This is a ICP result for the 5 Arabidopsis genotypes grown in plates supplemented with 0, 75, and 125 mM NaCl for two weeks. due to lack of tubes, here you will see the result for the salt stress only.

getwd()
## [1] "C:/Users/Julkowska Lab/Desktop/R codes by Maryam/20231010_ICP-MS_FW_DW_RSA_duf_wrky_2xko_Plate_Grown"
list.files(pattern = ".csv")
## [1] "Eric02142024NaK-analyzed for R.csv"
ICP_wd <- read.csv("Eric02142024NaK-analyzed for R.csv")
ICP_wd
ICP_wd$All.ID2<-paste(ICP_wd$Accession,ICP_wd$Condition, ICP_wd$Tissue, sep="_")
ICP_wd
library(ggplot2)
library(ggpubr)
library(multcompView)
## Warning: package 'multcompView' was built under R version 4.3.2
aov(Na.con.mg.mg.dry.weight ~ All.ID2, data = ICP_wd)
## Call:
##    aov(formula = Na.con.mg.mg.dry.weight ~ All.ID2, data = ICP_wd)
## 
## Terms:
##                  All.ID2 Residuals
## Sum of Squares   74158.9  362862.8
## Deg. of Freedom       19       113
## 
## Residual standard error: 56.66723
## Estimated effects may be unbalanced
Output <- TukeyHSD(aov(Na.con.mg.mg.dry.weight ~ All.ID2, data = ICP_wd))
Output
##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = Na.con.mg.mg.dry.weight ~ All.ID2, data = ICP_wd)
## 
## $All.ID2
##                            diff         lwr        upr     p adj
## a_125_sh-a_125_ro    9.22544370 -136.212511 154.663398 1.0000000
## a_75_ro-a_125_ro   -18.02988120 -146.946849 110.887087 1.0000000
## a_75_sh-a_125_ro    -9.21319450 -129.304633 110.878244 1.0000000
## b_125_ro-a_125_ro    6.95759736 -138.480357 152.395552 1.0000000
## b_125_sh-a_125_ro    8.97444331 -136.463511 154.412398 1.0000000
## b_75_ro-a_125_ro    -8.32713593 -131.925631 115.271359 1.0000000
## b_75_sh-a_125_ro    -8.93145145 -129.022890 111.159987 1.0000000
## c_125_ro-a_125_ro    1.65504334 -155.435902 158.745988 1.0000000
## c_125_sh-a_125_ro   14.50192452 -123.472634 152.476483 1.0000000
## c_75_ro-a_125_ro   -13.20252158 -142.119489 115.714446 1.0000000
## c_75_sh-a_125_ro    30.95017140  -90.731951 152.632294 0.9999930
## d_125_ro-a_125_ro    7.21061712 -149.880328 164.301562 1.0000000
## d_125_sh-a_125_ro    9.12771092 -147.963234 166.218656 1.0000000
## d_75_ro-a_125_ro    -9.95161135 -135.904575 116.001352 1.0000000
## d_75_sh-a_125_ro   -10.43157048 -132.113693 111.250552 1.0000000
## e_125_ro-a_125_ro   11.64099681 -133.796958 157.078951 1.0000000
## e_125_sh-a_125_ro  100.33742754  -37.637131 238.311986 0.4826809
## e_75_ro-a_125_ro   -13.85774825 -135.539871 107.824375 1.0000000
## e_75_sh-a_125_ro   -12.69329759 -132.784736 107.398141 1.0000000
## a_75_ro-a_125_sh   -27.25532491 -156.172293 101.661643 0.9999997
## a_75_sh-a_125_sh   -18.43863820 -138.530077 101.652800 1.0000000
## b_125_ro-a_125_sh   -2.26784635 -147.705801 143.170108 1.0000000
## b_125_sh-a_125_sh   -0.25100039 -145.688955 145.186954 1.0000000
## b_75_ro-a_125_sh   -17.55257964 -141.151074 106.045915 1.0000000
## b_75_sh-a_125_sh   -18.15689515 -138.248334 101.934543 1.0000000
## c_125_ro-a_125_sh   -7.57040037 -164.661345 149.520545 1.0000000
## c_125_sh-a_125_sh    5.27648082 -132.698077 143.251039 1.0000000
## c_75_ro-a_125_sh   -22.42796528 -151.344933 106.489003 1.0000000
## c_75_sh-a_125_sh    21.72472770  -99.957395 143.406851 1.0000000
## d_125_ro-a_125_sh   -2.01482658 -159.105772 155.076118 1.0000000
## d_125_sh-a_125_sh   -0.09773278 -157.188678 156.993212 1.0000000
## d_75_ro-a_125_sh   -19.17705505 -145.130018 106.775908 1.0000000
## d_75_sh-a_125_sh   -19.65701418 -141.339137 102.025109 1.0000000
## e_125_ro-a_125_sh    2.41555310 -143.022401 147.853508 1.0000000
## e_125_sh-a_125_sh   91.11198383  -46.862574 229.086542 0.6624204
## e_75_ro-a_125_sh   -23.08319196 -144.765315  98.598931 0.9999999
## e_75_sh-a_125_sh   -21.91874130 -142.010180  98.172697 1.0000000
## a_75_sh-a_75_ro      