Install tidymass packages
Please make sure your internet is connected and stable.
And if you have any problems during the installation, please feel free to send email to us (shenxt1990@outlook.edu) or contact me via other social medias.
Update R version 🔗︎
tidymass require R version > 4.1.
You can check your R version in your console:
version
If your R version is < 4.1, please download and install the latest version of R, and then restart your R.
Install tidymass from GitLab 🔗︎
Update remotes pacakge
You can use the remotes package to install tidymass.
Please update remotes first and then restart your r session.
install.packages("remotes")
Install tidymass
Install tidymass by:
remotes::install_gitlab("tidymass/tidymass", dependencies = TRUE)
During installing, it may ask you several times: “Would you like to update some pacakges?” Just Enter the
EnterorRetrunkey to skip updates.
If you have a completely fresh R enivorment, it needs to install all the dependent packages, so it will take around 30 mins to finish the installation of
tidymass. In my Mac pro (macOS Monterey, 2.3 GHz 8-core intel core i9, 16GB 2667 MHz DDR4), it takes about 30 mins to finish the installation in a completely fresh R enivorment.
Install tidymass from GitHub 🔗︎
Install tidymass
remotes::install_github("tidymass/tidymass", dependencies = TRUE)
During the installation, it will ask if you want to update some packages for few times, just enter
EnterorReurnkey to skip it.
If there is a error like below:
Error: Failed to install 'tidymass' from GitHub: HTTP error 403. API rate limit exceeded for 171.66.10.237. (But here's the good news: Authenticated requests get a higher rate limit. Check out the documentation for more details.)
Try to resolve it by:
- In you R console, type this code:
usethis::create_github_token()
It will open a page in browser, and create a “New personal access token” and copy it.
- Then type this code:
usethis::edit_r_environ()
and then add one line like below:
GITHUB_PAT=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
The
GITHUB_PATshould be yours that is created in step 1.
And then restart R session and try again.
Install tidymass from Gitee 🔗︎
If you can’t install packages from GitHub and GitLab, please try install packages from Gitee.
Install tidymass
remotes::install_git(url = "https://gitee.com/tidymass/tidymass", dependencies = TRUE)
Install tidymass by local packages 🔗︎
Source the install_tidymass function.
Copy and paste the below code in your console.
source("https://www.tidymass.org/tidymass-packages/install_tidymass.txt")
Install packages
Copy and paste the below code in your console.
library(tidyverse)
install_tidymass(from = "tidymass.org")
Update tidymass
You can use the tidymass to check the version of all packages and update them.
Check version 🔗︎
If you want to check if there are updates for tidymass and packages in it. Just check it like this.
tidymass::check_tidymass_version()
Update 🔗︎
The update_tidymass() function can be used to update tidymass and packages in it.
tidymass::update_tidymass(from = "gitlab")
If the
from = "gitlab"doesn’t work, try set it asfrom = "github"orfrom = "gitee".
Install docker version of tidymass
Docker is a set of platform as a service (PaaS) products that use OS-level virtualization to deliver software in packages called containers. So it is useful for people who want to share the code, data, and even analysis environment with other people to repeat their analysis and results.
We provide a docker version of tidymass, all the packages in tidymass and the dependent packages have been installed.
Install docker 🔗︎
Please refer to the offical website to download and install docker. And then run docker.
Pull the tidymass image 🔗︎
Open you terminal and then type code below:
docker pull jaspershen/tidymass:latest
Run tidymass docker image 🔗︎
In your terminal, run the code below:
docker run -e PASSWORD=tidymass -p 8787:8787 jaspershen/tidymass:latest
The below command will link the RStudio home folder with the desktop of the local machine running the container. Anything saved or edited in the home folder when using the container will be stored on the local desktop.
docker run -e PASSWORD=tidymass -v ~/Desktop:/home/rstudio/ -p 8787:8787 jaspershen/tidymass:latest
Open the Rstudio server 🔗︎
Then open the browser and visit http://localhost:8787 to power on RStudio server. The user name is rstudio and the password is tidymass.
