gganatogram绘制解剖图(2)之动植物篇

gganatogram软件包是一个可以快速绘制各种动植物解剖图的R包，今天来介绍如何通过其绘制动植物解剖图。喜欢的小伙伴可以关注个人公众号R语言数据分析指南持续分享更多优质资源，在此先行拜谢了！！

加载R包

library(gganatogram)
library(tidyverse)
library(viridis)
library(patchwork)

可以从此网址
https://ebi-gene-expression-group.github.io/anatomogram/获得所支持的物种清单

length(other_key)
#> [1] 24

names(other_key)
#>  [1] "anolis_carolinensis"                 
#>  [2] "arabidopsis_thaliana"                
#>  [3] "bos_taurus"                          
#>  [4] "brachypodium_distachyon.flower_parts"
#>  [5] "brachypodium_distachyon.whole_plant" 
#>  [6] "gallus_gallus"                       
#>  [7] "hordeum_vulgare.flower_parts"        
#>  [8] "hordeum_vulgare.whole_plant"         
#>  [9] "macaca_mulatta"                      
#> [10] "monodelphis_domestica"               
#> [11] "oryza_sativa.flower_parts"           
#> [12] "oryza_sativa.whole_plant"            
#> [13] "papio_anubis"                        
#> [14] "rattus_norvegicus"                   
#> [15] "solanum_lycopersicum.flower_parts"   
#> [16] "solanum_lycopersicum.whole_plant"    
#> [17] "sorghum_bicolor.flower_parts"        
#> [18] "sorghum_bicolor.whole_plant"         
#> [19] "tetraodon_nigroviridis"              
#> [20] "triticum_aestivum.flower_parts"      
#> [21] "triticum_aestivum.whole_plant"       
#> [22] "xenopus_tropicalis"                  
#> [23] "zea_mays.flower_parts"               
#> [24] "zea_mays.whole_plant"

other_key[["bos_taurus"]]
#>             organ  type  colour     value
#> 2        duodenum other #E41A1C 11.381132
#> 3           brain other #377EB8  2.264810
#> 4          kidney other #4DAF4A  4.131599
#> 5            lung other #984EA3  3.182946
#> 6           colon other #FF7F00  3.114481
#> 7           heart other #FFFF33 13.141334
#> 8           liver other #A65628 17.251310
#> 9  pulmonary vein other #F781BF 13.414659
#> 19 UBERON_0001013 other #999999 12.126515
#> 20 UBERON_0001013 other #66C2A5  1.898023
#> 21 UBERON_0001013 other #FC8D62 19.290389
#> 22 UBERON_0014892 other #8DA0CB 10.994221
#> 23 UBERON_0014892 other #E78AC3 16.761115
#> 24 UBERON_0014892 other #A6D854  2.468627
#> 25 UBERON_0014892 other #FFD92F  1.556285
#> 26 UBERON_0014892 other #E5C494  3.461740
#> 27 UBERON_0014892 other #B3B3B3 18.595027

gganatogram(data=other_key[["bos_taurus"]],
            outline = T, fillOutline='white',
organism="bos_taurus", sex='female', fill="colour")  +
  theme_void() +
  ggtitle("bos_taurus") + 
  theme(plot.title = element_text(hjust=0.5)) + 
  coord_fixed()

library(gridExtra)
plotList <- list()
for (organism in names(other_key)) {
    plotList[[organism]] <- gganatogram(data=other_key[[organism]],
outline = T, fillOutline='white',
organism=organism, sex='female', fill="colour")  +
                theme_void() +
                ggtitle(organism) + 
                theme(plot.title = element_text(hjust=0.5, size=9)) + 
                coord_fixed()
}

do.call(grid.arrange,  c(plotList[1:4], ncol=2))

do.call(grid.arrange,  c(plotList[5:8], ncol=2))

do.call(grid.arrange,  c(plotList[9:12], ncol=2))

do.call(grid.arrange,  c(plotList[13:16], ncol=2))

do.call(grid.arrange,  c(plotList[17:20], ncol=2))

do.call(grid.arrange,  c(plotList[21:24], ncol=2))

后面的内容更加精彩，喜欢的小伙伴可以关注我的公众号R语言数据分析指南在此先行拜谢了

原文链接：https://mp.weixin.qq.com/s/g-PGx1QRcZhsJV-ajKm2pA