8.81668670  -90.628472 108.261845 1.0000000
## b_125_ro-a_75_ro    24.98747856 -103.929489 153.904446 0.9999999
## b_125_sh-a_75_ro    27.00432452 -101.912643 155.921292 0.9999997
## b_75_ro-a_75_ro      9.70274527  -93.950397 113.355887 1.0000000
## b_75_sh-a_75_ro      9.09842976  -90.346729 108.543589 1.0000000
## c_125_ro-a_75_ro    19.68492454 -122.247986 161.617835 1.0000000
## c_125_sh-a_75_ro    32.53180572  -87.902262 152.965874 0.9999822
## c_75_ro-a_75_ro      4.82735962 -105.113400 114.768119 1.0000000
## c_75_sh-a_75_ro     48.98005260  -52.380319 150.340425 0.9670607
## d_125_ro-a_75_ro    25.24049832 -116.692412 167.173409 1.0000000
## d_125_sh-a_75_ro    27.15759213 -114.775318 169.090502 0.9999999
## d_75_ro-a_75_ro      8.07826985  -98.371413 114.527953 1.0000000
## d_75_sh-a_75_ro      7.59831073  -93.762061 108.958683 1.0000000
## e_125_ro-a_75_ro    29.67087801  -99.246090 158.587846 0.9999986
## e_125_sh-a_75_ro   118.36730874   -2.066759 238.801377 0.0599908
## e_75_ro-a_75_ro      4.17213295  -97.188239 105.532505 1.0000000
## e_75_sh-a_75_ro      5.33658361  -94.108575 104.781742 1.0000000
## b_125_ro-a_75_sh    16.17079186 -103.920647 136.262230 1.0000000
## b_125_sh-a_75_sh    18.18763781 -101.903801 138.279076 1.0000000
## b_75_ro-a_75_sh      0.88605857  -91.560374  93.332491 1.0000000
## b_75_sh-a_75_sh      0.28174305  -87.420643  87.984129 1.0000000
## c_125_ro-a_75_sh    10.86823784 -123.099370 144.835846 1.0000000
## c_125_sh-a_75_sh    23.71511902  -87.220600 134.650838 0.9999996
## c_75_ro-a_75_sh     -3.98932708 -103.434486  95.455832 1.0000000
## c_75_sh-a_75_sh     40.16336590  -49.704838 130.031569 0.9851695
## d_125_ro-a_75_sh    16.42381162 -117.543796 150.391420 1.0000000
## d_125_sh-a_75_sh    18.34090542 -115.626703 152.308514 1.0000000
## d_75_ro-a_75_sh     -0.73841685  -96.309877  94.833043 1.0000000
## d_75_sh-a_75_sh     -1.21837598  -91.086580  88.649828 1.0000000
## e_125_ro-a_75_sh    20.85419131  -99.237247 140.945630 1.0000000
## e_125_sh-a_75_sh   109.55062204   -1.385097 220.486341 0.0571118
## e_75_ro-a_75_sh     -4.64455375  -94.512757  85.223650 1.0000000
## e_75_sh-a_75_sh     -3.48010309  -91.182489  84.222283 1.0000000
## b_125_sh-b_125_ro    2.01684596 -143.421108 147.454800 1.0000000
## b_75_ro-b_125_ro   -15.28473329 -138.883228 108.313761 1.0000000
## b_75_sh-b_125_ro   -15.88904880 -135.980487 104.202390 1.0000000
## c_125_ro-b_125_ro   -5.30255402 -162.393499 151.788391 1.0000000
## c_125_sh-b_125_ro    7.54432716 -130.430231 145.518885 1.0000000
## c_75_ro-b_125_ro   -20.16011893 -149.077087 108.756849 1.0000000
## c_75_sh-b_125_ro    23.99257404  -97.689549 145.674697 0.9999999
## d_125_ro-b_125_ro    0.25301976 -156.837925 157.343965 1.0000000
## d_125_sh-b_125_ro    2.17011357 -154.920831 159.261059 1.0000000
## d_75_ro-b_125_ro   -16.90920870 -142.862172 109.043755 1.0000000
## d_75_sh-b_125_ro   -17.38916783 -139.071291 104.292955 1.0000000
## e_125_ro-b_125_ro    4.68339945 -140.754555 150.121354 1.0000000
## e_125_sh-b_125_ro   93.37983018  -44.594728 231.354388 0.6187473
## e_75_ro-b_125_ro   -20.81534561 -142.497468 100.866777 1.0000000
## e_75_sh-b_125_ro   -19.65089495 -139.742333 100.440543 1.0000000
## b_75_ro-b_125_sh   -17.30157925 -140.900074 106.296915 1.0000000
## b_75_sh-b_125_sh   -17.90589476 -137.997333 102.185544 1.0000000
## c_125_ro-b_125_sh   -7.31939998 -164.410345 149.771545 1.0000000
## c_125_sh-b_125_sh    5.52748121 -132.447077 143.502039 1.0000000
## c_75_ro-b_125_sh   -22.17696489 -151.093933 106.740003 1.0000000
## c_75_sh-b_125_sh    21.97572809  -99.706395 143.657851 1.0000000
## d_125_ro-b_125_sh   -1.76382619 -158.854771 155.327119 1.0000000
## d_125_sh-b_125_sh    0.15326761 -156.937677 157.244213 1.0000000
## d_75_ro-b_125_sh   -18.92605466 -144.879018 107.026909 1.0000000
## d_75_sh-b_125_sh   -19.40601379 -141.088137 102.276109 1.0000000
## e_125_ro-b_125_sh    2.66655349 -142.771401 148.104508 1.0000000
## e_125_sh-b_125_sh   91.36298422  -46.611574 229.337542 0.6576411
## e_75_ro-b_125_sh   -22.83219157 -144.514314  98.849931 1.0000000
## e_75_sh-b_125_sh   -21.66774091 -141.759179  98.423698 1.0000000
## b_75_sh-b_75_ro     -0.60431551  -93.050748  91.842117 1.0000000
## c_125_ro-b_75_ro     9.98217927 -127.138039 147.102398 1.0000000
## c_125_sh-b_75_ro    22.82906045  -91.893945 137.552066 0.9999999
## c_75_ro-b_75_ro     -4.87538565 -108.528528  98.777757 1.0000000
## c_75_sh-b_75_ro     39.27730733  -55.226281 133.780896 0.9934073
## d_125_ro-b_75_ro    15.53775305 -121.582465 152.657971 1.0000000
## d_125_sh-b_75_ro    17.45484686 -119.665372 154.575065 1.0000000
## d_75_ro-b_75_ro     -1.62447542 -101.567150  98.318199 1.0000000
## d_75_sh-b_75_ro     -2.10443454  -96.608023  92.399154 1.0000000
## e_125_ro-b_75_ro    19.96813274 -103.630362 143.566627 1.0000000
## e_125_sh-b_75_ro   108.66456347   -6.058442 223.387569 0.0862917
## e_75_ro-b_75_ro     -5.53061232 -100.034201  88.972976 1.0000000
## e_75_sh-b_75_ro     -4.36616166  -96.812594  88.080271 1.0000000
## c_125_ro-b_75_sh    10.58649478 -123.381113 144.554103 1.0000000
## c_125_sh-b_75_sh    23.43337597  -87.502343 134.369095 0.9999997
## c_75_ro-b_75_sh     -4.27107013 -103.716229  95.174089 1.0000000
## c_75_sh-b_75_sh     39.88162285  -49.986581 129.749826 0.9862518
## d_125_ro-b_75_sh    16.14206857 -117.825540 150.109677 1.0000000
## d_125_sh-b_75_sh    18.05916237 -115.908446 152.026770 1.0000000
## d_75_ro-b_75_sh     -1.02015990  -96.591620  94.551300 1.0000000
## d_75_sh-b_75_sh     -1.50011903  -91.368323  88.368085 1.0000000
## e_125_ro-b_75_sh    20.57244826  -99.518990 140.663887 1.0000000
## e_125_sh-b_75_sh   109.26887898   -1.666840 220.204598 0.0586606
## e_75_ro-b_75_sh     -4.92629681  -94.794500  84.941907 1.0000000
## e_75_sh-b_75_sh     -3.76184615  -91.464233  83.940540 1.0000000
## c_125_sh-c_125_ro   12.84688118 -137.360792 163.054555 1.0000000
## c_75_ro-c_125_ro   -14.85756491 -156.790475 127.075345 1.0000000
## c_75_sh-c_125_ro    29.29512806 -106.100239 164.690495 0.9999995
## d_125_ro-c_125_ro    5.55557378 -162.381710 173.492858 1.0000000
## d_125_sh-c_125_ro    7.47266759 -160.464617 175.409952 1.0000000
## d_75_ro-c_125_ro   -11.60665468 -150.852895 127.639585 1.0000000
## d_75_sh-c_125_ro   -12.08661381 -147.481981 123.308753 1.0000000
## e_125_ro-c_125_ro    9.98595347 -147.104992 167.076899 1.0000000
## e_125_sh-c_125_ro   98.68238420  -51.525289 248.890058 0.6712579
## e_75_ro-c_125_ro   -15.51279159 -150.908159 119.882576 1.0000000
## e_75_sh-c_125_ro   -14.34834093 -148.315949 119.619267 1.0000000
## c_75_ro-c_125_sh   -27.70444610 -148.138514  92.729622 0.9999986
## c_75_sh-c_125_sh    16.44824688  -96.207508 129.104002 1.0000000
## d_125_ro-c_125_sh   -7.29130740 -157.498981 142.916366 1.0000000
## d_125_sh-c_125_sh   -5.37421360 -155.581887 144.833460 1.0000000
## d_75_ro-c_125_sh   -24.45353587 -141.709363  92.802292 0.9999997
## d_75_sh-c_125_sh   -24.93349500 -137.589250  87.722260 0.9999993
## e_125_ro-c_125_sh   -2.86092771 -140.835486 135.113631 1.0000000
## e_125_sh-c_125_sh   85.83550302  -44.248158 215.919164 0.6637444
## e_75_ro-c_125_sh   -28.35967277 -141.015428  84.296082 0.9999941
## e_75_sh-c_125_sh   -27.19522211 -138.130941  83.740497 0.9999961
## c_75_sh-c_75_ro     44.15269298  -57.207679 145.513065 0.9887797
## d_125_ro-c_75_ro    20.41313870 -121.519772 162.346049 1.0000000
## d_125_sh-c_75_ro    22.33023250 -119.602678 164.263143 1.0000000
## d_75_ro-c_75_ro      3.25091023 -103.198773 109.700593 1.0000000
## d_75_sh-c_75_ro      2.77095110  -98.589421 104.131323 1.0000000
## e_125_ro-c_75_ro    24.84351839 -104.073449 153.760486 0.9999999
## e_125_sh-c_75_ro   113.53994912   -6.894119 233.974017 0.0901527
## e_75_ro-c_75_ro     -0.65522667 -102.015599 100.705145 1.0000000
## e_75_sh-c_75_ro      0.50922398  -98.935935  99.954383 1.0000000
## d_125_ro-c_75_sh   -23.73955428 -159.134921 111.655813 1.0000000
## d_125_sh-c_75_sh   -21.82246048 -157.217828 113.572907 1.0000000
## d_75_ro-c_75_sh    -40.90178275 -138.464529  56.660963 0.9927129
## d_75_sh-c_75_sh    -41.38174188 -133.364781  50.601297 0.9840824
## e_125_ro-c_75_sh   -19.30917459 -140.991297 102.372948 1.0000000
## e_125_sh-c_75_sh    69.38725614  -43.268499 182.043011 0.7722752
## e_75_ro-c_75_sh    -44.80791965 -136.790958  47.175119 0.9644019
## e_75_sh-c_75_sh    -43.64346899 -133.511673  46.224735 0.9654371
## d_125_sh-d_125_ro    1.91709380 -166.020190 169.854378 1.0000000
## d_75_ro-d_125_ro   -17.16222847 -156.408469 122.084012 1.0000000
## d_75_sh-d_125_ro   -17.64218760 -153.037555 117.753180 1.0000000
## e_125_ro-d_125_ro    4.43037969 -152.660565 161.521325 1.0000000
## e_125_sh-d_125_ro   93.12681042  -57.080863 243.334484 0.7629135
## e_75_ro-d_125_ro   -21.06836537 -156.463733 114.327002 1.0000000
## e_75_sh-d_125_ro   -19.90391471 -153.871523 114.063693 1.0000000
## d_75_ro-d_125_sh   -19.07932227 -158.325562 120.166918 1.0000000
## d_75_sh-d_125_sh   -19.55928140 -154.954649 115.836086 1.0000000
## e_125_ro-d_125_sh    2.51328589 -154.577659 159.604231 1.0000000
## e_125_sh-d_125_sh   91.20971662  -58.997957 241.417390 0.7917419
## e_75_ro-d_125_sh   -22.98545918 -158.380826 112.409908 1.0000000
## e_75_sh-d_125_sh   -21.82100852 -155.788617 112.146600 1.0000000
## d_75_sh-d_75_ro     -0.47995913  -98.042705  97.082787 1.0000000
## e_125_ro-d_75_ro    21.59260816 -104.360355 147.545571 1.0000000
## e_125_sh-d_75_ro   110.28903889   -6.966789 227.544866 0.0920946
## e_75_ro-d_75_ro     -3.90613690 -101.468883  93.656609 1.0000000
## e_75_sh-d_75_ro     -2.74168625  -98.313146  92.829774 1.0000000
## e_125_ro-d_75_sh    22.07256729  -99.609556 143.754690 1.0000000
## e_125_sh-d_75_sh   110.76899801   -1.886757 223.424753 0.0597316
## e_75_ro-d_75_sh     -3.42617778  -95.409217  88.556861 1.0000000
## e_75_sh-d_75_sh     -2.26172712  -92.129931  87.606476 1.0000000
## e_125_sh-e_125_ro   88.69643073  -49.278128 226.670989 0.7074715
## e_75_ro-e_125_ro   -25.49874506 -147.180868  96.183378 0.9999997
## e_75_sh-e_125_ro   -24.33429440 -144.425733  95.757144 0.9999998
## e_75_ro-e_125_sh  -114.19517579 -226.850931  -1.539421 0.0431106
## e_75_sh-e_125_sh  -113.03072513 -223.966444  -2.095006 0.0407070
## e_75_sh-e_75_ro      1.16445066  -88.703753  91.032654 1.0000000
P8 = Output$All.ID2[,'p adj']
stat.test<- multcompLetters(P8)
stat.test
## a_125_sh  a_75_ro  a_75_sh b_125_ro b_125_sh  b_75_ro  b_75_sh c_125_ro 
##     "ab"     "ab"     "ab"     "ab"     "ab"     "ab"     "ab"     "ab" 
## c_125_sh  c_75_ro  c_75_sh d_125_ro d_125_sh  d_75_ro  d_75_sh e_125_ro 
##     "ab"     "ab"     "ab"     "ab"     "ab"     "ab"     "ab"     "ab" 
## e_125_sh  e_75_ro  e_75_sh a_125_ro 
##      "a"      "b"      "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] "125"
test$info[[1]][3]
## [1] "sh"
test$Accession <- "none"
test$Condition<- "none"
test$Tissue<- "none"
test
for(i in 1:nrow(test)){
  test$Accession[i] <- test$info[[i]][1]
  test$Condition[i] <- test$info[[i]][2]
  test$Tissue[i] <- test$info[[i]][3]
  
}

test2 <- test[,c(5:7,1)]
test2$group1 <- test2$Accession
test2$group2 <- test2$Accession


ICP_wd
ICP_wd$Condition <- as.numeric(as.character(ICP_wd$Condition))
unique(ICP_wd$Condition)
## [1]  75 125
ICP_wd$Condition <- factor(ICP_wd$Condition, levels = c("75", "125"))

