# tidymass **Repository Path**: jaspershen/tidymass ## Basic Information - **Project Name**: tidymass - **Description**: No description available - **Primary Language**: R - **License**: MIT - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2022-02-20 - **Last Updated**: 2022-09-16 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README ## `tidymass`: An R package to organize all the packages in tidyMass project [![](https://www.r-pkg.org/badges/version/tidymass?color=green)](https://cran.r-project.org/package=tidymass) [![](https://img.shields.io/github/languages/code-size/tidymass/tidymass.svg)](https://github.com/tidymass/tidymass) [![Dependencies](https://tinyverse.netlify.com/badge/tidymass)](https://cran.r-project.org/package=tidymass) [![](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://www.tidyverse.org/lifecycle/#experimental) `tidymass` is a part of [tidymass project](https://www.tidymass.org/). # **About** `tidymass` is a R package which is used to manage and organize all the pacakges in [tidyMass project](https://www.tidymass.org/) # **Installation** You can install `tidymass` from [GitLab](https://gitlab.com/jaspershen/tidymass) ``` r if(!require(remotes)){ install.packages("remotes") } remotes::install_gitlab("jaspershen/tidymass") ``` or [GitHub](https://github.com/tidymass/tidymass) ``` r remotes::install_github("tidymass/tidymass") ``` # **Usage** Please see the `Help documents` page to get the instruction of `tidymass`. # **Need help?** If you have any quesitions about `tidymass`, please don’t hesitate to email me (). [shenzutao1990](https://www.shenxt.info/files/wechat_QR.jpg) [Twitter](https://twitter.com/JasperShen1990) [M339, Alway building, Cooper Lane, Palo Alto, CA 94304](https://www.google.com/maps/place/Alway+Building/@37.4322345,-122.1770883,17z/data=!3m1!4b1!4m5!3m4!1s0x808fa4d335c3be37:0x9057931f3b312c29!8m2!3d37.4322345!4d-122.1748996) # **Citation** If you use `tidymass` in your publications, please cite this paper: Shen, X., Yan, H., Wang, C. et al. TidyMass an object-oriented reproducible analysis framework for LC–MS data. Nat Commun 13, 4365 (2022). [Weblink](https://www.nature.com/articles/s41467-022-32155-w) Thanks very much!