R genes
Last updated: 2022-02-21
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Knit directory: Amphibolis_Posidonia_Comparison/
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library(tidyverse)Warning: package 'tidyverse' was built under R version 4.1.1-- Attaching packages --------------------------------------- tidyverse 1.3.1 --v ggplot2 3.3.5 v purrr 0.3.4
v tibble 3.1.5 v dplyr 1.0.7
v tidyr 1.1.4 v stringr 1.4.0
v readr 2.0.2 v forcats 0.5.1Warning: package 'ggplot2' was built under R version 4.1.1Warning: package 'tibble' was built under R version 4.1.1Warning: package 'tidyr' was built under R version 4.1.1Warning: package 'readr' was built under R version 4.1.1Warning: package 'purrr' was built under R version 4.1.1Warning: package 'dplyr' was built under R version 4.1.1Warning: package 'stringr' was built under R version 4.1.1Warning: package 'forcats' was built under R version 4.1.1-- Conflicts ------------------------------------------ tidyverse_conflicts() --
x dplyr::filter() masks stats::filter()
x dplyr::lag() masks stats::lag()library(wesanderson)Warning: package 'wesanderson' was built under R version 4.1.1library(ggtree)ggtree v3.0.4 For help: https://yulab-smu.top/treedata-book/
If you use ggtree in published research, please cite the most appropriate paper(s):
1. Guangchuang Yu. Using ggtree to visualize data on tree-like structures. Current Protocols in Bioinformatics, 2020, 69:e96. doi:10.1002/cpbi.96
2. Guangchuang Yu, Tommy Tsan-Yuk Lam, Huachen Zhu, Yi Guan. Two methods for mapping and visualizing associated data on phylogeny using ggtree. Molecular Biology and Evolution 2018, 35(12):3041-3043. doi:10.1093/molbev/msy194
3. Guangchuang Yu, David Smith, Huachen Zhu, Yi Guan, Tommy Tsan-Yuk Lam. ggtree: an R package for visualization and annotation of phylogenetic trees with their covariates and other associated data. Methods in Ecology and Evolution 2017, 8(1):28-36. doi:10.1111/2041-210X.12628
Attaching package: 'ggtree'The following object is masked from 'package:tidyr':
expandlibrary(ggtreeExtra)Warning: package 'ggtreeExtra' was built under R version 4.1.1ggtreeExtra v1.2.3 For help: https://yulab-smu.top/treedata-book/
If you use ggtreeExtra in published research, please cite the paper:
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, G Yu. ggtreeExtra: Compact visualization of richly annotated phylogenetic data. Molecular Biology and Evolution 2021, 38(9):4039-4042. doi: 10.1093/molbev/msab166knitr::opts_knit$set(root.dir = rprojroot::find_rstudio_root_file())Visualising R-gene differences here
pal <- wes_palette("Zissou1", 3, type = "continuous")
df <- readxl::read_xlsx('./data/R_genes.xlsx')
df %>% ggplot(aes(fill=Class, x=Genome, y=Count)) + geom_bar(stat='identity') +
scale_fill_manual(values=pal) +
coord_flip() + cowplot::theme_minimal_vgrid() +
theme(axis.text.y = element_text(face = "italic")) 
pal <- wes_palette("Zissou1", 4, type = "continuous")
df2 <- df %>% mutate(Class2= case_when(str_detect(Subclass, pattern = 'TN') ~ 'NLR (TNL)',
str_detect(Subclass, pattern = '^R') ~ Subclass,
TRUE ~ 'NLR (CNL)'))
df2 %>% ggplot(aes(fill=Class2, x=Genome, y=Count)) + geom_bar(stat='identity') +
scale_fill_manual(values=pal) + coord_flip() + cowplot::theme_minimal_vgrid() +
theme(axis.text.y = element_text(face = "italic")) 
df2 %>% dplyr::filter(Genome %in% c('P. australis', 'Z. marina', 'Z. muelleri', 'O. sativa', 'A. antarctica', 'A. thaliana')) %>%
ggplot(aes(fill=Class2, x=factor(Genome, levels=c('Z. marina', 'Z. muelleri', 'P. australis', 'A. antarctica', 'O. sativa', 'A. thaliana' )), y=Count)) +
geom_bar(stat='identity') +
scale_fill_manual(values=pal) + coord_flip() + cowplot::theme_minimal_vgrid() +
theme(axis.text.y = element_text(face = "italic")) +
xlab('Genome') +
labs(fill='Class')
Let’s link those to the phylogeny we got from timetree.org
tree <- ape::read.tree('./data/timetree_species.nwk')
tree$tip.label <- c('O. lucimarinus', 'C. reinhardtii', 'P. patens', 'S. moellendorffii', 'O. sativa', 'B. distachyon', 'Z. mays', 'P. australis', 'Z. marina', 'Z. muelleri', 'A. antarctica', 'S. polyrhiza', 'L. gibba', 'V. vinifera', 'A. thaliana', 'S. parvula', 'P. trichocarpa', 'A. trichopada')p2 <- df2 %>% ggplot(aes(fill=Class2, x=Genome, y=Count)) + geom_bar(stat='identity') +
scale_fill_manual(values=pal) + coord_flip() + cowplot::theme_minimal_vgrid() +
theme(axis.text.y = element_text(face = "italic")) p1 <- ggtree(tree)
p1
df2$label <- df2$Genome
# get species not in tree
subtree <- ape::drop.tip(tree, tree$tip.label[!tree$tip.label %in% df2$label])p1 <- ggtree(subtree)
p1 
df3 <- as.data.frame(df2)
df3$label <- df3$Genome
df3$id <- df3$label# code from https://thackl.github.io/ggtree-composite-plots
tree_y <- function(ggtree, data){
if(!inherits(ggtree, "ggtree"))
stop("not a ggtree object")
left_join(select(data, label), select(ggtree$data, label, y)) %>%
pull(y)
}
# overwrite the default expand for continuous scales
scale_y_tree <- function(expand=expand_scale(0, 0.6), ...){
scale_y_continuous(expand=expand, ...)