ICP_wd2 <- subset(ICP_wd, ICP_wd$Na.con.mg.mg.dry.weight < 100)



Na_content_wd <- ggplot(data = ICP_wd2, mapping = aes(x = Accession, y = Na.con.mg.mg.dry.weight, colour = Accession)) 
Na_content_wd <- Na_content_wd + geom_boxplot(alpha=0.2) + geom_jitter(width=0.1,alpha=0.2)

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

Na_content_wd <- Na_content_wd + stat_summary(fun=mean, geom="point", shape=95, size=6, color="black", fill="black")
Na_content_wd <- Na_content_wd + scale_color_manual(values = c("blue", "plum", "rosybrown1", "hotpink","red"))
Na_content_wd <- Na_content_wd + ylab("Na content, mg/mg dry weight") + xlab("")+stat_pvalue_manual(test2, label = "Tukey", y.position = 80)
Na_content_wd <- Na_content_wd + theme(axis.text.x = element_text(angle=90, hjust=0.9, vjust=0.5))
Na_content_wd <- Na_content_wd + rremove("legend")
Na_content_wd

aov(K.con..mg.mg.dry.weight ~ All.ID2, data = ICP_wd)
## Call:
##    aov(formula = K.con..mg.mg.dry.weight ~ All.ID2, data = ICP_wd)
## 
## Terms:
##                   All.ID2 Residuals
## Sum of Squares   30391.43 116043.18
## Deg. of Freedom        19       113
## 
## Residual standard error: 32.04576
## Estimated effects may be unbalanced
Output <- TukeyHSD(aov(K.con..mg.mg.dry.weight ~ All.ID2, data = ICP_wd))
Output
##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = K.con..mg.mg.dry.weight ~ All.ID2, data = ICP_wd)
## 
## $All.ID2
##                           diff         lwr        upr     p adj
## a_125_sh-a_125_ro -12.85556405  -95.101863  69.390735 1.0000000
## a_75_ro-a_125_ro  -16.71661544  -89.620167  56.186936 0.9999987
## a_75_sh-a_125_ro    3.59302796  -64.319618  71.505674 1.0000000
## b_125_ro-a_125_ro  15.79651336  -66.449785  98.042812 0.9999999
## b_125_sh-a_125_ro -17.31953192  -99.565831  64.926767 0.9999997
## b_75_ro-a_125_ro   -7.23983338  -77.135747  62.656080 1.0000000
## b_75_sh-a_125_ro   -1.00789903  -68.920545  66.904747 1.0000000
## c_125_ro-a_125_ro   5.93912047  -82.897035  94.775276 1.0000000
## c_125_sh-a_125_ro -18.83004948  -96.855739  59.195640 0.9999970
## c_75_ro-a_125_ro    0.49733212  -72.406220  73.400884 1.0000000
## c_75_sh-a_125_ro   15.02902590  -53.783164  83.841216 0.9999994
## d_125_ro-a_125_ro  28.11727754  -60.718878 116.953433 0.9998107
## d_125_sh-a_125_ro  -8.97904431  -97.815200  79.857111 1.0000000
## d_75_ro-a_125_ro  -13.00696964  -84.234354  58.220414 1.0000000
## d_75_sh-a_125_ro    0.51326471  -68.298926  69.325455 1.0000000
## e_125_ro-a_125_ro  36.74550687  -45.500792 118.991805 0.9852193
## e_125_sh-a_125_ro  46.85920134  -31.166488 124.884891 0.8060958
## e_75_ro-a_125_ro   -7.63927457  -76.451465  61.172916 1.0000000
## e_75_sh-a_125_ro   -0.22375941  -68.136405  67.688887 1.0000000
## a_75_ro-a_125_sh   -3.86105139  -76.764603  69.042500 1.0000000
## a_75_sh-a_125_sh   16.44859201  -51.464054  84.361238 0.9999968
## b_125_ro-a_125_sh  28.65207742  -53.594221 110.898376 0.9992825
## b_125_sh-a_125_sh  -4.46396787  -86.710266  77.782331 1.0000000
## b_75_ro-a_125_sh    5.61573067  -64.280183  75.511644 1.0000000
## b_75_sh-a_125_sh   11.84766503  -56.064981  79.760311 1.0000000
## c_125_ro-a_125_sh  18.79468453  -70.041471 107.630840 0.9999997
## c_125_sh-a_125_sh  -5.97448542  -84.000175  72.051204 1.0000000
## c_75_ro-a_125_sh   13.35289618  -59.550656  86.256448 1.0000000
## c_75_sh-a_125_sh   27.88458995  -40.927600  96.696780 0.9951035
## d_125_ro-a_125_sh  40.97284160  -47.863314 129.808997 0.9793423
## d_125_sh-a_125_sh   3.87651974  -84.959636  92.712675 1.0000000
## d_75_ro-a_125_sh   -0.15140558  -71.378790  71.075978 1.0000000
## d_75_sh-a_125_sh   13.36882877  -55.443362  82.181019 0.9999999
## e_125_ro-a_125_sh  49.60107092  -32.645228 131.847370 0.8007289
## e_125_sh-a_125_sh  59.71476539  -18.310924 137.740455 0.3849221
