<p>prolfqua – R-package for proteomics label-free quantification using linear models</p>

Witold Wolski; Christian Panse; Jonas Grossmann; Maria D'Errico; Paolo Nanni

doi:10.7490/f1000research.1118707.1

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Wolski W, Panse C, Grossmann J et al. prolfqua – R-package for proteomics label-free quantification using linear models [version 1; not peer reviewed]. F1000Research 2021, 10:740 (poster) (https://doi.org/10.7490/f1000research.1118707.1)

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prolfqua – R-package for proteomics label-free quantification using linear models

Witold Wolski¹, Christian Panse, Jonas Grossmann, Maria D'Errico, Paolo Nanni

Published 03 Aug 2021 (https://doi.org/10.7490/f1000research.1118707.1)

Author Affiliations

¹ Functional Genomics Center Zurich, Switzerland

Copyright © 2021 Wolski W et al. This is an open access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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CITE

Published 03 Aug 2021

prolfqua – R-package for proteomics label-free quantification using linear models
[version 1; not peer reviewed]

Witold Wolski¹, Christian Panse, Jonas Grossmann, Maria D'Errico, Paolo Nanni

Author Affiliations

¹ Functional Genomics Center Zurich, Switzerland

Presented at

Bioconductor Virtual Conference 2021

Abstract

Competing Interests

No competing interests were disclosed

Keywords

mass sectrometrcy, metabolomics, statistics, label free quantification, linear modelling, false discovery rate, benchmarking

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