this is the ICP result for salt only treatment.

getwd()
## [1] "C:/Users/Julkowska Lab/Desktop/R codes by Maryam/20240916_RSA_atorthologoues_for_tomato_hormones"
setwd("C:/Users/Julkowska Lab/Desktop/R codes by Maryam/20240916_RSA_atorthologoues_for_tomato_hormones")
list.files(pattern = ".csv")
##  [1] "202409_AtOrthologue_for_tomato_hormone_mutants_growth_factors.csv"
##  [2] "d12-1stbatch-.csv"                                                
##  [3] "d12-2ndBatch-modified.csv"                                        
##  [4] "d12-both.csv"                                                     
##  [5] "d5-1stbatch.csv"                                                  
##  [6] "d5-2ndBatch.csv"                                                  
##  [7] "d5-both.csv"                                                      
##  [8] "d8-1stbatch.csv"                                                  
##  [9] "d8-2ndBatch-modified.csv"                                         
## [10] "d8-both.csv"                                                      
## [11] "ICP-both-batch-Atortholougues-for-hormonesv2.csv"
ICP <- read.csv("ICP-both-batch-Atortholougues-for-hormonesv2.csv")
ICP
colnames(ICP)
## [1] "Accession"               "Tissue"                 
## [3] "DW.g"                    "DW.mg"                  
## [5] "Na.con.mg.mg.dry.weight" "K.con..mg.mg.dry.weight"
## [7] "Na.K.ratio"
ICP$All.ID<-paste(ICP$Accession, ICP$Tissue, sep="_")
ICP
library(ggplot2)
library(ggpubr)
library(multcompView)
## Warning: package 'multcompView' was built under R version 4.3.2
library(cowplot)
## 
## Attaching package: 'cowplot'
## The following object is masked from 'package:ggpubr':
## 
##     get_legend

#double check if my group # is correct…I have one group, since there is one condition