## e_75_ro-a_125_sh    5.21628948  -63.595901  74.028480 1.0000000
## e_75_sh-a_125_sh   12.63180465  -55.280841  80.544451 1.0000000
## a_75_sh-a_75_ro    20.30964340  -35.927370  76.546657 0.9988421
## b_125_ro-a_75_ro   32.51312881  -40.390423 105.416681 0.9855007
## b_125_sh-a_75_ro   -0.60291648  -73.506468  72.300635 1.0000000
## b_75_ro-a_75_ro     9.47678206  -49.139879  68.093443 1.0000000
## b_75_sh-a_75_ro    15.70871641  -40.528297  71.945730 0.9999702
## c_125_ro-a_75_ro   22.65573592  -57.608433 102.919905 0.9999650
## c_125_sh-a_75_ro   -2.11343403  -70.219840  65.992972 1.0000000
## c_75_ro-a_75_ro    17.21394756  -44.958410  79.386305 0.9999739
## c_75_sh-a_75_ro    31.74564134  -25.574440  89.065723 0.8914502
## d_125_ro-a_75_ro   44.83389299  -35.430276 125.098062 0.8840742
## d_125_sh-a_75_ro    7.73757113  -72.526598  88.001740 1.0000000
## d_75_ro-a_75_ro     3.70964580  -56.488481  63.907772 1.0000000
## d_75_sh-a_75_ro    17.22988015  -40.090202  74.549962 0.9999105
## e_125_ro-a_75_ro   53.46212231  -19.441429 126.365674 0.4665110
## e_125_sh-a_75_ro   63.57581678   -4.530589 131.682222 0.0986928
## e_75_ro-a_75_ro     9.07734087  -48.242741  66.397423 1.0000000
## e_75_sh-a_75_ro    16.49285603  -39.744158  72.729870 0.9999378
## b_125_ro-a_75_sh   12.20348541  -55.709161  80.116131 1.0000000
## b_125_sh-a_75_sh  -20.91255988  -88.825206  47.000086 0.9998726
## b_75_ro-a_75_sh   -10.83286134  -63.112041  41.446318 0.9999998
## b_75_sh-a_75_sh    -4.60092698  -54.197311  44.995457 1.0000000
## c_125_ro-a_75_sh    2.34609252  -73.413636  78.105821 1.0000000
## c_125_sh-a_75_sh  -22.42307743  -85.158092  40.311938 0.9989896
## c_75_ro-a_75_sh    -3.09569584  -59.332709  53.141318 1.0000000
## c_75_sh-a_75_sh    11.43599794  -39.385173  62.257169 0.9999990
## d_125_ro-a_75_sh   24.52424959  -51.235479 100.283978 0.9997394
## d_125_sh-a_75_sh  -12.57207227  -88.331800  63.187656 1.0000000
## d_75_ro-a_75_sh   -16.59999759  -70.646404  37.446409 0.9998773
## d_75_sh-a_75_sh    -3.07976325  -53.900934  47.741407 1.0000000
## e_125_ro-a_75_sh   33.15247891  -34.760167 101.065125 0.9636738
## e_125_sh-a_75_sh   43.26617338  -19.468842 106.001188 0.5839960
## e_75_ro-a_75_sh   -11.23230253  -62.053473  39.588868 0.9999993
## e_75_sh-a_75_sh    -3.81678737  -53.413172  45.779597 1.0000000
## b_125_sh-b_125_ro -33.11604529 -115.362344  49.130253 0.9954631
## b_75_ro-b_125_ro  -23.03634675  -92.932260  46.859567 0.9996646
## b_75_sh-b_125_ro  -16.80441239  -84.717058  51.108234 0.9999955
## c_125_ro-b_125_ro  -9.85739289  -98.693549  78.978763 1.0000000
## c_125_sh-b_125_ro -34.62656284 -112.652253  43.399127 0.9862500
## c_75_ro-b_125_ro  -15.29918124  -88.202733  57.604370 0.9999997
## c_75_sh-b_125_ro   -0.76748747  -69.579678  68.044703 1.0000000
## d_125_ro-b_125_ro  12.32076418  -76.515392 101.156920 1.0000000
## d_125_sh-b_125_ro -24.77555767 -113.611713  64.060598 0.9999709
## d_75_ro-b_125_ro  -28.80348300 -100.030867  42.423901 0.9952229
## d_75_sh-b_125_ro  -15.28324865  -84.095439  53.528942 0.9999992
## e_125_ro-b_125_ro  20.94899350  -61.297305 103.195292 0.9999929
## e_125_sh-b_125_ro  31.06268797  -46.963002 109.088378 0.9960412
## e_75_ro-b_125_ro  -23.43578793  -92.247978  45.376402 0.9994721
## e_75_sh-b_125_ro  -16.02027277  -83.932919  51.892373 0.9999979
## b_75_ro-b_125_sh   10.07969854  -59.816215  79.975612 1.0000000
## b_75_sh-b_125_sh   16.31163290  -51.601013  84.224279 0.9999972
## c_125_ro-b_125_sh  23.25865240  -65.577503 112.094808 0.9999890
## c_125_sh-b_125_sh  -1.51051755  -79.536207  76.515172 1.0000000
## c_75_ro-b_125_sh   17.81686405  -55.086688  90.720416 0.9999963
## c_75_sh-b_125_sh   32.34855782  -36.463633 101.160748 0.9749100
## d_125_ro-b_125_sh  45.43680947  -43.399346 134.272965 0.9441122