Build your own docker image based on tidymass
You can build your own docker image, which contains all your code, data and analysis environment, which is more efficient for reproducible analysis.
Create dockerfile 🔗︎
Create a dockerfile without extension. And then open and modify it.
FROM jaspershen/tidymass:latest
MAINTAINER "Xiaotao Shen" shenxt1990@outlook.com
RUN apt-get update && apt-get install -y curl
COPY demo_data/ /home/rstudio/demo_data/
RUN chmod 777 /home/rstudio/demo_data/
RUN R -e 'install.packages("remotes")'
RUN R -e "remotes::install_gitlab('tidymass/tidymass')"
If you want to install packages (for example ggraph) which are necessary for you analysis, please add a new line:
RUN R -e 'install.packages("ggraph")'
And you also need to copy your data to the image use the COPY.
Build image 🔗︎
In the terminal, use below code to build the image.
docker build -t image-name -f Dockerfile .
Change the image-name.
Use the docker tag command to give the tidymass image a new name 🔗︎
We need to create a account on the docker hub (https://hub.docker.com/) and then use the next code to link the local image to our account.
docker tag image-name your-account/image-name:latest
Push image to docker hub 🔗︎
docker push your-account/image-name:latest
Then other people can download your image which contains your code, data and analysis environment, which make it is pretty easy to repeat your analysis and results.
How to pull docker image and run it can refer this document.
Session information
sessionInfo()
## R version 4.2.1 (2022-06-23)
## Platform: x86_64-apple-darwin17.0 (64-bit)
## Running under: macOS Big Sur ... 10.16
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRlapack.dylib
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] magrittr_2.0.3
##
## loaded via a namespace (and not attached):
## [1] utf8_1.2.2 tidyselect_1.1.2
## [3] robust_0.7-0 htmlwidgets_1.5.4
## [5] grid_4.2.1 BiocParallel_1.30.3
## [7] munsell_0.5.0 codetools_0.2-18
## [9] preprocessCore_1.58.0 interp_1.1-2
## [11] future_1.26.1 colorspace_2.0-3
## [13] Biobase_2.56.0 ggfortify_0.4.14
## [15] knitr_1.39 rstudioapi_0.14
## [17] stats4_4.2.1 robustbase_0.95-0
## [19] Rttf2pt1_1.3.10 listenv_0.8.0
## [21] mzID_1.34.0 MatrixGenerics_1.8.1
## [23] GenomeInfoDbData_1.2.8 polyclip_1.10-0
## [25] farver_2.1.1 parallelly_1.32.0
## [27] vctrs_0.4.1 generics_0.1.3
## [29] xfun_0.31 itertools_0.1-3
## [31] randomForest_4.7-1.1 R6_2.5.1
## [33] doParallel_1.0.17 GenomeInfoDb_1.32.4
## [35] graphlayouts_0.8.0 clue_0.3-61
## [37] MsCoreUtils_1.8.0 bitops_1.0-7
## [39] gridGraphics_0.5-1 DelayedArray_0.22.0
## [41] assertthat_0.2.1 scales_1.2.0
## [43] ggraph_2.0.5 nnet_7.3-17
## [45] gtable_0.3.0 globals_0.15.1
## [47] affy_1.74.0 tidygraph_1.2.1