aov(Na.con.mg.mg.dry.weight ~ All.ID, data = ICP)
## Call:
##    aov(formula = Na.con.mg.mg.dry.weight ~ All.ID, data = ICP)
## 
## Terms:
##                   All.ID Residuals
## Sum of Squares  15243.57  16270.26
## Deg. of Freedom       17       195
## 
## Residual standard error: 9.134399
## Estimated effects may be unbalanced
Output <- TukeyHSD(aov(Na.con.mg.mg.dry.weight ~ All.ID, data = ICP))
Output
##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = Na.con.mg.mg.dry.weight ~ All.ID, data = ICP)
## 
## $All.ID
##                     diff         lwr         upr     p adj
## 1B_SH-1B_RO  15.48258432   0.9638069  30.0013617 0.0235833
## 1C_RO-1B_RO  -0.93709926 -15.4558767  13.5816782 1.0000000
## 1C_SH-1B_RO  11.42735652  -3.0914209  25.9461339 0.3323697
## 1D_RO-1B_RO   4.63337134 -11.6454277  20.9121704 0.9999264
## 1D_SH-1B_RO  18.02201849   1.7432194  34.3008176 0.0144045
## 1E_RO-1B_RO   1.26562720 -13.5762281  16.1074825 1.0000000
## 1E_SH-1B_RO  20.74163054   6.2228531  35.2604080 0.0001432
## A_RO-1B_RO    0.72776886 -12.0537039  13.5092416 1.0000000
## A_SH-1B_RO    9.17014344  -3.6993772  22.0396641 0.5184190
## B_RO-1B_RO   -2.51994000 -17.3617953  12.3219153 1.0000000
## B_SH-1B_RO    9.15676309  -5.0871861  23.4007123 0.7012221
## C_RO-1B_RO   -3.60208373 -18.1208611  10.9166937 0.9999895
## C_SH-1B_RO   11.63259480  -2.6113544  25.8765440 0.2693405
## D_RO-1B_RO   -2.87896827 -17.1229175  11.3649809 0.9999995
## D_SH-1B_RO    8.75083136  -5.4931178  22.9947806 0.7689489
## E_RO-1B_RO   -2.63106095 -16.8750101  11.6128882 0.9999999
## E_SH-1B_RO   25.45559327  11.2116441  39.6995425 0.0000003
## 1C_RO-1B_SH -16.41968358 -30.1934052  -2.6459619 0.0047847
## 1C_SH-1B_SH  -4.05522780 -17.8289494   9.7184938 0.9998830
## 1D_RO-1B_SH -10.84921298 -26.4671453   4.7687193 0.5661286
## 1D_SH-1B_SH   2.53943417 -13.0784981  18.1573665 1.0000000
## 1E_RO-1B_SH -14.21695713 -28.3308219  -0.1030924 0.0461863
## 1E_SH-1B_SH   5.25904622  -8.5146754  19.0327679 0.9968283
## A_RO-1B_SH  -14.75481546 -26.6832083  -2.8264226 0.0025792
## A_SH-1B_SH   -6.31244088 -18.3351308   5.7102490 0.9238050
## B_RO-1B_SH  -18.00252432 -32.1163891  -3.8886596 0.0014877
## B_SH-1B_SH   -6.32582123 -19.8095373   7.1578948 0.9717580
## C_RO-1B_SH  -19.08466806 -32.8583897  -5.3109464 0.0002831
## C_SH-1B_SH   -3.84998952 -17.3337056   9.6337265 0.9999231
## D_RO-1B_SH  -18.36155259 -31.8452687  -4.8778365 0.0004098
## D_SH-1B_SH   -6.73175296 -20.2154690   6.7519631 0.9501745
## E_RO-1B_SH  -18.11364527 -31.5973613  -4.6299292 0.0005430
## E_SH-1B_SH    9.97300895  -3.5107071  23.4567250 0.4474642
## 1C_SH-1C_RO  12.36445578  -1.4092659  26.1381774 0.1382008
## 1D_RO-1C_RO   5.57047060 -10.0474617  21.1884029 0.9985944
## 1D_SH-1C_RO  18.95911775   3.3411854  34.5770501 0.0035525
## 1E_RO-1C_RO   2.20272645 -11.9111383  16.3165912 1.0000000
## 1E_SH-1C_RO  21.67872980   7.9050082  35.4524514 0.0000126
## A_RO-1C_RO    1.66486812 -10.2635247  13.5932610 1.0000000
## A_SH-1C_RO   10.10724270  -1.9154472  22.1299326 0.2240544
## B_RO-1C_RO   -1.58284074 -15.6967055  12.5310240 1.0000000
## B_SH-1C_RO   10.09386235  -3.3898537  23.5775784 0.4246417
## C_RO-1C_RO   -2.66498448 -16.4387061  11.1087372 0.9999998
## C_SH-1C_RO   12.56969406  -0.9140220  26.0534101 0.1000937
## D_RO-1C_RO   -1.94186901 -15.4255851  11.5418471 1.0000000
## D_SH-1C_RO    9.68793061  -3.7957855  23.1716467 0.5026581
## E_RO-1C_RO   -1.69396169 -15.1776778  11.7897544 1.0000000
## E_SH-1C_RO   26.39269253  12.9089765  39.8764086 0.0000000
## 1D_RO-1C_SH  -6.79398518 -22.4119175   8.8239471 0.9866600
## 1D_SH-1C_SH   6.59466197  -9.0232703  22.2125943 0.9902435
## 1E_RO-1C_SH -10.16172933 -24.2755941   3.9521354 0.4987176
## 1E_SH-1C_SH   9.31427402  -4.4594476  23.0879957 0.6151781
## A_RO-1C_SH  -10.69958766 -22.6279805   1.2288052 0.1390755
## A_SH-1C_SH   -2.25721308 -14.2799030   9.7654768 0.9999998
## B_RO-1C_SH  -13.94729652 -28.0611613   0.1665682 0.0567351
## B_SH-1C_SH   -2.27059343 -15.7543095  11.2131226 1.0000000
## C_RO-1C_SH  -15.02944025 -28.8031619  -1.2557186 0.0175163
## C_SH-1C_SH    0.20523828 -13.2784778  13.6889543 1.0000000
## D_RO-1C_SH  -14.30632479 -27.7900409  -0.8226087 0.0251253
## D_SH-1C_SH   -2.67652516 -16.1602412  10.8071909 0.9999996
## E_RO-1C_SH  -14.05841747 -27.5421335  -0.5747014 0.0311014
## E_SH-1C_SH   14.02823675   0.5445207  27.5119528 0.0319089
## 1D_SH-1D_RO  13.38864715  -3.8776267  30.6549210 0.3591986
## 1E_RO-1D_RO  -3.36774415 -19.2864621  12.5509738 0.9999990
## 1E_SH-1D_RO  16.10825920   0.4903269  31.7261915 0.0353410
## A_RO-1D_RO   -3.90560248 -17.9231257  10.1119208 0.9999453
## A_SH-1D_RO    4.53677210  -9.5610814  18.6346256 0.9996171
## B_RO-1D_RO   -7.15331134 -23.0720293   8.7654066 0.9814415
## B_SH-1D_RO    4.52339175 -10.8393880  19.8861715 0.9998829
## C_RO-1D_RO   -8.23545508 -23.8533874   7.3824772 0.9211087
## C_SH-1D_RO    6.99922346  -8.3635563  22.3620032 0.9787265
## D_RO-1D_RO   -7.51233961 -22.8751193   7.8504401 0.9585581
## D_SH-1D_RO    4.11746002 -11.2453197  19.4802397 0.9999683
## E_RO-1D_RO   -7.26443229 -22.6272120   8.0983474 0.9695724
## E_SH-1D_RO   20.82222193   5.4594422  36.1850017 0.0004521
## 1E_RO-1D_SH -16.75639130 -32.6751092  -0.8376734 0.0277108
## 1E_SH-1D_SH   2.71961205 -12.8983203  18.3375444 1.0000000
## A_RO-1D_SH  -17.29424963 -31.3117729  -3.2767264 0.0026972
## A_SH-1D_SH   -8.85187505 -22.9497286   5.2459785 0.7376296
## B_RO-1D_SH  -20.54195849 -36.4606764  -4.6232406 0.0011973
## B_SH-1D_SH   -8.86525540 -24.2280351   6.4975243 0.8454401
## C_RO-1D_SH  -21.62410223 -37.2420345  -6.0061699 0.0002877
## C_SH-1D_SH   -6.38942369 -21.7522034   8.9733560 0.9917081
## D_RO-1D_SH  -20.90098676 -36.2637665  -5.5382070 0.0004179
## D_SH-1D_SH   -9.27118714 -24.6339669   6.0915926 0.7928264
## E_RO-1D_SH  -20.65307944 -36.0158592  -5.2902997 0.0005349
## E_SH-1D_SH    7.43357478  -7.9292050  22.7963545 0.9623358
## 1E_SH-1E_RO  19.47600335   5.3621386  33.5898681 0.0003093
## A_RO-1E_RO   -0.53785833 -12.8574495  11.7817328 1.0000000
## A_SH-1E_RO    7.90451625  -4.5064000  20.3154325 0.7159059
## B_RO-1E_RO   -3.78556719 -18.2315683  10.6604339 0.9999770
## B_SH-1E_RO    7.89113590  -5.9398572  21.7221290 0.8571439
## C_RO-1E_RO   -4.86771093 -18.9815757   9.2461538 0.9990724
## C_SH-1E_RO   10.36696761  -3.4640255  24.1979607 0.4222482
## D_RO-1E_RO   -4.14459546 -17.9755885   9.6863976 0.9998513
## D_SH-1E_RO    7.48520416  -6.3457889  21.3161972 0.9031658
## E_RO-1E_RO   -3.89668814 -17.7276812   9.9343049 0.9999361
## E_SH-1E_RO   24.18996608  10.3589730  38.0209591 0.0000005
## A_RO-1E_SH  -20.01386168 -31.9422545  -8.0854688 0.0000020
## A_SH-1E_SH  -11.57148710 -23.5941770   0.4512028 0.0741373
## B_RO-1E_SH  -23.26157054 -37.3754353  -9.1477058 0.0000034
## B_SH-1E_SH  -11.58486745 -25.0685835   1.8988486 0.1928879
## C_RO-1E_SH  -24.34371428 -38.1174359 -10.5699926 0.0000004
## C_SH-1E_SH   -9.10903574 -22.5927518   4.3746803 0.6169674
## D_RO-1E_SH  -23.62059881 -37.1043149 -10.1368827 0.0000005
## D_SH-1E_SH  -11.99079919 -25.4745153   1.4929169 0.1489922
## E_RO-1E_SH  -23.37269149 -36.8564076  -9.8889754 0.0000007
## E_SH-1E_SH    4.71396273  -8.7697533  18.1976788 0.9989015
## A_SH-A_RO     8.44237458  -1.4123817  18.2971308 0.1969027
## B_RO-A_RO    -3.24770886 -15.5673000   9.0718823 0.9999749
## B_SH-A_RO     8.42899423  -3.1633199  20.0213084 0.4799421
## C_RO-A_RO    -4.32985260 -16.2582454   7.5985402 0.9982598
## C_SH-A_RO    10.90482594  -0.6874882  22.4971401 0.0921644
## D_RO-A_RO    -3.60673713 -15.1990513   7.9855770 0.9997542
## D_SH-A_RO     8.02306249  -3.5692516  19.6153766 0.5729715
## E_RO-A_RO    -3.35882981 -14.9511439   8.2334843 0.9999059
## E_SH-A_RO    24.72782441  13.1355103  36.3201385 0.0000000
## B_RO-A_SH   -11.69008344 -24.1009997   0.7208328 0.0910627
## B_SH-A_SH    -0.01338035 -11.7027030  11.6759423 1.0000000
## C_RO-A_SH   -12.77222718 -24.7949171  -0.7495373 0.0247339
## C_SH-A_SH     2.46245136  -9.2268713  14.1517740 0.9999991
## D_RO-A_SH   -12.04911171 -23.7384344  -0.3597891 0.0355876
## D_SH-A_SH    -0.41931209 -12.1086347  11.2700106 1.0000000
## E_RO-A_SH   -11.80120439 -23.4905270  -0.1118817 0.0450552
## E_SH-A_SH    16.28544983   4.5961272  27.9747725 0.0002513
## B_SH-B_RO    11.67670309  -2.1542900  25.5076962 0.2178009
## C_RO-B_RO    -1.08214373 -15.1960085  13.0317210 1.0000000
## C_SH-B_RO    14.15253480   0.3215417  27.9835279 0.0387283
## D_RO-B_RO    -0.35902827 -14.1900213  13.4719648 1.0000000
## D_SH-B_RO    11.27077136  -2.5602217  25.1017644 0.2729050
## E_RO-B_RO    -0.11112095 -13.9421140  13.7198721 1.0000000
## E_SH-B_RO    27.97553327  14.1445402  41.8065263 0.0000000
## C_RO-B_SH   -12.75884683 -26.2425629   0.7248692 0.0872620
## C_SH-B_SH     2.47583171 -10.7115028  15.6631662 0.9999998
## D_RO-B_SH   -12.03573136 -25.2230658   1.1516031 0.1204629
## D_SH-B_SH    -0.40593174 -13.5932662  12.7814027 1.0000000
## E_RO-B_SH   -11.78782404 -24.9751585   1.3995104 0.1430158
## E_SH-B_SH    16.29883018   3.1114957  29.4861646 0.0026158
## C_SH-C_RO    15.23467853   1.7509625  28.7183946 0.0108227
## D_RO-C_RO     0.72311546 -12.7606006  14.2068315 1.0000000
## D_SH-C_RO    12.35291509  -1.1308010  25.8366312 0.1166320
## E_RO-C_RO     0.97102279 -12.5126933  14.4547389 1.0000000
## E_SH-C_RO    29.05767700  15.5739609  42.5413931 0.0000000
## D_RO-C_SH   -14.51156307 -27.6988975  -1.3242286 0.0156412
## D_SH-C_SH    -2.88176344 -16.0690979  10.3055710 0.9999984
## E_RO-C_SH   -14.26365575 -27.4509902  -1.0763213 0.0196637
## E_SH-C_SH    13.82299847   0.6356640  27.0103329 0.0291665
## D_SH-D_RO    11.62979963  -1.5575348  24.8171341 0.1589969
## E_RO-D_RO     0.24790732 -12.9394271  13.4352418 1.0000000
## E_SH-D_RO    28.33456154  15.1472271  41.5218960 0.0000000
## E_RO-D_SH   -11.38189231 -24.5692268   1.8054422 0.1867000
## E_SH-D_SH    16.70476191   3.5174274  29.8920964 0.0016890
## E_SH-E_RO    28.08665422  14.8993198  41.2739887 0.0000000
P5 = Output$All.ID[,'p adj']
stat.test<- multcompLetters(P5)
stat.test
##   1B_SH   1C_RO   1C_SH   1D_RO   1D_SH   1E_RO   1E_SH    A_RO    A_SH    B_RO 
##   "abc"   "def"  "abde"  "bdef"   "abc"   "def"    "ac"   "def"  "abde"    "ef" 
##    B_SH    C_RO    C_SH    D_RO    D_SH    E_RO    E_SH   1B_RO 
## "abdef"     "f"   "abd"     "f" "abdef"     "f"     "c"   "def"
test <- as.data.frame(stat.test$Letters)
test$group1 <- rownames(test)
#test$group2 <- rownames(test)
colnames(test)[1] <- "Tukey"
test
test$info <- strsplit(test$group1, "_")
test$info[[1]][2]
## [1] "SH"
test$Accession <- "none"
test$Tissue<- "none"
test
for(i in 1:nrow(test)){
  test$Accession[i] <- test$info[[i]][1]
     test$Tissue[i] <- test$info[[i]][2]
  
