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Authors
Charlotte Soneson (0000-0003-3833-2169), Vytautas Iesmantavicius (0000-0002-2512-9957), Daniel Hess (0000-0002-1642-5404), Michael B. Stadler (0000-0002-2269-4934), Jan Seebacher (0000-0002-7858-2720)
Citation
Soneson et al., (2023). einprot: flexible, easy-to-use, reproducible workflows for statistical analysis of quantitative proteomics data. Journal of Open Source Software, 8(89), 5750, https://doi.org/10.21105/joss.05750
@article{Soneson2023,
doi = {10.21105/joss.05750},
url = {https://doi.org/10.21105/joss.05750},
year = {2023},
publisher = {The Open Journal},
volume = {8},
number = {89},
pages = {5750},
author = {Charlotte Soneson and Vytautas Iesmantavicius and Daniel Hess and Michael B. Stadler and Jan Seebacher},
title = {einprot: flexible, easy-to-use, reproducible workflows for statistical analysis of quantitative proteomics data},
journal = {Journal of Open Source Software}
}
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This work is licensed under a Creative Commons Attribution 4.0 International License.
