美文网首页R作图
gganatogram绘制解剖图(1)之人体篇

gganatogram绘制解剖图(1)之人体篇

作者: R语言数据分析指南 | 来源:发表于2021-02-21 19:51 被阅读0次

    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人体解剖图。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!!

    由于我一直习惯安装开发版R包,各位可以根据个人喜好安装官方版也可,如何方便如何来,如果安装gituhub版R包有困难请给我留言,可以出一个完美的教程给各位

    安装必须的R包

    devtools::install_github("jespermaag/gganatogram")
    devtools::install_github("mdsumner/ggpolypath")
    devtools::install_github("jrowen/rhandsontable")
    
    install.packages("ggpolypath")
    install.packages("rhandsontable")
    

    加载R包

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

    创建人体解剖图图像

    hgMale <- gganatogram(data=hgMale_key, 
    fillOutline='#a6bddb', organism='human', sex='male', fill="colour") + 
    theme_void()
    
    hgFemale <- gganatogram(data=hgFemale_key, 
    fillOutline='#a6bddb', organism='human', sex='female', fill="colour") + 
    theme_void()
    
    hgMale+hgFemale
    

    用数值进行填充

    hgMale <- gganatogram(data=hgMale_key,
    fillOutline='#440154FF', organism='human', 
    sex='male', fill="value") + theme_void() +  
    scale_fill_viridis()
    
    hgFemale <- gganatogram(data=hgFemale_key,
    fillOutline='#440154FF', organism='human',
    sex='female', fill="value") + theme_void() +
    scale_fill_viridis()
    
    hgMale+hgFemale
    

    创建包含器官,颜色和值的数据框进行绘图

    organPlot <- data.frame(organ = c("heart", "leukocyte",
     "nerve","brain","liver","stomach","colon"), 
     type = c("circulation","circulation","nervous system", 
    "nervous system","digestion","digestion","digestion"), 
     colour = c("red","red","purple","purple", "orange", "orange", "orange"), 
     value = c(10, 5, 1, 8, 2, 5, 5), 
     stringsAsFactors=F)
    
    gganatogram(data=organPlot,fillOutline='#a6bddb',
                organism='human', sex='male', fill="colour")+
      theme_void()
    

    hgMale_key绘制所有可用的组织

    hgMale_key$organ
    
     [1] "thyroid_gland"             "bone_marrow"               "frontal_cortex"           
     [4] "prefrontal_cortex"         "pituitary_gland"           "aorta"                    
     [7] "gastroesophageal_junction" "left_ventricle"            "caecum"                   
    [10] "ileum"                     "rectum"                    "nose"                     
    [13] "breast"                    "tongue"                    "left_atrium"              
    [16] "pulmonary_valve"           "mitral_valve"              "penis"                    
    [19] "nasal_pharynx"             "spinal_cord"               "throat"                   
    [22] "tricuspid_valve"           "diaphragm"                 "liver"                    
    [25] "stomach"                   "spleen"                    "duodenum"                 
    [28] "gall_bladder"              "pancreas"                  "colon"                    
    [31] "small_intestine"           "appendix"                  "smooth_muscle"            
    [34] "urinary_bladder"           "bone"                      "cartilage"                
    [37] "esophagus"                 "salivary_gland"            "parotid_gland"            
    [40] "submandibular_gland"       "skin"                      "pleura"                   
    [43] "brain"                     "heart"                     "adrenal_gland"            
    [46] "lymph_node"                "adipose_tissue"            "skeletal_muscle"          
    [49] "leukocyte"                 "temporal_lobe"             "atrial_appendage"         
    [52] "coronary_artery"           "hippocampus"               "vas_deferens"             
    [55] "seminal_vesicle"           "epididymis"                "tonsil"                   
    [58] "lung"                      "amygdala"                  "trachea"                  
    [61] "bronchus"                  "nerve"                     "cerebellum"               
    [64] "cerebellar_hemisphere"     "kidney"                    "renal_cortex"             
    [67] "testis"  
    
    gganatogram(data=hgMale_key, 
    fillOutline='#a6bddb', organism='human', 
    sex='male', fill="colour") +theme_void()
    