}

test2 <- test[,c(4:5,1)]
test2$group1 <- test2$Accession
test2$group2 <- test2$Accession
ICP
ICP$Accession<- factor(ICP$Accession, levels=c("A", "D", "E",  "1D", "1E" , "B", "C", "1B" , "1C" ))


ICP2 <- subset(ICP, ICP$Na.con.mg.mg.dry.weight < 40 & ICP$Na.con.mg.mg.dry.weight > 5)

Na_content <- ggplot(data = ICP2, mapping = aes(x = Accession, y = Na.con.mg.mg.dry.weight, colour = Accession)) 
Na_content <- Na_content + geom_boxplot(alpha=0.2) + geom_jitter(width=0.1,alpha=0.2)

Na_content <- Na_content + facet_grid(~Tissue , scales = "free_y")

Na_content <- Na_content + stat_summary(fun=mean, geom="point", shape=95, size=6, color="black", fill="black")
Na_content <- Na_content + scale_color_manual(values = c("blue", "plum", "darkorchid1","cyan1", "darkturquoise","red","hotpink","deeppink", "darkgoldenrod","darkorange" ))
Na_content <- Na_content + ylab("Na content, mg/mg dry weight") + xlab("")+stat_pvalue_manual(test2, label = "Tukey", y.position = 40)
Na_content <- Na_content + theme(axis.text.x = element_text(angle=90, hjust=0.9, vjust=0.5))
Na_content <- Na_content + rremove("legend")
Na_content