## d_125_sh-b_125_sh   8.34048761  -80.495668  97.176643 1.0000000
## d_75_ro-b_125_sh    4.31256229  -66.914822  75.539946 1.0000000
## d_75_sh-b_125_sh   17.83279664  -50.979394  86.644987 0.9999907
## e_125_ro-b_125_sh  54.06503879  -28.181260 136.311337 0.6702615
## e_125_sh-b_125_sh  64.17873326  -13.846957 142.204423 0.2581064
## e_75_ro-b_125_sh    9.68025735  -59.131933  78.492448 1.0000000
## e_75_sh-b_125_sh   17.09577252  -50.816873  85.008418 0.9999941
## b_75_sh-b_75_ro     6.23193436  -46.047245  58.511114 1.0000000
## c_125_ro-b_75_ro   13.17895386  -64.363600  90.721508 1.0000000
## c_125_sh-b_75_ro  -11.59021609  -76.466971  53.286539 1.0000000
## c_75_ro-b_75_ro     7.73716551  -50.879496  66.353827 1.0000000
## c_75_sh-b_75_ro    22.26885928  -31.173658  75.711376 0.9932078
## d_125_ro-b_75_ro   35.35711093  -42.185443 112.899665 0.9816581
## d_125_sh-b_75_ro   -1.73921093  -79.281765  75.803343 1.0000000
## d_75_ro-b_75_ro    -5.76713625  -62.285499  50.751226 1.0000000
## d_75_sh-b_75_ro     7.75309809  -45.689419  61.195615 1.0000000
## e_125_ro-b_75_ro   43.98534025  -25.910573 113.881254 0.7408717
## e_125_sh-b_75_ro   54.09903472  -10.777721 118.975790 0.2365090
## e_75_ro-b_75_ro    -0.39944119  -53.841958  53.043076 1.0000000
## e_75_sh-b_75_ro     7.01607397  -45.263105  59.295253 1.0000000
## c_125_ro-b_75_sh    6.94701950  -68.812709  82.706748 1.0000000
## c_125_sh-b_75_sh  -17.82215045  -80.557165  44.912865 0.9999614
## c_75_ro-b_75_sh     1.50523115  -54.731782  57.742245 1.0000000
## c_75_sh-b_75_sh    16.03692492  -34.784246  66.858096 0.9998187
## d_125_ro-b_75_sh   29.12517657  -46.634552 104.884905 0.9974226
## d_125_sh-b_75_sh   -7.97114528  -83.730873  67.788583 1.0000000
## d_75_ro-b_75_sh   -11.99907061  -66.045477  42.047336 0.9999992
## d_75_sh-b_75_sh     1.52116374  -49.300007  52.342334 1.0000000
## e_125_ro-b_75_sh   37.75340589  -30.159240 105.666052 0.8882558
## e_125_sh-b_75_sh   47.86710036  -14.867915 110.602115 0.3906199
## e_75_ro-b_75_sh    -6.63137554  -57.452546  44.189795 1.0000000
## e_75_sh-b_75_sh     0.78413962  -48.812245  50.380524 1.0000000
## c_125_sh-c_125_ro -24.76916995 -109.712782  60.174442 0.9999429
## c_75_ro-c_125_ro   -5.44178835  -85.705957  74.822380 1.0000000
## c_75_sh-c_125_ro    9.08990542  -67.477232  85.657042 1.0000000
## d_125_ro-c_125_ro  22.17815707  -72.791688 117.148002 0.9999982
## d_125_sh-c_125_ro -14.91816478 -109.888010  80.051680 1.0000000
## d_75_ro-c_125_ro  -18.94609011  -97.690926  59.798746 0.9999971
## d_75_sh-c_125_ro   -5.42585576  -81.992993  71.141281 1.0000000
## e_125_ro-c_125_ro  30.80638639  -58.029769 119.642542 0.9993255
## e_125_sh-c_125_ro  40.92008086  -44.023531 125.863693 0.9680376
## e_75_ro-c_125_ro  -13.57839504  -90.145532  62.988742 1.0000000
## e_75_sh-c_125_ro   -6.16287988  -81.922608  69.596848 1.0000000
## c_75_ro-c_125_sh   19.32738160  -48.779024  87.433787 0.9999621
## c_75_sh-c_125_sh   33.85907537  -29.848634  97.566784 0.9221421
## d_125_ro-c_125_sh  46.94732702  -37.996285 131.890939 0.8931807
## d_125_sh-c_125_sh   9.85100517  -75.092607  94.794617 1.0000000
## d_75_ro-c_125_sh    5.82307984  -60.486006  72.132166 1.0000000
## d_75_sh-c_125_sh   19.34331419  -44.364395  83.051023 0.9998962
## e_125_ro-c_125_sh  55.57555634  -22.450133 133.601246 0.5227425
## e_125_sh-c_125_sh  65.68925081   -7.874075 139.252577 0.1439829
## e_75_ro-c_125_sh   11.19077491  -52.516934  74.898484 1.0000000
## e_75_sh-c_125_sh   18.60629007  -44.128725  81.341305 0.9999266
## c_75_sh-c_75_ro    14.53169377  -42.788388  71.851775 0.9999934
## d_125_ro-c_75_ro   27.61994542  -52.644223 107.884114 0.9993924
## d_125_sh-c_75_ro   -9.47637643  -89.740545  70.787792 1.0000000
## d_75_ro-c_75_ro   -13.50430176  -73.702428  46.693825 0.9999991
