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DAPAR & ProStaR: software to perform statistical analyses in quantitative discovery proteomics.
Bioinformatics. 2017 Jan 1;33(1):135-136. doi: 10.1093/bioinformatics/btw580. Epub 2016 Sep 6.
Bioinformatics. 2017.
PMID: 27605098
Free PMC article.
Protein-Level Statistical Analysis of Quantitative Label-Free Proteomics Data with ProStaR.
Wieczorek S, Combes F, Borges H, Burger T.
Wieczorek S, et al.
Methods Mol Biol. 2019;1959:225-246. doi: 10.1007/978-1-4939-9164-8_15.
Methods Mol Biol. 2019.
PMID: 30852826
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Statistical Analysis of Quantitative Peptidomics and Peptide-Level Proteomics Data with Prostar.
Tardif M, Fremy E, Hesse AM, Burger T, Couté Y, Wieczorek S.
Tardif M, et al. Among authors: wieczorek s.
Methods Mol Biol. 2023;2426:163-196. doi: 10.1007/978-1-0716-1967-4_9.
Methods Mol Biol. 2023.
PMID: 36308690
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Mass-spectrometry-based spatial proteomics data analysis using pRoloc and pRolocdata.
Gatto L, Breckels LM, Wieczorek S, Burger T, Lilley KS.
Gatto L, et al. Among authors: wieczorek s.
Bioinformatics. 2014 May 1;30(9):1322-4. doi: 10.1093/bioinformatics/btu013. Epub 2014 Jan 11.
Bioinformatics. 2014.
PMID: 24413670
Free PMC article.
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Five simple yet essential steps to correctly estimate the rate of false differentially abundant proteins in mass spectrometry analyses.
Wieczorek S, Giai Gianetto Q, Burger T.
Wieczorek S, et al.
J Proteomics. 2019 Sep 15;207:103441. doi: 10.1016/j.jprot.2019.103441. Epub 2019 Jul 10.
J Proteomics. 2019.
PMID: 31301518
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