aov(K.con..mg.mg.dry.weight ~ All.ID, data = ICP)
## Call:
##    aov(formula = K.con..mg.mg.dry.weight ~ All.ID, data = ICP)
## 
## Terms:
##                    All.ID Residuals
## Sum of Squares   19599.13 155747.29
## Deg. of Freedom        17       195
## 
## Residual standard error: 28.26135
## Estimated effects may be unbalanced
Output <- TukeyHSD(aov(K.con..mg.mg.dry.weight ~ All.ID, data = ICP))
Output
##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = K.con..mg.mg.dry.weight ~ All.ID, data = ICP)
## 
## $All.ID
##                    diff         lwr      upr     p adj
## 1B_SH-1B_RO   6.4984471 -38.4218892 51.41878 1.0000000
## 1C_RO-1B_RO  -0.2532144 -45.1735508 44.66712 1.0000000
## 1C_SH-1B_RO  11.2042936 -33.7160428 56.12463 0.9999887
## 1D_RO-1B_RO  11.3344264 -39.0313248 61.70018 0.9999975
## 1D_SH-1B_RO   9.9746172 -40.3911340 60.34037 0.9999996
## 1E_RO-1B_RO   2.5866786 -43.3332437 48.50660 1.0000000
## 1E_SH-1B_RO   7.7998617 -37.1204747 52.72020 1.0000000
## A_RO-1B_RO    4.8631872 -34.6820196 44.40839 1.0000000
## A_SH-1B_RO   12.4851517 -27.3324707 52.30277 0.9997276
## B_RO-1B_RO   -1.9568267 -47.8767491 43.96310 1.0000000
## B_SH-1B_RO   12.3665520 -31.7034803 56.43658 0.9999396
## C_RO-1B_RO    0.9257743 -43.9945620 45.84611 1.0000000
## C_SH-1B_RO    8.5686200 -35.5014122 52.63865 0.9999997
## D_RO-1B_RO    3.1065215 -40.9635107 47.17655 1.0000000
## D_SH-1B_RO   13.0191286 -31.0509037 57.08916 0.9998774
## E_RO-1B_RO   -1.0776816 -45.1477139 42.99235 1.0000000
## E_SH-1B_RO   41.8551643  -2.2148680 85.92520 0.0842795
## 1C_RO-1B_SH  -6.7516615 -49.3668344 35.86351 1.0000000
## 1C_SH-1B_SH   4.7058465 -37.9093264 47.32102 1.0000000
## 1D_RO-1B_SH   4.8359793 -43.4850847 53.15704 1.0000000
## 1D_SH-1B_SH   3.4761701 -44.8448939 51.79723 1.0000000
## 1E_RO-1B_SH  -3.9117685 -47.5793263 39.75579 1.0000000
## 1E_SH-1B_SH   1.3014146 -41.3137583 43.91659 1.0000000
## A_RO-1B_SH   -1.6352599 -38.5410822 35.27056 1.0000000
## A_SH-1B_SH    5.9867046 -31.2108678 43.18428 1.0000000
## B_RO-1B_SH   -8.4552738 -52.1228316 35.21228 0.9999997
## B_SH-1B_SH    5.8681049 -35.8498059 47.58602 1.0000000
## C_RO-1B_SH   -5.5726728 -48.1878456 37.04250 1.0000000
## C_SH-1B_SH    2.0701729 -39.6477379 43.78808 1.0000000
## D_RO-1B_SH   -3.3919256 -45.1098364 38.32599 1.0000000
## D_SH-1B_SH    6.5206815 -35.1972293 48.23859 1.0000000
## E_RO-1B_SH   -7.5761287 -49.2940395 34.14178 0.9999999
## E_SH-1B_SH   35.3567172  -6.3611936 77.07463 0.2121527
## 1C_SH-1C_RO  11.4575080 -31.1576648 54.07268 0.9999668
## 1D_RO-1C_RO  11.5876408 -36.7334232 59.90870 0.9999936
## 1D_SH-1C_RO  10.2278316 -38.0932324 58.54890 0.9999990
## 1E_RO-1C_RO   2.8398931 -40.8276647 46.50745 1.0000000
## 1E_SH-1C_RO   8.0530761 -34.5620967 50.66825 0.9999998
## A_RO-1C_RO    5.1164016 -31.7894206 42.02222 1.0000000
## A_SH-1C_RO   12.7383662 -24.4592063 49.93594 0.9991513
## B_RO-1C_RO   -1.7036123 -45.3711701 41.96395 1.0000000
## B_SH-1C_RO   12.6197664 -29.0981444 54.33768 0.9998312
## C_RO-1C_RO    1.1789888 -41.4361841 43.79416 1.0000000
## C_SH-1C_RO    8.8218345 -32.8960763 50.53975 0.9999990
## D_RO-1C_RO    3.3597360 -38.3581748 45.07765 1.0000000
## D_SH-1C_RO   13.2723430 -28.4455678 54.99025 0.9996702
## E_RO-1C_RO   -0.8244672 -42.5423780 40.89344 1.0000000
## E_SH-1C_RO   42.1083787   0.3904679 83.82629 0.0451597
## 1D_RO-1C_SH   0.1301328 -48.1909312 48.45120 1.0000000
## 1D_SH-1C_SH  -1.2296764 -49.5507404 47.09139 1.0000000
## 1E_RO-1C_SH  -8.6176149 -52.2851727 35.04994 0.9999997
## 1E_SH-1C_SH  -3.4044319 -46.0196047 39.21074 1.0000000
## A_RO-1C_SH   -6.3411064 -43.2469286 30.56472 1.0000000
## A_SH-1C_SH    1.2808582 -35.9167143 38.47843 1.0000000
## B_RO-1C_SH  -13.1611203 -56.8286781 30.50644 0.9998393
## B_SH-1C_SH    1.1622584 -40.5556524 42.88017 1.0000000
## C_RO-1C_SH  -10.2785192 -52.8936921 32.33665 0.9999931
## C_SH-1C_SH   -2.6356735 -44.3535843 39.08224 1.0000000
## D_RO-1C_SH   -8.0977720 -49.8156828 33.62014 0.9999997
## D_SH-1C_SH    1.8148350 -39.9030758 43.53275 1.0000000
## E_RO-1C_SH  -12.2819752 -53.9998860 29.43594 0.9998830
## E_SH-1C_SH   30.6508707 -11.0670401 72.36878 0.4601464
## 1D_SH-1D_RO  -1.3598092 -54.7807555 52.06114 1.0000000
## 1E_RO-1D_RO  -8.7477478 -57.9994267 40.50393 0.9999999
## 1E_SH-1D_RO  -3.5345647 -51.8556288 44.78650 1.0000000
## A_RO-1D_RO   -6.4712392 -49.8407214 36.89824 1.0000000
## A_SH-1D_RO    1.1507253 -42.4672946 44.76875 1.0000000
## B_RO-1D_RO  -13.2912531 -62.5429320 35.96043 0.9999650
## B_SH-1D_RO    1.0321256 -46.4995097 48.56376 1.0000000
## C_RO-1D_RO  -10.4086521 -58.7297161 37.91241 0.9999987
## C_SH-1D_RO   -2.7658064 -50.2974417 44.76583 1.0000000
## D_RO-1D_RO   -8.2279049 -55.7595402 39.30373 1.0000000
## D_SH-1D_RO    1.6847022 -45.8469331 49.21634 1.0000000
## E_RO-1D_RO  -12.4121080 -59.9437433 35.11953 0.9999781
## E_SH-1D_RO   30.5207379 -17.0108974 78.05237 0.7030576
## 1E_RO-1D_SH  -7.3879386 -56.6396175 41.86374 1.0000000
## 1E_SH-1D_SH  -2.1747555 -50.4958196 46.14631 1.0000000
## A_RO-1D_SH   -5.1114300 -48.4809122 38.25805 1.0000000
## A_SH-1D_SH    2.5105345 -41.1074854 46.12855 1.0000000
## B_RO-1D_SH  -11.9314439 -61.1831228 37.32023 0.9999926
## B_SH-1D_SH    2.3919348 -45.1397005 49.92357 1.0000000
## C_RO-1D_SH   -9.0488429 -57.3699069 39.27222 0.9999998
## C_SH-1D_SH   -1.4059972 -48.9376325 46.12564 1.0000000
## D_RO-1D_SH   -6.8680957 -54.3997310 40.66354 1.0000000
## D_SH-1D_SH    3.0445114 -44.4871239 50.57615 1.0000000
## E_RO-1D_SH  -11.0522988 -58.5839341 36.47934 0.9999960
## E_SH-1D_SH   31.8805471 -15.6510882 79.41218 0.6297127
## 1E_SH-1E_RO   5.2131830 -38.4543747 48.88074 1.0000000
## A_RO-1E_RO    2.2765086 -35.8396608 40.39268 1.0000000
## A_SH-1E_RO    9.8984731 -28.5002514 48.29720 0.9999818
## B_RO-1E_RO   -4.5435053 -49.2386757 40.15166 1.0000000
## B_SH-1E_RO    9.7798734 -33.0124943 52.57224 0.9999969
## C_RO-1E_RO   -1.6609043 -45.3284621 42.00665 1.0000000
## C_SH-1E_RO    5.9819414 -36.8104262 48.77431 1.0000000
## D_RO-1E_RO    0.5198429 -42.2725248 43.31221 1.0000000
## D_SH-1E_RO   10.4324500 -32.3599177 53.22482 0.9999919
## E_RO-1E_RO   -3.6643602 -46.4567279 39.12801 1.0000000
## E_SH-1E_RO   39.2684857  -3.5238820 82.06085 0.1149854
## A_RO-1E_SH   -2.9366745 -39.8424967 33.96915 1.0000000
## A_SH-1E_SH    4.6852901 -32.5122824 41.88286 1.0000000
## B_RO-1E_SH   -9.7566884 -53.4242462 33.91087 0.9999978
## B_SH-1E_SH    4.5666903 -37.1512205 46.28460 1.0000000
## C_RO-1E_SH   -6.8740873 -49.4892602 35.74109 1.0000000
## C_SH-1E_SH    0.7687584 -40.9491524 42.48667 1.0000000
## D_RO-1E_SH   -4.6933401 -46.4112509 37.02457 1.0000000
## D_SH-1E_SH    5.2192669 -36.4986439 46.93718 1.0000000
## E_RO-1E_SH   -8.8775433 -50.5954541 32.84037 0.9999989
## E_SH-1E_SH   34.0553026  -7.6626082 75.77321 0.2700321
## A_SH-A_RO     7.6219645 -22.8681348 38.11206 0.9999883
## B_RO-A_RO    -6.8200139 -44.9361833 31.29616 0.9999999
## B_SH-A_RO     7.5033648 -28.3626476 43.36938 0.9999992
## C_RO-A_RO    -3.9374129 -40.8432351 32.96841 1.0000000
## C_SH-A_RO     3.7054328 -32.1605795 39.57145 1.0000000
## D_RO-A_RO    -1.7566657 -37.6226780 34.10935 1.0000000
## D_SH-A_RO     8.1559414 -27.7100710 44.02195 0.9999971
## E_RO-A_RO    -5.9408688 -41.8068812 29.92514 1.0000000
## E_SH-A_RO    36.9919771   1.1259647 72.85799 0.0353416
## B_RO-A_SH   -14.4419785 -52.8407030 23.95675 0.9973416
## B_SH-A_SH    -0.1185997 -36.2847513 36.04755 1.0000000
## C_RO-A_SH   -11.5593774 -48.7569498 25.63820 0.9997581
## C_SH-A_SH    -3.9165317 -40.0826833 32.24962 1.0000000
## D_RO-A_SH    -9.3786302 -45.5447818 26.78752 0.9999802
## D_SH-A_SH     0.5339768 -35.6321748 36.70013 1.0000000
## E_RO-A_SH   -13.5628333 -49.7289849 22.60332 0.9974311
## E_SH-A_SH    29.3700125  -6.7961391 65.53616 0.2785945
## B_SH-B_RO    14.3233787 -28.4689889 57.11575 0.9993643
## C_RO-B_RO     2.8826011 -40.7849567 46.55016 1.0000000
## C_SH-B_RO    10.5254468 -32.2669209 53.31781 0.9999908
## D_RO-B_RO     5.0633483 -37.7290194 47.85572 1.0000000
## D_SH-B_RO    14.9759553 -27.8164123 57.76832 0.9988872
## E_RO-B_RO     0.8791451 -41.9132225 43.67151 1.0000000
## E_SH-B_RO    43.8119910   1.0196233 86.60436 0.0384784
## C_RO-B_SH   -11.4407777 -53.1586885 30.27713 0.9999561
## C_SH-B_SH    -3.7979320 -44.5988536 37.00299 1.0000000
## D_RO-B_SH    -9.2600305 -50.0609521 31.54089 0.9999972
## D_SH-B_SH     0.6525766 -40.1483451 41.45350 1.0000000
## E_RO-B_SH   -13.4442336 -54.2451553 27.35669 0.9994799
## E_SH-B_SH    29.4886123 -11.3123094 70.28953 0.4914342
## C_SH-C_RO     7.6428457 -34.0750651 49.36076 0.9999999
## D_RO-C_RO     2.1807472 -39.5371636 43.89866 1.0000000
## D_SH-C_RO    12.0933543 -29.6245566 53.81127 0.9999053
## E_RO-C_RO    -2.0034559 -43.7213667 39.71445 1.0000000
## E_SH-C_RO    40.9293899  -0.7885209 82.64730 0.0611492
## D_RO-C_SH    -5.4620985 -46.2630202 35.33882 1.0000000
## D_SH-C_SH     4.4505085 -36.3504131 45.25143 1.0000000
## E_RO-C_SH    -9.6463016 -50.4472233 31.15462 0.9999948
## E_SH-C_SH    33.2865442  -7.5143774 74.08747 0.2710240
## D_SH-D_RO     9.9126071 -30.8883146 50.71353 0.9999923
## E_RO-D_RO    -4.1842031 -44.9851248 36.61672 1.0000000
## E_SH-D_RO    38.7486427  -2.0522789 79.54956 0.0843147
## E_RO-D_SH   -14.0968102 -54.8977319 26.70411 0.9990516
## E_SH-D_SH    28.8360357 -11.9648860 69.63696 0.5338549
## E_SH-E_RO    42.9328459   2.1319242 83.73377 0.0278302
P6 = Output$All.ID[,'p adj']
stat.test<- multcompLetters(P6)
stat.test
## 1B_SH 1C_RO 1C_SH 1D_RO 1D_SH 1E_RO 1E_SH  A_RO  A_SH  B_RO  B_SH  C_RO  C_SH 
##  "ab"   "a"  "ab"  "ab"  "ab"  "ab"  "ab"   "a"  "ab"   "a"  "ab"  "ab"  "ab" 
##  D_RO  D_SH  E_RO  E_SH 1B_RO 
##  "ab"  "ab"   "a"   "b"  "ab"
test <- as.data.frame(stat.test$Letters)
test$group1 <- rownames(test)
#test$group2 <- rownames(test)
colnames(test)[1] <- "Tukey"
test
test$info <- strsplit(test$group1, "_")
test$info[[1]][2]
## [1] "SH"
test$Accession <- "none"
test$Tissue<- "none"
test
for(i in 1:nrow(test)){
  test$Accession[i] <- test$info[[i]][1]
     test$Tissue[i] <- test$info[[i]][2]
  