    根据每个器官的值进行颜色填充

    gganatogram(data=organPlot, fillOutline='#a6bddb',
                organism='human', sex='male', fill="value") + 
      theme_void() +
      scale_fill_gradient(low = "white", high = "red")
    

    使用facet_wrap来对数据进行可视化。首先在类型列中创建两个具有不同值和条件的数据框

    compareGroups <- rbind(data.frame(organ = c("heart",
     "leukocyte", "nerve", "brain", "liver", "stomach", "colon"), 
      colour = c("red", "red", "purple", "purple", 
    "orange", "orange", "orange"), 
     value = c(10, 5, 1, 8, 2, 5, 5), 
     type = rep('Normal', 7), 
     stringsAsFactors=F),
     data.frame(organ = c("heart", "leukocyte", 
    "nerve", "brain", "liver", "stomach", "colon"), 
      colour = c("red", "red", "purple", "purple", 
    "orange", "orange", "orange"), 
     value = c(5, 5, 10, 8, 2, 5, 5), 
     type = rep('Cancer', 7), 
     stringsAsFactors=F))
    
    gganatogram(data=compareGroups,
    fillOutline='#a6bddb', organism='human', sex='male', fill="value") + 
    theme_void() +
    facet_wrap(~type) +
    scale_fill_gradient(low = "white", high = "red") 
    

    根据组织类型进行分面

    gganatogram(data=hgMale_key, outline = T, 
    fillOutline='#a6bddb', organism='human', sex='male', fill="colour") +
    facet_wrap(~type, ncol=4) +
    theme_void()
    

    所有女性组织

    > hgFemale_key$organ
     [1] "atrial_appendage"          "ectocervix"                "hippocampus"              
     [4] "pleura"                    "bronchus"                  "trachea"                  
     [7] "lung"                      "tonsil"                    "submandibular_gland"      
    [10] "breast"                    "spinal_cord"               "pancreas"                 
    [13] "liver"                     "colon"                     "bone_marrow"              
    [16] "urinary_bladder"           "stomach"                   "duodenum"                 
    [19] "esophagus"                 "gall_bladder"              "spleen"                   
    [22] "small_intestine"           "placenta"                  "endometrium"              
    [25] "vagina"                    "aorta"                     "pituitary_gland"          
    [28] "gastroesophageal_junction" "caecum"                    "appendix"                 
    [31] "ileum"                     "left_atrium"               "left_ventricle"           
    [34] "pulmonary_valve"           "mitral_valve"              "diaphragm"                
    [37] "bone"                      "cartilage"                 "throat"                   
    [40] "rectum"                    "nasal_septum"              "nasal_pharynx"            
    [43] "cerebellum"                "cerebellar_hemisphere"     "prefrontal_cortex"        
    [46] "frontal_cortex"            "nose"                      "temporal_lobe"            
    [49] "cerebral_cortex"           "kidney"                    "renal_cortex"             
    [52] "coronary_artery"           "tricuspid_valve"           "thyroid_gland"            
    [55] "skin"                      "parotid_gland"             "adipose_tissue"           
    [58] "heart"                     "smooth_muscle"             "brain"                    
    [61] "adrenal_gland"             "lymph_node"                "skeletal_muscle"          
    [64] "ovary"                     "leukocyte"                 "salivary_gland"           
    [67] "fallopian_tube"            "uterus"                    "uterine_cervix"           
    [70] "nerve"
    
    gganatogram(data=hgFemale_key, outline = T, fillOutline='#a6bddb',
                organism='human', sex='female', fill="colour")  +theme_void()
    

    根据组织类型进行分面

    gganatogram(data=hgFemale_key, outline = T, 
    fillOutline='#a6bddb', organism='human', sex='female', fill="colour") +
    facet_wrap(~type, ncol=4) +
    theme_void()
    

    这一节就介绍如何绘制人体的解剖图,接着将介绍其它动植物及细胞结构的解剖图绘制,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/8nDXyghWrAPjDLqrd-GSsw

    相关文章

      网友评论

        本文标题:gganatogram绘制解剖图(1)之人体篇

        本文链接:https://www.haomeiwen.com/subject/koazxltx.html