
MSqRob : analysis of label-free proteomics data in an R/Shiny environment
- Author
- Ludger Goeminne, Kris Gevaert (UGent) and Lieven Clement (UGent)
- Organization
- Keywords
- MSqRob, R, Shiny, statistics, biostatistics, data analysis, differential protein abundance, label-free quantification, differential proteomics, peptide-based linear model, robust ridge regression, M estimation, Huber weights, empirical Bayes variance estimation, tandem mass spectrometry, overfitting, outliers, missing values
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presentation Eubic Winter School 2017 3.pdf
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poster Eubic Ludger.pdf
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-8616173
- MLA
- Goeminne, Ludger, et al. “MSqRob : Analysis of Label-Free Proteomics Data in an R/Shiny Environment.” EuBIC Winter School, Abstracts, 2017.
- APA
- Goeminne, L., Gevaert, K., & Clement, L. (2017). MSqRob : analysis of label-free proteomics data in an R/Shiny environment. EuBIC Winter School, Abstracts. Presented at the 2017 EuBIC Winter School, Semmering, Austria.
- Chicago author-date
- Goeminne, Ludger, Kris Gevaert, and Lieven Clement. 2017. “MSqRob : Analysis of Label-Free Proteomics Data in an R/Shiny Environment.” In EuBIC Winter School, Abstracts.
- Chicago author-date (all authors)
- Goeminne, Ludger, Kris Gevaert, and Lieven Clement. 2017. “MSqRob : Analysis of Label-Free Proteomics Data in an R/Shiny Environment.” In EuBIC Winter School, Abstracts.
- Vancouver
- 1.Goeminne L, Gevaert K, Clement L. MSqRob : analysis of label-free proteomics data in an R/Shiny environment. In: EuBIC Winter School, Abstracts. 2017.
- IEEE
- [1]L. Goeminne, K. Gevaert, and L. Clement, “MSqRob : analysis of label-free proteomics data in an R/Shiny environment,” in EuBIC Winter School, Abstracts, Semmering, Austria, 2017.
@inproceedings{8616173, author = {{Goeminne, Ludger and Gevaert, Kris and Clement, Lieven}}, booktitle = {{EuBIC Winter School, Abstracts}}, keywords = {{MSqRob,R,Shiny,statistics,biostatistics,data analysis,differential protein abundance,label-free quantification,differential proteomics,peptide-based linear model,robust ridge regression,M estimation,Huber weights,empirical Bayes variance estimation,tandem mass spectrometry,overfitting,outliers,missing values}}, language = {{eng}}, location = {{Semmering, Austria}}, title = {{MSqRob : analysis of label-free proteomics data in an R/Shiny environment}}, year = {{2017}}, }