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.


Reference manual

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0.1.0 by Jan-Philipp Quast, 16 days ago,

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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