}

test2 <- test[,c(4:5,1)]
test2$group1 <- test2$Accession
test2$group2 <- test2$Accession
ICP
ICP3 <- subset(ICP, ICP$K.con..mg.mg.dry.weight < 70 & ICP$K.con..mg.mg.dry.weight > 30)

k_content <- ggplot(data = ICP3, mapping = aes(x = Accession, y = K.con..mg.mg.dry.weight, colour = Accession)) 
k_content <- k_content + geom_boxplot(alpha=0.2) + geom_jitter(width=0.1,alpha=0.2)

k_content <- k_content + facet_grid(~Tissue , scales = "free_y")

k_content <- k_content + stat_summary(fun=mean, geom="point", shape=95, size=6, color="black", fill="black")
k_content <- k_content + scale_color_manual(values = c("blue", "plum", "darkorchid1","cyan1", "darkturquoise","red","hotpink","deeppink", "darkgoldenrod","darkorange" ))
k_content <- k_content + ylab("K content, mg/mg dry weight") + xlab("")+stat_pvalue_manual(test2, label = "Tukey", y.position = 65)
k_content <- k_content + theme(axis.text.x = element_text(angle=90, hjust=0.9, vjust=0.5))
k_content <- k_content + rremove("legend")
k_content

aov(Na.K.ratio ~ All.ID, data = ICP)
## Call:
##    aov(formula = Na.K.ratio ~ All.ID, data = ICP)
## 
## Terms:
##                   All.ID Residuals
## Sum of Squares  5.003694  9.595997
## Deg. of Freedom       17       195
## 
## Residual standard error: 0.2218338
## Estimated effects may be unbalanced
Output <- TukeyHSD(aov(Na.K.ratio ~ All.ID, data = ICP))
Output
##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = Na.K.ratio ~ All.ID, data = ICP)
## 
## $All.ID
##                     diff           lwr           upr     p adj
## 1B_SH-1B_RO  0.353315610  0.0007192752  0.7059119449 0.0489085
## 1C_RO-1B_RO -0.019860266 -0.3724566006  0.3327360692 1.0000000
## 1C_SH-1B_RO  0.147557103 -0.2050392321  0.5001534377 0.9911351
## 1D_RO-1B_RO  0.006685744 -0.3886536660  0.4020251538 1.0000000
## 1D_SH-1B_RO  0.301253265 -0.0940861449  0.6965926750 0.3913240
## 1E_RO-1B_RO  0.013463658 -0.3469787966  0.3739061131 1.0000000
## 1E_SH-1B_RO  0.441176073  0.0885797382  0.7937724079 0.0021082
## A_RO-1B_RO  -0.024419270 -0.3348242249  0.2859856845 1.0000000
## A_SH-1B_RO   0.091793304 -0.2207499418  0.4043365503 0.9998868
## B_RO-1B_RO  -0.040142737 -0.4005851914  0.3202997183 1.0000000
## B_SH-1B_RO   0.112982474 -0.2329395102  0.4589044572 0.9995358
## C_RO-1B_RO  -0.089766836 -0.4423631711  0.2628294987 0.9999848
## C_SH-1B_RO   0.245584458 -0.1003375254  0.5915064419 0.5253500
## D_RO-1B_RO  -0.087561816 -0.4334838001  0.2583601673 0.9999860
## D_SH-1B_RO   0.093089240 -0.2528327434  0.4390112240 0.9999664
## E_RO-1B_RO  -0.054485446 -0.4004074299  0.2914365375 1.0000000
## E_SH-1B_RO   0.291061434 -0.0548605499  0.6369834175 0.2227678
## 1C_RO-1B_SH -0.373175876 -0.7076781296 -0.0386736219 0.0129523
## 1C_SH-1B_SH -0.205758507 -0.5402607611  0.1287437466 0.7672258
## 1D_RO-1B_SH -0.346629866 -0.7259197705  0.0326600381 0.1191039
## 1D_SH-1B_SH -0.052062345 -0.4313522493  0.3272275593 1.0000000
## 1E_RO-1B_SH -0.339851952 -0.6826147645  0.0029108608 0.0547723
## 1E_SH-1B_SH  0.087860463 -0.2466417909  0.4223627169 0.9999762
## A_RO-1B_SH  -0.377734880 -0.6674223297 -0.0880474308 0.0009813
## A_SH-1B_SH  -0.261522306 -0.5534998103  0.0304551986 0.1407015
## B_RO-1B_SH  -0.393458347 -0.7362211593 -0.0506955340 0.0085863
## B_SH-1B_SH  -0.240333137 -0.5677924489  0.0871261758 0.4621798
## C_RO-1B_SH  -0.443082446 -0.7775847001 -0.1085801924 0.0007211
## C_SH-1B_SH  -0.107731152 -0.4351904642  0.2197281606 0.9994903
## D_RO-1B_SH  -0.440877426 -0.7683367389 -0.1134181141 0.0005189
## D_SH-1B_SH  -0.260226370 -0.5876856821  0.0672329426 0.3154412
## E_RO-1B_SH  -0.407801056 -0.7352603686 -0.0803417439 0.0022913
## E_SH-1B_SH  -0.062254176 -0.3897134886  0.2652051361 0.9999998
## 1C_SH-1C_RO  0.167417368 -0.1670848854  0.5019196223 0.9490775
## 1D_RO-1C_RO  0.026546010 -0.3527438947  0.4058359139 1.0000000
## 1D_SH-1C_RO  0.321113531 -0.0581763736  0.7004034350 0.2136959
## 1E_RO-1C_RO  0.033323924 -0.3094388887  0.3760867365 1.0000000
## 1E_SH-1C_RO  0.461036339  0.1265340849  0.7955385926 0.0003173
## A_RO-1C_RO  -0.004559005 -0.2942464540  0.2851284449 1.0000000
## A_SH-1C_RO   0.111653570 -0.1803239346  0.4036310744 0.9967711
## B_RO-1C_RO  -0.020282471 -0.3630452835  0.3224803417 1.0000000
## B_SH-1C_RO   0.132842739 -0.1946165732  0.4603020515 0.9936856
## C_RO-1C_RO  -0.069906571 -0.4044088244  0.2645956833 0.9999992
## C_SH-1C_RO   0.265444724 -0.0620145885  0.5929040363 0.2815961
## D_RO-1C_RO  -0.067701551 -0.3951608631  0.2597577616 0.9999993
## D_SH-1C_RO   0.112949506 -0.2145098064  0.4404088184 0.9990711
## E_RO-1C_RO  -0.034625181 -0.3620844929  0.2928341319 1.0000000
## E_SH-1C_RO   0.310921699 -0.0165376129  0.6383810119 0.0844854
## 1D_RO-1C_SH -0.140871359 -0.5201612632  0.2384185454 0.9977090
## 1D_SH-1C_SH  0.153696162 -0.2255937420  0.5329860666 0.9937638
## 1E_RO-1C_SH -0.134093445 -0.4768562572  0.2086693681 0.9958020
## 1E_SH-1C_SH  0.293618970 -0.0408832836  0.6281212241 0.1647798
## A_RO-1C_SH  -0.171976373 -0.4616638225  0.1177110765 0.8133209
## A_SH-1C_SH  -0.055763799 -0.3477413030  0.2362137059 0.9999998
## B_RO-1C_SH  -0.187699839 -0.5304626520  0.1550629733 0.8940429
## B_SH-1C_SH  -0.034574629 -0.3620339417  0.2928846831 1.0000000
## C_RO-1C_SH  -0.237323939 -0.5718261929  0.0971783149 0.5265692
## C_SH-1C_SH   0.098027355 -0.2294319569  0.4254866678 0.9998533
## D_RO-1C_SH  -0.235118919 -0.5625782316  0.0923403932 0.5039321
## D_SH-1C_SH  -0.054467862 -0.3819271748  0.2729914499 1.0000000
## E_RO-1C_SH  -0.202042549 -0.5295018613  0.1254167634 0.7629581
## E_SH-1C_SH   0.143504331 -0.1839549813  0.4709636434 0.9856051
## 1D_SH-1D_RO  0.294567521 -0.1247532453  0.7138882876 0.5452286
## 1E_RO-1D_RO  0.006777914 -0.3798167305  0.3933725591 1.0000000
## 1E_SH-1D_RO  0.434490329  0.0552004249  0.8137802335 0.0088531
## A_RO-1D_RO  -0.031105014 -0.3715281215  0.3093180933 1.0000000
## A_SH-1D_RO   0.085107560 -0.2572664118  0.4274815325 0.9999892
## B_RO-1D_RO  -0.046828480 -0.4334231253  0.3397661643 1.0000000
## B_SH-1D_RO   0.106296730 -0.2667966567  0.4793901159 0.9999254
## C_RO-1D_RO  -0.096452580 -0.4757424844  0.2828373242 0.9999850
## C_SH-1D_RO   0.238898714 -0.1341946720  0.6119921007 0.7075036
## D_RO-1D_RO  -0.094247560 -0.4673409467  0.2788458260 0.9999864
## D_SH-1D_RO   0.086403496 -0.2866898899  0.4594968828 0.9999962
## E_RO-1D_RO  -0.061171190 -0.4342645764  0.3119221963 1.0000000
## E_SH-1D_RO   0.284375690 -0.0887176964  0.6574690763 0.3908388
## 1E_RO-1D_SH -0.287789607 -0.6743842516  0.0988050380 0.4352200
## 1E_SH-1D_SH  0.139922808 -0.2393670963  0.5192127123 0.9978863
## A_RO-1D_SH  -0.325672535 -0.6660956427  0.0147505721 0.0786256
## A_SH-1D_SH  -0.209459961 -0.5518339329  0.1329140113 0.7746959
## B_RO-1D_SH  -0.341396002 -0.7279906464  0.0451986432 0.1573474
## B_SH-1D_SH  -0.188270792 -0.5613641779  0.1848225948 0.9453237
## C_RO-1D_SH  -0.391020101 -0.7703100056 -0.0117301970 0.0355285
## C_SH-1D_SH  -0.055668807 -0.4287621931  0.3174245795 1.0000000
## D_RO-1D_SH  -0.388815081 -0.7619084678 -0.0157216951 0.0312742
## D_SH-1D_SH  -0.208164025 -0.5812574111  0.1649293616 0.8782470
## E_RO-1D_SH  -0.355738711 -0.7288320976  0.0173546751 0.0811850
## E_SH-1D_SH  -0.010191831 -0.3832852176  0.3629015551 1.0000000
## 1E_SH-1E_RO  0.427712415  0.0849496022  0.7704752275 0.0022119
## A_RO-1E_RO  -0.037882928 -0.3370708398  0.2613049829 1.0000000
## A_SH-1E_RO   0.078329646 -0.2230761453  0.3797354373 0.9999795
## B_RO-1E_RO  -0.053606395 -0.4044353184  0.2972225288 1.0000000
## B_SH-1E_RO   0.099518815 -0.2363743064  0.4354119369 0.9998725
## C_RO-1E_RO  -0.103230494 -0.4459933071  0.2395323182 0.9998409
## C_SH-1E_RO   0.232120800 -0.1037723216  0.5680139216 0.5757652
## D_RO-1E_RO  -0.101025475 -0.4369185963  0.2348676470 0.9998437
## D_SH-1E_RO   0.079625582 -0.2562675395  0.4155187037 0.9999946
## E_RO-1E_RO  -0.067949104 -0.4038422260  0.2679440172 0.9999995
## E_SH-1E_RO   0.277597776 -0.0582953460  0.6134908972 0.2502475
## A_RO-1E_SH  -0.465595343 -0.7552827927 -0.1759078938 0.0000071
## A_SH-1E_SH  -0.349382769 -0.6413602733 -0.0574052644 0.0045016
## B_RO-1E_SH  -0.481318810 -0.8240816223 -0.1385559970 0.0002112
## B_SH-1E_SH  -0.328193600 -0.6556529119 -0.0007342872 0.0488013
## C_RO-1E_SH  -0.530942909 -0.8654451631 -0.1964406554 0.0000100
## C_SH-1E_SH  -0.195591615 -0.5230509272  0.1318676976 0.8058528
## D_RO-1E_SH  -0.528737889 -0.8561972019 -0.2012785771 0.0000062
## D_SH-1E_SH  -0.348086833 -0.6755461451 -0.0206275204 0.0245458
## E_RO-1E_SH  -0.495661519 -0.8231208316 -0.1682022069 0.0000354
## E_SH-1E_SH  -0.150114639 -0.4775739516  0.1773446731 0.9773972
## A_SH-A_RO    0.116212574 -0.1231154926  0.3555406415 0.9611059
## B_RO-A_RO   -0.015723466 -0.3149113777  0.2834644450 1.0000000
## B_SH-A_RO    0.137401744 -0.1441238534  0.4189273408 0.9592670
## C_RO-A_RO   -0.065347566 -0.3550350155  0.2243398835 0.9999974
## C_SH-A_RO    0.270003728 -0.0115218686  0.5515293255 0.0767392
## D_RO-A_RO   -0.063142546 -0.3446681433  0.2183830509 0.9999976
## D_SH-A_RO    0.117508511 -0.1640170865  0.3990341076 0.9913803
## E_RO-A_RO   -0.030066176 -0.3115917730  0.2514594211 1.0000000
## E_SH-A_RO    0.315480704  0.0339551070  0.5970063011 0.0121652
## B_RO-A_SH   -0.131936041 -0.4333418321  0.1694697505 0.9857729
## B_SH-A_SH    0.021189169 -0.2626923316  0.3050706701 1.0000000
## C_RO-A_SH   -0.181560140 -0.4735376449  0.1104173640 0.7518561
## C_SH-A_SH    0.153791154 -0.1300903469  0.4376726549 0.9023997
## D_RO-A_SH   -0.179355121 -0.4632366215  0.1045263802 0.7282896
## D_SH-A_SH    0.001295936 -0.2825855648  0.2851774370 1.0000000
## E_RO-A_SH   -0.146278750 -0.4301602513  0.1376027505 0.9347132
## E_SH-A_SH    0.199268130 -0.0846133713  0.4831496305 0.5466869
## B_SH-B_RO    0.153125210 -0.1827679116  0.4890183317 0.9785982
## C_RO-B_RO   -0.049624100 -0.3923869123  0.2931387130 1.0000000
## C_SH-B_RO    0.285727195 -0.0501659268  0.6216203164 0.2068527
## D_RO-B_RO   -0.047419080 -0.3833122015  0.2884740418 1.0000000
## D_SH-B_RO    0.133231977 -0.2026611447  0.4691250985 0.9950899
## E_RO-B_RO   -0.014342710 -0.3502358312  0.3215504120 1.0000000
## E_SH-B_RO    0.331204170 -0.0046889512  0.6670972920 0.0580471
## C_RO-B_SH   -0.202749310 -0.5302086221  0.1247100027 0.7580225
## C_SH-B_SH    0.132601985 -0.1876595407  0.4528635102 0.9921014
## D_RO-B_SH   -0.200544290 -0.5208058154  0.1197172355 0.7416510
## D_SH-B_SH   -0.019893233 -0.3401547586  0.3003682923 1.0000000
## E_RO-B_SH   -0.167467920 -0.4877294451  0.1527936058 0.9262889
## E_SH-B_SH    0.178078960 -0.1421825651  0.4983404858 0.8812519
## C_SH-C_RO    0.335351294  0.0078919821  0.6628106068 0.0383609
## D_RO-C_RO    0.002205020 -0.3252542926  0.3296643322 1.0000000
## D_SH-C_RO    0.182856077 -0.1446032358  0.5103153889 0.8774996
## E_RO-C_RO    0.035281390 -0.2921779223  0.3627407024 1.0000000
## E_SH-C_RO    0.380828270  0.0533689577  0.7082875824 0.0070534
## D_RO-C_SH   -0.333146275 -0.6534078001 -0.0128847492 0.0319643
## D_SH-C_SH   -0.152495218 -0.4727567434  0.1677663075 0.9675251
## E_RO-C_SH   -0.300069904 -0.6203314299  0.0201916210 0.0955970
## E_SH-C_SH    0.045476976 -0.2747845499  0.3657385010 1.0000000
## D_SH-D_RO    0.180651057 -0.1396104687  0.5009125822 0.8682261
## E_RO-D_RO    0.033076370 -0.2871851552  0.3533378957 1.0000000
## E_SH-D_RO    0.378623250  0.0583617248  0.6988847757 0.0054638
## E_RO-D_SH   -0.147574687 -0.4678362120  0.1726868390 0.9762323
## E_SH-D_SH    0.197972193 -0.1222893320  0.5182337190 0.7603167
## E_SH-E_RO    0.345546880  0.0252853545  0.6658084055 0.0203040
P7 = Output$All.ID[,'p adj']
stat.test<- multcompLetters(P7)
stat.test
##   1B_SH   1C_RO   1C_SH   1D_RO   1D_SH   1E_RO   1E_SH    A_RO    A_SH    B_RO 
##    "ab"   "cde" "abcde"  "acde"  "abcd"  "acde"     "b"    "ce"  "acde"   "cde" 
##    B_SH    C_RO    C_SH    D_RO    D_SH    E_RO    E_SH   1B_RO 
##  "acde"     "e"  "abcd"     "e"  "acde"    "ce"   "abd"   "cde"
test <- as.data.frame(stat.test$Letters)
test$group1 <- rownames(test)
#test$group2 <- rownames(test)
colnames(test)[1] <- "Tukey"
test
test$info <- strsplit(test$group1, "_")
test$info[[1]][2]
## [1] "SH"
test$Accession <- "none"
test$Tissue<- "none"
test
for(i in 1:nrow(test)){
  test$Accession[i] <- test$info[[i]][1]
     test$Tissue[i] <- test$info[[i]][2]
  