## [49] rlang_1.0.5 tidymass_1.0.7
## [51] mzR_2.30.0 GlobalOptions_0.1.2
## [53] massqc_1.0.5 splines_4.2.1
## [55] extrafontdb_1.0 Rdisop_1.56.0
## [57] lazyeval_0.2.2 impute_1.70.0
## [59] checkmate_2.1.0 reshape2_1.4.4
## [61] BiocManager_1.30.18 yaml_2.3.5
## [63] backports_1.4.1 Hmisc_4.7-0
## [65] extrafont_0.18 MassSpecWavelet_1.62.0
## [67] tools_4.2.1 bookdown_0.27
## [69] ggplotify_0.1.0 metid_1.2.24
## [71] ggplot2_3.3.6 affyio_1.66.0
## [73] ellipsis_0.3.2 jquerylib_0.1.4
## [75] RColorBrewer_1.1-3 proxy_0.4-27
## [77] BiocGenerics_0.42.0 MSnbase_2.22.0
## [79] Rcpp_1.0.8.3 plyr_1.8.7
## [81] progress_1.2.2 base64enc_0.1-3
## [83] zlibbioc_1.42.0 purrr_0.3.4
## [85] RCurl_1.98-1.7 prettyunits_1.1.1
## [87] rpart_4.1.16 deldir_1.0-6
## [89] viridis_0.6.2 pbapply_1.5-0
## [91] GetoptLong_1.0.5 S4Vectors_0.34.0
## [93] SummarizedExperiment_1.26.1 masscleaner_1.0.6
## [95] ggrepel_0.9.1 cluster_2.1.3
## [97] furrr_0.3.0 RSpectra_0.16-1
## [99] masstools_1.0.8 data.table_1.14.2
## [101] blogdown_1.10 openxlsx_4.2.5
## [103] circlize_0.4.15 RANN_2.6.1
## [105] pcaMethods_1.88.0 mvtnorm_1.1-3
## [107] ProtGenerics_1.28.0 matrixStats_0.62.0
## [109] hms_1.1.1 patchwork_1.1.1
## [111] evaluate_0.15 XML_3.99-0.10
## [113] massstat_1.0.3 jpeg_0.1-9
## [115] massprocesser_1.0.5 readxl_1.4.0
## [117] fastDummies_1.6.3 IRanges_2.30.0
## [119] gridExtra_2.3 shape_1.4.6
## [121] compiler_4.2.1 ellipse_0.4.3
## [123] tibble_3.1.7 ncdf4_1.19
## [125] crayon_1.5.1 htmltools_0.5.2
## [127] corpcor_1.6.10 pcaPP_2.0-1
## [129] tzdb_0.3.0 Formula_1.2-4
## [131] tidyr_1.2.0 rrcov_1.7-0
## [133] DBI_1.1.3 tweenr_1.0.2
## [135] ComplexHeatmap_2.12.1 MASS_7.3-57
## [137] MsFeatures_1.4.0 Matrix_1.4-1
## [139] readr_2.1.2 cli_3.3.0
## [141] vsn_3.64.0 igraph_1.3.2
## [143] parallel_4.2.1 GenomicRanges_1.48.0
## [145] pkgconfig_2.0.3 fit.models_0.64
## [147] foreign_0.8-82 plotly_4.10.0
## [149] MALDIquant_1.21 foreach_1.5.2
## [151] rARPACK_0.11-0 bslib_0.3.1
## [153] ggcorrplot_0.1.3 missForest_1.5
## [155] rngtools_1.5.2 XVector_0.36.0
## [157] massdataset_1.0.18 metpath_1.0.5
## [159] doRNG_1.8.2 yulab.utils_0.0.5
## [161] stringr_1.4.1 digest_0.6.29
## [163] Biostrings_2.64.0 xcms_3.18.0
## [165] rmarkdown_2.14 cellranger_1.1.0
## [167] htmlTable_2.4.0 rjson_0.2.21
## [169] lifecycle_1.0.1 jsonlite_1.8.0
## [171] mixOmics_6.20.0 viridisLite_0.4.0
## [173] limma_3.52.2 fansi_1.0.3
## [175] pillar_1.7.0 ggsci_2.9
## [177] lattice_0.20-45 KEGGREST_1.36.2
## [179] fastmap_1.1.0 httr_1.4.3
## [181] DEoptimR_1.0-11 survival_3.3-1
## [183] glue_1.6.2 remotes_2.4.2
## [185] zip_2.2.0 png_0.1-7
## [187] iterators_1.0.14 ggforce_0.3.3
## [189] class_7.3-20 stringi_1.7.8
## [191] sass_0.4.1 latticeExtra_0.6-30
## [193] dplyr_1.0.9 e1071_1.7-11