}
# get the range of the ggtree y-axis data
tree_ylim <- function(ggtree){
if(!inherits(ggtree, "ggtree"))
stop("not a ggtree object")
range(ggtree$data$y)
}
# plot data next to a ggtree aligned by shared labels
ggtreeplot <- function(ggtree, data = NULL, mapping = aes(), flip=FALSE,
expand_limits=expand_scale(0,.6), ...){
if(!inherits(ggtree, "ggtree"))
stop("not a ggtree object")
# match the tree limits
limits <- tree_ylim(ggtree)
limits[1] <- limits[1] + (limits[1] * expand_limits[1]) - expand_limits[2]
limits[2] <- limits[2] + (limits[2] * expand_limits[3]) + expand_limits[4]
if(flip){
mapping <- modifyList(aes_(x=~x), mapping)
data <- mutate(data, x=tree_y(ggtree, data))
gg <- ggplot(data=data, mapping = mapping, ...) +
scale_x_continuous(limits=limits, expand=c(0,0))
}else{
mapping <- modifyList(aes_(y=~y), mapping)
data <- mutate(data, y=tree_y(ggtree, data))
gg <- ggplot(data=data, mapping = mapping, ...) +
scale_y_continuous(limits=limits, expand=c(0,0))
}
gg
}
# get rid of superfluous axis - this works after coord_flip, so it also works
# for the rotated histogram
no_y_axis <- function ()
theme(axis.line.y = element_blank(),
axis.title.y = element_blank(),
axis.text.y = element_blank(),
axis.ticks.y = element_blank())p3 <- ggtree(subtree) + geom_tiplab(align=TRUE, fontface='italic') +
scale_x_continuous(expand=expand_scale(0.8)) + scale_y_tree()Warning: `expand_scale()` is deprecated; use `expansion()` instead.
Warning: `expand_scale()` is deprecated; use `expansion()` instead.Scale for 'y' is already present. Adding another scale for 'y', which will
replace the existing scale.myhist <- ggtreeplot(p3, df3, aes(y=Count, color=Class2, fill=Class2), flip=TRUE) +
geom_col(aes(fill=Class2,group=Class2,color=Class2)) +
#theme(legend.position="none") +
coord_flip() + no_y_axis() +
theme(legend.position=c(0.6, 0.87)) +
labs(fill='Class', color='Class')Warning: `expand_scale()` is deprecated; use `expansion()` instead.Joining, by = "label"p3 + myhist 
sessionInfo()R version 4.1.0 (2021-05-18)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19042)
Matrix products: default
locale:
[1] LC_COLLATE=English_Australia.1252 LC_CTYPE=English_Australia.1252
[3] LC_MONETARY=English_Australia.1252 LC_NUMERIC=C
[5] LC_TIME=English_Australia.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] ggtreeExtra_1.2.3 ggtree_3.0.4 wesanderson_0.3.6 forcats_0.5.1
[5] stringr_1.4.0 dplyr_1.0.7 purrr_0.3.4 readr_2.0.2
[9] tidyr_1.1.4 tibble_3.1.5 ggplot2_3.3.5 tidyverse_1.3.1
[13] workflowr_1.6.2
loaded via a namespace (and not attached):
[1] nlme_3.1-152 fs_1.5.0 lubridate_1.8.0 httr_1.4.2
[5] rprojroot_2.0.2 tools_4.1.0 backports_1.2.1 bslib_0.3.1
[9] utf8_1.2.2 R6_2.5.1 DBI_1.1.1 lazyeval_0.2.2
[13] colorspace_2.0-2 withr_2.4.2 tidyselect_1.1.1 compiler_4.1.0
[17] git2r_0.28.0 cli_3.0.1 rvest_1.0.2 xml2_1.3.2
[21] labeling_0.4.2 sass_0.4.0 scales_1.1.1 digest_0.6.28
[25] yulab.utils_0.0.4 rmarkdown_2.11 pkgconfig_2.0.3 htmltools_0.5.2
[29] highr_0.9 dbplyr_2.1.1 fastmap_1.1.0 rlang_0.4.12
[33] readxl_1.3.1 rstudioapi_0.13 farver_2.1.0 gridGraphics_0.5-1
[37] jquerylib_0.1.4 generics_0.1.1 jsonlite_1.7.2 magrittr_2.0.1
[41] ggplotify_0.1.0 patchwork_1.1.1 Rcpp_1.0.7 munsell_0.5.0
[45] fansi_0.5.0 ape_5.5 ggnewscale_0.4.5 lifecycle_1.0.1
[49] stringi_1.7.5 whisker_0.4 yaml_2.2.1 grid_4.1.0
[53] parallel_4.1.0 promises_1.2.0.1 crayon_1.4.1 lattice_0.20-44
[57] haven_2.4.3 cowplot_1.1.1 hms_1.1.1 knitr_1.36
[61] pillar_1.6.4 reprex_2.0.1 glue_1.4.2 evaluate_0.14
[65] ggfun_0.0.5 modelr_0.1.8 vctrs_0.3.8 treeio_1.16.2
[69] tzdb_0.1.2 httpuv_1.6.3 cellranger_1.1.0 gtable_0.3.0
[73] assertthat_0.2.1 xfun_0.27 broom_0.7.9 tidytree_0.3.7
[77] later_1.3.0 aplot_0.1.2 ellipsis_0.3.2