}

test2 <- test[,c(4:5,1)]
test2$group1 <- test2$Accession
test2$group2 <- test2$Accession
ICP
ICP4 <- subset(ICP, ICP$Na.K.ratio < 0.7 & ICP$Na.K.ratio > 0.25)

ratio <- ggplot(data = ICP4, mapping = aes(x = Accession, y = Na.K.ratio, colour = Accession)) 
ratio <- ratio + geom_boxplot(alpha=0.2) + geom_jitter(width=0.1,alpha=0.2)

ratio <- ratio + facet_grid(~Tissue , scales = "free_y")

ratio <- ratio + stat_summary(fun=mean, geom="point", shape=95, size=6, color="black", fill="black")
ratio <- ratio + scale_color_manual(values = c("blue", "plum", "darkorchid1","cyan1", "darkturquoise","red","hotpink","deeppink", "darkgoldenrod","darkorange" ))
ratio <- ratio + ylab("Na/K ratio, mg/mg dry weight") + xlab("")+stat_pvalue_manual(test2, label = "Tukey", y.position = 1)
ratio <- ratio + theme(axis.text.x = element_text(angle=90, hjust=0.9, vjust=0.5))
ratio <- ratio + rremove("legend")
ratio

pdf("all-ICP.pdf", height = 8, width = 12)
plot_grid(Na_content, k_content, ratio, ncol=2,
          align = "hv", labels=c("AUTO"), 
          label_size = 24)
dev.off()
## png 
##   2
aov(DW.mg ~ All.ID, data = ICP)
## Call:
##    aov(formula = DW.mg ~ All.ID, data = ICP)
## 
## Terms:
##                    All.ID Residuals
## Sum of Squares   343.3993 1588.7332
## Deg. of Freedom        17       195
## 
## Residual standard error: 2.854356
## Estimated effects may be unbalanced
Output <- TukeyHSD(aov(DW.mg ~ All.ID, data = ICP))
Output
##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = DW.mg ~ All.ID, data = ICP)
## 
## $All.ID
##                     diff         lwr         upr     p adj
## 1B_SH-1B_RO  1.602020202 -2.93486965  6.13891006 0.9987573
## 1C_RO-1B_RO -0.170707071 -4.70759693  4.36618279 1.0000000
## 1C_SH-1B_RO  1.338383838 -3.19850602  5.87527370 0.9998798
## 1D_RO-1B_RO -0.317460317 -5.40432930  4.76940866 1.0000000
## 1D_SH-1B_RO  1.153968254 -3.93290073  6.24083724 0.9999972
## 1E_RO-1B_RO -0.078888889 -4.71673550  4.55895772 1.0000000
## 1E_SH-1B_RO  1.274747475 -3.26214238  5.81163733 0.9999385
## A_RO-1B_RO   0.011111111 -3.98289833  4.00512055 1.0000000
## A_SH-1B_RO   3.858730159 -0.16279288  7.88025319 0.0763932
## B_RO-1B_RO  -0.098888889 -4.73673550  4.53895772 1.0000000
## B_SH-1B_RO   2.111111111 -2.33989925  6.56212147 0.9686912
## C_RO-1B_RO  -0.243434343 -4.78032420  4.29345551 1.0000000
## C_SH-1B_RO   1.402777778 -3.04823258  5.85378814 0.9997087
## D_RO-1B_RO  -0.005555556 -4.45656591  4.44545480 1.0000000
## D_SH-1B_RO   2.227777778 -2.22323258  6.67878814 0.9490654
## E_RO-1B_RO  -0.188888889 -4.63989925  4.26212147 1.0000000
## E_SH-1B_RO   1.511111111 -2.93989925  5.96212147 0.9992390
## 1C_RO-1B_SH -1.772727273 -6.07679890  2.53134436 0.9925409
## 1C_SH-1B_SH -0.263636364 -4.56770800  4.04043527 1.0000000
## 1D_RO-1B_SH -1.919480519 -6.79983902  2.96087798 0.9955388
## 1D_SH-1B_SH -0.448051948 -5.32841045  4.43230655 1.0000000
## 1E_RO-1B_SH -1.680909091 -6.09127010  2.72945192 0.9968945
## 1E_SH-1B_SH -0.327272727 -4.63134436  3.97679890 1.0000000
## A_RO-1B_SH  -1.590909091 -5.31834446  2.13652628 0.9890658
## A_SH-1B_SH   2.256709957 -1.50019177  6.01361168 0.7987767
## B_RO-1B_SH  -1.700909091 -6.11127010  2.70945192 0.9964375
## B_SH-1B_SH   0.509090909 -3.70435854  4.72254036 1.0000000
## C_RO-1B_SH  -1.845454545 -6.14952618  2.45861709 0.9885259
## C_SH-1B_SH  -0.199242424 -4.41269187  4.01420702 1.0000000
## D_RO-1B_SH  -1.607575758 -5.82102521  2.60587369 0.9968556
## D_SH-1B_SH   0.625757576 -3.58769187  4.83920702 1.0000000
## E_RO-1B_SH  -1.790909091 -6.00435854  2.42254036 0.9895345
## E_SH-1B_SH  -0.090909091 -4.30435854  4.12254036 1.0000000
## 1C_SH-1C_RO  1.509090909 -2.79498072  5.81316254 0.9988613
## 1D_RO-1C_RO -0.146753247 -5.02711175  4.73360525 1.0000000
## 1D_SH-1C_RO  1.324675325 -3.55568317  6.20503382 0.9999621
## 1E_RO-1C_RO  0.091818182 -4.31854283  4.50217919 1.0000000
## 1E_SH-1C_RO  1.445454545 -2.85861709  5.74952618 0.9993368
## A_RO-1C_RO   0.181818182 -3.54561719  3.90925355 1.0000000
## A_SH-1C_RO   4.029437229  0.27253551  7.78633895 0.0219213
## B_RO-1C_RO   0.071818182 -4.33854283  4.48217919 1.0000000
## B_SH-1C_RO   2.281818182 -1.93163127  6.49526763 0.9026608
## C_RO-1C_RO  -0.072727273 -4.37679890  4.23134436 1.0000000
## C_SH-1C_RO   1.573484848 -2.63996460  5.78693430 0.9975555
## D_RO-1C_RO   0.165151515 -4.04829793  4.37860096 1.0000000
## D_SH-1C_RO   2.398484848 -1.81496460  6.61193430 0.8594056
## E_RO-1C_RO  -0.018181818 -4.23163127  4.19526763 1.0000000
## E_SH-1C_RO   1.681818182 -2.53163127  5.89526763 0.9947294
## 1D_RO-1C_SH -1.655844156 -6.53620265  3.22451434 0.9992450
## 1D_SH-1C_SH -0.184415584 -5.06477408  4.69594291 1.0000000
## 1E_RO-1C_SH -1.417272727 -5.82763374  2.99308828 0.9996241
## 1E_SH-1C_SH -0.063636364 -4.36770800  4.24043527 1.0000000
## A_RO-1C_SH  -1.327272727 -5.05470810  2.40016265 0.9986225
## A_SH-1C_SH   2.520346320 -1.23655540  6.27724804 0.6293579
## B_RO-1C_SH  -1.437272727 -5.84763374  2.97308828 0.9995490
## B_SH-1C_SH   0.772727273 -3.44072218  4.98617672 0.9999999
## C_RO-1C_SH  -1.581818182 -5.88588981  2.72225345 0.9979797
## C_SH-1C_SH   0.064393939 -4.14905551  4.27784339 1.0000000
## D_RO-1C_SH  -1.343939394 -5.55738884  2.86951005 0.9996589
## D_SH-1C_SH   0.889393939 -3.32405551  5.10284339 0.9999991
## E_RO-1C_SH  -1.527272727 -5.74072218  2.68617672 0.9982893
## E_SH-1C_SH   0.172727273 -4.04072218  4.38617672 1.0000000
## 1D_SH-1D_RO  1.471428571 -3.92401076  6.86686790 0.9999594
## 1E_RO-1D_RO  0.238571429 -4.73577785  5.21292070 1.0000000
## 1E_SH-1D_RO  1.592207792 -3.28815071  6.47256629 0.9995425
## A_RO-1D_RO   0.328571429 -4.05168438  4.70882723 1.0000000
## A_SH-1D_RO   4.176190476 -0.22916729  8.58154824 0.0857701
## B_RO-1D_RO   0.218571429 -4.75577785  5.19292070 1.0000000
## B_SH-1D_RO   2.428571429 -2.37205590  7.22919875 0.9441335
## C_RO-1D_RO   0.074025974 -4.80633252  4.95438447 1.0000000
## C_SH-1D_RO   1.720238095 -3.08038923  6.52086542 0.9985121
## D_RO-1D_RO   0.311904762 -4.48872256  5.11253209 1.0000000
## D_SH-1D_RO   2.545238095 -2.25538923  7.34586542 0.9175849
## E_RO-1D_RO   0.128571429 -4.67205590  4.92919875 1.0000000
## E_SH-1D_RO   1.828571429 -2.97205590  6.62919875 0.9969158
## 1E_RO-1D_SH -1.232857143 -6.20720642  