Bottom-Up Proteomics and LiP-MS Quality Control and Data Analysis Tools

Useful functions and workflows for proteomics quality control and data analysis of both limited proteolysis-coupled mass spectrometry (LiP-MS) (Schopper et al. (2017) ) and regular bottom-up proteomics experiments. Data generated with search tools such as 'Spectronaut', 'MaxQuant' and 'Proteome Discover' can be easily used due to flexibility of functions.


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install.packages("protti")

0.1.0 by Jan-Philipp Quast, 16 days ago


https://github.com/jpquast/protti, https://jpquast.github.io/protti/


Report a bug at https://github.com/jpquast/protti/issues


Browse source code at https://github.com/cran/protti


Authors: Jan-Philipp Quast [aut, cre] , Dina Schuster [aut] , ETH Zurich [cph, fnd]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports rlang, dplyr, stringr, magrittr, data.table, janitor, progress, purrr, tidyr, ggplot2, forcats, tibble, plotly, ggrepel, methods, utils, grDevices

Suggests testthat, covr, knitr, rmarkdown, proDA, limma, dendextend, pheatmap, heatmaply, viridis, iq, furrr, future, parallel, seriation, drc, naniar, httr, igraph, stringi, STRINGdb


See at CRAN