Useful functions and workflows for proteomics quality control and data analysis of both limited proteolysis-coupled mass spectrometry (LiP-MS) (Feng et. al. (2014) <doi:10.1038/nbt.2999>) 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.
Version: 0.9.1 Depends: R (≥ 4.0) Imports: rlang, dplyr, stringr, magrittr, data.table, janitor, progress, purrr, tidyr, ggplot2, forcats, tibble, plotly, ggrepel, utils, grDevices, curl, readr, lifecycle, httr, methods, R.utils, stats Suggests: testthat, covr, knitr, rmarkdown, shiny, r3dmol, proDA, limma, dendextend, pheatmap, heatmaply, furrr, future, parallel, seriation, drc, igraph, stringi, STRINGdb, iq, scales, farver, ggforce, xml2, jsonlite Published: 2024-10-21 DOI: 10.32614/CRAN.package.protti Author: Jan-Philipp Quast [aut, cre], Dina Schuster [aut], ETH Zurich [cph, fnd] Maintainer: Jan-Philipp Quast <quast at imsb.biol.ethz.ch> BugReports: https://github.com/jpquast/protti/issues License: MIT + file LICENSE URL: https://github.com/jpquast/protti, https://jpquast.github.io/protti/ NeedsCompilation: no Citation: protti citation info Materials: README NEWS In views: Omics CRAN checks: protti results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=protti to link to this page.
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