sarah J Parker; Georgia Saylor; Yizhi Wang; Guoqiang Yu; Jennifer E Van Eyk; Robert Clarke; David M Herrington; Yue Wang
Journal:  Sci Rep       Date:  2022-01-20       Impact factor: 4.379

  5 in total

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