YuLab-SMU / plotting-tree-with-data-using-ggtreeExtra

Home Page:https://doi.org/10.1093/molbev/msab166

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ggtreeExtra: Compact visualization of richly annotated phylogenetic data

If you use this work in published research, please cite:

S Xu, Z Dai, P Guo, X Fu, S Liu, L Zhou, W Tang, T Feng, M Chen, L Zhan, T Wu, E Hu, Y Jiang*, X Bo* and G Yu*. ggtreeExtra: Compact visualization of richly annotated phylogenetic data. Molecular Biology and Evolution. 2021, 38(9):4039-4042. doi: 10.1093/molbev/msab166.

This repo contains source code and data to produce

Supplementary Material of the above paper.
  • rawdata: contains HMP_tree, kegg and PhyloPhlAn, downloaded from the examples of GraPhlAn, and the Methanotroph, downloaded from the repo.
  • scripts: contains the script to produce the dataset of data using the data set of rawdata.
  • data: contains all the data sets that used to generate figures in Supplemental file.
  • Rmarkdown: contains the source code to produce Supplementary File.

Dependencies and locations

  • R (>= 4.0.3) should be installed and located in the user’s PATH, and the following packages should be installed.
    • ggtreeExtra : BiocManager::install("ggtreeExtra")
    • ggtree : BiocManager::install("ggtree")
    • treeio : BiocManager::install("treeio")
    • tidytree : install.packages("tidytree")
    • ggplot2 : install.packages("ggplot2")
    • kableExtra : install.packages("kableExtra")
    • bookdown : install.package("bookdown")
    • MicrobiotaProcess : BiocManager::install("MicrobiotaProcess")
    • ggstar : install.packages("ggstar")
    • Cairo : install.packages("Cairo")
    • aplot : install.packages("aplot")
    • patchwork : install.packages("patchwork")
    • ggnewscale : install.packages("ggnewscale")
    • knitr : install.packages("knitr")
    • ggpp : install.packages("ggpp")
    • ggpattern : remotes::install_github("coolbutuseless/ggpattern")
    • tibble : install.packages("tibble")
    • tidyr : install.packages("tidyr")
    • dplyr : install.packages("dplyr")
    • ggimage : install.packages("ggimage")
    • ggridges : install.packages("ggridges")

To compile the Rmarkdown/supplemental_file.pdf, please run the following command on terminal.

Rscript -e 'rmarkdown::render("./Rmarkdown/supplementary_file.Rmd")'

Or run the following command in R.

rmarkdown::render("./Rmarkdown/supplementary_file.Rmd")

Here is the output of sessionInfo() of the system on which the Supplemental file was compiled:

## R version 4.1.0 (2021-05-18)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 18.04.4 LTS
## 
## Matrix products: default
## BLAS:   /mnt/d/UbuntuApps/R/4.1.0/lib/R/lib/libRblas.so
## LAPACK: /mnt/d/UbuntuApps/R/4.1.0/lib/R/lib/libRlapack.so
## 
## locale:
##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
##  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
##  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
##  [1] ggimage_0.2.9               tibble_3.1.2               
##  [3] dplyr_1.0.7                 tidyr_1.1.3                
##  [5] ggridges_0.5.3              ggpp_0.4.0                 
##  [7] ggpattern_0.1.3             knitr_1.33                 
##  [9] patchwork_1.1.1             Cairo_1.5-12.2             
## [11] kableExtra_1.3.4            aplot_0.0.6                
## [13] MicrobiotaProcess_1.5.3.992 ggnewscale_0.4.5           
## [15] tidytree_0.3.4.991          treeio_1.17.2              
## [17] ggtree_3.1.3.991            ggplot2_3.3.5              
## [19] ggstar_1.0.2.991            ggtreeExtra_1.3.3          
## 
## loaded via a namespace (and not attached):
##   [1] TH.data_1.0-10              colorspace_2.0-2           
##   [3] ggsignif_0.6.3              class_7.3-19               
##   [5] ellipsis_0.3.2              modeltools_0.2-23          
##   [7] XVector_0.32.0              GenomicRanges_1.44.0       
##   [9] proxy_0.4-26                rstudioapi_0.13            
##  [11] ggrepel_0.9.1               fansi_0.5.0                
##  [13] mvtnorm_1.1-2               coin_1.4-1                 
##  [15] xml2_1.3.2                  codetools_0.2-18           
##  [17] splines_4.1.0               libcoin_1.0-8              
##  [19] polyclip_1.10-0             ade4_1.7-17                
##  [21] jsonlite_1.7.2              phyloseq_1.36.0            
##  [23] cluster_2.1.2               png_0.1-7                  
##  [25] compiler_4.1.0              httr_1.4.2                 
##  [27] assertthat_0.2.1            Matrix_1.3-4               
##  [29] lazyeval_0.2.2              htmltools_0.5.1.1          
##  [31] tools_4.1.0                 igraph_1.2.6               
##  [33] gtable_0.3.0                glue_1.4.2                 
##  [35] GenomeInfoDbData_1.2.6      reshape2_1.4.4             
##  [37] Rcpp_1.0.6                  Biobase_2.52.0             
##  [39] vctrs_0.3.8                 Biostrings_2.60.1          
##  [41] rhdf5filters_1.4.0          multtest_2.48.0            
##  [43] ape_5.5                     svglite_2.0.0              
##  [45] nlme_3.1-152                iterators_1.0.13           
##  [47] xfun_0.24                   stringr_1.4.0              
##  [49] rvest_1.0.0                 lifecycle_1.0.0            
##  [51] zlibbioc_1.38.0             MASS_7.3-54                
##  [53] zoo_1.8-9                   scales_1.1.1               
##  [55] MatrixGenerics_1.4.0        parallel_4.1.0             
##  [57] SummarizedExperiment_1.22.0 biomformat_1.20.0          
##  [59] sandwich_3.0-1              rhdf5_2.36.0               
##  [61] yaml_2.2.1                  gridGeometry_0.2-0         
##  [63] gridExtra_2.3               ggfun_0.0.3                
##  [65] yulab.utils_0.0.3           stringi_1.6.2              
##  [67] S4Vectors_0.30.0            foreach_1.5.1              
##  [69] e1071_1.7-7                 permute_0.9-5              
##  [71] BiocGenerics_0.38.0         GenomeInfoDb_1.28.0        
##  [73] rlang_0.4.11                pkgconfig_2.0.3            
##  [75] systemfonts_1.0.2           matrixStats_0.59.0         
##  [77] bitops_1.0-7                evaluate_0.14              
##  [79] lattice_0.20-44             sf_1.0-0                   
##  [81] purrr_0.3.4                 Rhdf5lib_1.14.1            
##  [83] tidyselect_1.1.1            plyr_1.8.6                 
##  [85] magrittr_2.0.1              R6_2.5.0                   
##  [87] IRanges_2.26.0              magick_2.7.2               
##  [89] generics_0.1.0              multcomp_1.4-17            
##  [91] DelayedArray_0.18.0         DBI_1.1.1                  
##  [93] pillar_1.6.1                withr_2.4.2                
##  [95] mgcv_1.8-36                 units_0.7-2                
##  [97] survival_3.2-11             RCurl_1.98-1.3             
##  [99] crayon_1.4.1                KernSmooth_2.23-20         
## [101] utf8_1.2.1                  rmarkdown_2.9.7            
## [103] grid_4.1.0                  data.table_1.14.0          
## [105] vegan_2.5-7                 classInt_0.4-3             
## [107] digest_0.6.27               webshot_0.5.2              
## [109] gridGraphics_0.5-1          stats4_4.1.0               
## [111] munsell_0.5.0               ggplotify_0.0.9            
## [113] viridisLite_0.4.0

Docker image

We also provided a docker image to help users to build the computing environment. You can pull and run it according to the following commands.

  • Install Docker (https://www.docker.com/)
    • sudo apt-get install docker.io (Ubuntu)
  • Pull the Docker image from Docker Hub:
    • docker pull xushuangbin/ggtreeextraarticleenv:latest
    • or
    • sudo pull xushuangbin/ggtreeextraarticleenv:latest
  • Run the image:
    • docker run -e PASSWORD=yourpassword -p 8787:8787 xushuangbin/ggtreeextraarticleenv
    • or
    • sudo docker run -e PASSWORD=yourpassword -p 8787:8787 xushuangbin/ggtreeextraarticleenv
  • Log in to RStudio at http://localhost:8787 using username rstudio and password yourpassword. For Windows users, you also need to provide your IP address, you can find it using docker-machine ip default.
  • Inside the RStudio, run: browseVignettes(package = "ggtreeExtraArticleEnv")
  • You can click one of the links: “PDF”, “source”, “R code”
  • In case of The requested page was not found error, try add ‘help/’ in front of the hostname in the URL (this is a known bug): http://localhost:8787/help/library/ggtreeExtraArticleEnv/doc/supplementary_file.pdf

About

https://doi.org/10.1093/molbev/msab166


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