3.74149213 0.9999897
## 1E_SH-1D_SH  0.120779221 -4.75957928  5.00113772 1.0000000
## A_RO-1D_SH  -1.142857143 -5.52311295  3.23739866 0.9999783
## A_SH-1D_SH   2.704761905 -1.70059586  7.11011967 0.7698111
## B_RO-1D_SH  -1.252857143 -6.22720642  3.72149213 0.9999870
## B_SH-1D_SH   0.957142857 -3.84348447  5.75777018 0.9999996
## C_RO-1D_SH  -1.397402597 -6.27776110  3.48295590 0.9999201
## C_SH-1D_SH   0.248809524 -4.55181780  5.04943685 1.0000000
## D_RO-1D_SH  -1.159523810 -5.96015113  3.64110352 0.9999929
## D_SH-1D_SH   1.073809524 -3.72681780  5.87443685 0.9999977
## E_RO-1D_SH  -1.342857143 -6.14348447  3.45777018 0.9999422
## E_SH-1D_SH   0.357142857 -4.44348447  5.15777018 1.0000000
## 1E_SH-1E_RO  1.353636364 -3.05672465  5.76399737 0.9997950
## A_RO-1E_RO   0.090000000 -3.75967870  3.93967870 1.0000000
## A_SH-1E_RO   3.937619048  0.05940268  7.81583542 0.0422953
## B_RO-1E_RO  -0.020000000 -4.53414841  4.49414841 1.0000000
## B_SH-1E_RO   2.190000000 -2.13196806  6.51196806 0.9433452
## C_RO-1E_RO  -0.164545455 -4.57490647  4.24581556 1.0000000
## C_SH-1E_RO   1.481666667 -2.84030139  5.80363472 0.9991397
## D_RO-1E_RO   0.073333333 -4.24863472  4.39530139 1.0000000
## D_SH-1E_RO   2.306666667 -2.01530139  6.62863472 0.9131397
## E_RO-1E_RO  -0.110000000 -4.43196806  4.21196806 1.0000000
## E_SH-1E_RO   1.590000000 -2.73196806  5.91196806 0.9979551
## A_RO-1E_SH  -1.263636364 -4.99107174  2.46379901 0.9992528
## A_SH-1E_SH   2.583982684 -1.17291904  6.34088441 0.5844614
## B_RO-1E_SH  -1.373636364 -5.78399737  3.03672465 0.9997508
## B_SH-1E_SH   0.836363636 -3.37708581  5.04981308 0.9999996
## C_RO-1E_SH  -1.518181818 -5.82225345  2.78588981 0.9987736
## C_SH-1E_SH   0.128030303 -4.08541915  4.34147975 1.0000000
## D_RO-1E_SH  -1.280303030 -5.49375248  2.93314642 0.9998207
## D_SH-1E_SH   0.953030303 -3.26041915  5.16647975 0.9999973
## E_RO-1E_SH  -1.463636364 -5.67708581  2.74981308 0.9989855
## E_SH-1E_SH   0.236363636 -3.97708581  4.44981308 1.0000000
## A_SH-A_RO    3.847619048  0.76816254  6.92707556 0.0021620
## B_RO-A_RO   -0.110000000 -3.95967870  3.73967870 1.0000000
## B_SH-A_RO    2.100000000 -1.52241606  5.72241606 0.8405098
## C_RO-A_RO   -0.254545455 -3.98198083  3.47288992 1.0000000
## C_SH-A_RO    1.391666667 -2.23074939  5.01408273 0.9965925
## D_RO-A_RO   -0.016666667 -3.63908273  3.60574939 1.0000000
## D_SH-A_RO    2.216666667 -1.40574939  5.83908273 0.7743766
## E_RO-A_RO   -0.200000000 -3.82241606  3.42241606 1.0000000
## E_SH-A_RO    1.500000000 -2.12241606  5.12241606 0.9920920
## B_RO-A_SH   -3.957619048 -7.83583542 -0.07940268 0.0399448
## B_SH-A_SH   -1.747619048 -5.40034874  1.90511064 0.9660483
## C_RO-A_SH   -4.102164502 -7.85906623 -0.34526278 0.0173606
## C_SH-A_SH   -2.455952381 -6.10868207  1.19677731 0.6254030
## D_RO-A_SH   -3.864285714 -7.51701541 -0.21155602 0.0260520
## D_SH-A_SH   -1.630952381 -5.28368207  2.02177731 0.9825934
## E_RO-A_SH   -4.047619048 -7.70034874 -0.39488936 0.0142228
## E_SH-A_SH   -2.347619048 -6.00034874  1.30511064 0.7015956
## B_SH-B_RO    2.210000000 -2.11196806  6.53196806 0.9387900
## C_RO-B_RO   -0.144545455 -4.55490647  4.26581556 1.0000000
## C_SH-B_RO    1.501666667 -2.82030139  5.82363472 0.9989827
## D_RO-B_RO    0.093333333 -4.22863472  4.41530139 1.0000000
## D_SH-B_RO    2.326666667 -1.99530139  6.64863472 0.9070559
## E_RO-B_RO   -0.090000000 -4.41196806  4.23196806 1.0000000
## E_SH-B_RO    1.610000000 -2.71196806  5.93196806 0.9976266
## C_RO-B_SH   -2.354545455 -6.56799490  1.85890399 0.8768453
## C_SH-B_SH   -0.708333333 -4.82916819  3.41250152 1.0000000
## D_RO-B_SH   -2.116666667 -6.23750152  2.00416819 0.9364233
## D_SH-B_SH    0.116666667 -4.00416819  4.23750152 1.0000000
## E_RO-B_SH   -2.300000000 -6.42083485  1.82083485 0.8779301
## E_SH-B_SH   -0.600000000 -4.72083485  3.52083485 1.0000000
## C_SH-C_RO    1.646212121 -2.56723733  5.85966157 0.9958640
## D_RO-C_RO    0.237878788 -3.97557066  4.45132824 1.0000000
## D_SH-C_RO    2.471212121 -1.74223733  6.68466157 0.8275663
## E_RO-C_RO    0.054545455 -4.15890399  4.26799490 1.0000000
## E_SH-C_RO    1.754545455 -2.45890399  5.96799490 0.9915970
## D_RO-C_SH   -1.408333333 -5.52916819  2.71250152 0.9991726
## D_SH-C_SH    0.825000000 -3.29583485  4.94583485 0.9999996
## E_RO-C_SH   -1.591666667 -5.71250152  2.52916819 0.9963745
## E_SH-C_SH    0.108333333 -4.01250152  4.22916819 1.0000000
## D_SH-D_RO    2.233333333 -1.88750152  6.35416819 0.9020981
## E_RO-D_RO   -0.183333333 -4.30416819  3.93750152 1.0000000
## E_SH-D_RO    1.516666667 -2.60416819  5.63750152 0.9979444
## E_RO-D_SH   -2.416666667 -6.53750152  1.70416819 0.8276734
## E_SH-D_SH   -0.716666667 -4.83750152  3.40416819 1.0000000
## E_SH-E_RO    1.700000000 -2.42083485  5.82083485 0.9924083
P4 = Output$All.ID[,'p adj']
stat.test<- multcompLetters(P4)
stat.test
## 1B_SH 1C_RO 1C_SH 1D_RO 1D_SH 1E_RO 1E_SH  A_RO  A_SH  B_RO  B_SH  C_RO  C_SH 
##  "ab"   "a"  "ab"  "ab"  "ab"   "a"  "ab"   "a"   "b"   "a"  "ab"   "a"  "ab" 
##  D_RO  D_SH  E_RO  E_SH 1B_RO 
##   "a"  "ab"   "a"  "ab"  "ab"
test <- as.data.frame(stat.test$Letters)
test$group1 <- rownames(test)
#test$group2 <- rownames(test)
colnames(test)[1] <- "Tukey"
test
test$info <- strsplit(test$group1, "_")
test$info[[1]][2]
## [1] "SH"
test$Accession <- "none"
test$Tissue<- "none"
test
for(i in 1:nrow(test)){
  test$Accession[i] <- test$info[[i]][1]
     test$Tissue[i] <- test$info[[i]][2]
  
}

test2 <- test[,c(4:5,1)]
test2$group1 <- test2$Accession
test2$group2 <- test2$Accession
ICP
ICP5 <- subset(ICP, ICP$DW.mg < 10 ) #& ICP$Na.K.ratio > 0.25)

DW <- ggplot(data = ICP5, mapping = aes(x = Accession, y = DW.mg, colour = Accession)) 
DW <- DW + geom_boxplot(alpha=0.2) + geom_jitter(width=0.1,alpha=0.2)

DW <- DW + facet_grid(~Tissue , scales = "free_y")

DW <- DW + stat_summary(fun=mean, geom="point", shape=95, size=6, color="black", fill="black")
DW <- DW + scale_color_manual(values = c("blue", "plum", "darkorchid1","cyan1", "darkturquoise","red","hotpink","deeppink", "darkgoldenrod","darkorange" ))
DW <- DW + ylab("Dry weight, mg") + xlab("")+stat_pvalue_manual(test2, label = "Tukey", y.position = 5)
DW <- DW + theme(axis.text.x = element_text(angle=90, hjust=0.9, vjust=0.5))
DW <- DW + rremove("legend")
DW