## d_75_sh-c_75_ro     0.01593259  -57.304149  57.336014 1.0000000
## e_125_ro-c_75_ro   36.24817474  -36.655377 109.151726 0.9568054
## e_125_sh-c_75_ro   46.36186921  -21.744536 114.468275 0.6081562
## e_75_ro-c_75_ro    -8.13660669  -65.456688  49.183475 1.0000000
## e_75_sh-c_75_ro    -0.72109153  -56.958105  55.515922 1.0000000
## d_125_ro-c_75_sh   13.08825165  -63.478885  89.655389 1.0000000
## d_125_sh-c_75_sh  -24.00807020 -100.575207  52.559067 0.9998345
## d_75_ro-c_75_sh   -28.03599553  -83.208490  27.136499 0.9472756
## d_75_sh-c_75_sh   -14.51576118  -66.532888  37.501365 0.9999706
## e_125_ro-c_75_sh   21.71648097  -47.095709  90.528671 0.9998184
## e_125_sh-c_75_sh   31.83017544  -31.877533  95.537884 0.9548150
## e_75_ro-c_75_sh   -22.66830046  -74.685427  29.348826 0.9887272
## e_75_sh-c_75_sh   -15.25278530  -66.073956  35.568385 0.9999125
## d_125_sh-d_125_ro -37.09632185 -132.066167  57.873523 0.9968606
## d_75_ro-d_125_ro  -41.12424718 -119.869083  37.620589 0.9329020
## d_75_sh-d_125_ro  -27.60401283 -104.171150  48.963124 0.9988680
## e_125_ro-d_125_ro   8.62822932  -80.207926  97.464385 1.0000000
## e_125_sh-d_125_ro  18.74192379  -66.201688 103.685536 0.9999993
## e_75_ro-d_125_ro  -35.75655211 -112.323689  40.810585 0.9765350
## e_75_sh-d_125_ro  -28.34103695 -104.100765  47.418691 0.9981735
## d_75_ro-d_125_sh   -4.02792533  -82.772761  74.716910 1.0000000
## d_75_sh-d_125_sh    9.49230902  -67.074828  86.059446 1.0000000
## e_125_ro-d_125_sh  45.72455118  -43.111605 134.560707 0.9408941
## e_125_sh-d_125_sh  55.83824565  -29.105366 140.781858 0.6702580
## e_75_ro-d_125_sh    1.33976974  -75.227367  77.906907 1.0000000
## e_75_sh-d_125_sh    8.75528490  -67.004443  84.515013 1.0000000
## d_75_sh-d_75_ro    13.52023435  -41.652260  68.692729 0.9999962
## e_125_ro-d_75_ro   49.75247650  -21.474907 120.979860 0.5600320
## e_125_sh-d_75_ro   59.86617097   -6.442915 126.175257 0.1316769
## e_75_ro-d_75_ro     5.36769507  -49.804799  60.540189 1.0000000
## e_75_sh-d_75_ro    12.78321023  -41.263196  66.829617 0.9999978
## e_125_ro-d_75_sh   36.23224215  -32.579948 105.044433 0.9280345
## e_125_sh-d_75_sh   46.34593662  -17.361772 110.053646 0.4819878
## e_75_ro-d_75_sh    -8.15253928  -60.169666  43.864587 1.0000000
## e_75_sh-d_75_sh    -0.73702412  -51.558195  50.084147 1.0000000
## e_125_sh-e_125_ro  10.11369447  -67.911995  88.139384 1.0000000
## e_75_ro-e_125_ro  -44.38478143 -113.196972  24.427409 0.7019999
## e_75_sh-e_125_ro  -36.96926627 -104.881912  30.943380 0.9052562
## e_75_ro-e_125_sh  -54.49847590 -118.206185   9.209233 0.1988661
## e_75_sh-e_125_sh  -47.08296074 -109.817976  15.652054 0.4219675
## e_75_sh-e_75_ro     7.41551516  -43.405655  58.236686 1.0000000
P7 = Output$All.ID2[,'p adj']
stat.test<- multcompLetters(P7)
stat.test
## $Letters
## a_125_sh  a_75_ro  a_75_sh b_125_ro b_125_sh  b_75_ro  b_75_sh c_125_ro 
##      "a"      "a"      "a"      "a"      "a"      "a"      "a"      "a" 
## c_125_sh  c_75_ro  c_75_sh d_125_ro d_125_sh  d_75_ro  d_75_sh e_125_ro 
##      "a"      "a"      "a"      "a"      "a"      "a"      "a"      "a" 
## e_125_sh  e_75_ro  e_75_sh a_125_ro 
##      "a"      "a"      "a"      "a" 
## 
## $LetterMatrix
##             a
## a_125_sh TRUE
## a_75_ro  TRUE
## a_75_sh  TRUE
## b_125_ro TRUE
## b_125_sh TRUE
## b_75_ro  TRUE
## b_75_sh  TRUE
## c_125_ro TRUE
## c_125_sh TRUE
## c_75_ro  TRUE
## c_75_sh  TRUE
## d_125_ro TRUE
## d_125_sh TRUE
## d_75_ro  TRUE
## d_75_sh  TRUE
## e_125_ro TRUE
## e_125_sh TRUE
## e_75_ro  TRUE
## e_75_sh  TRUE
## a_125_ro TRUE
test <- as.data.frame(stat.test$Letters)
test$group1 <- rownames(test)
test$group2 <- rownames(test)
colnames(test)[1] <- "Tukey"
test
test$info <- strsplit(test$group1, "_")
test$info[[1]][2]
## [1] "125"
test$info[[1]][3]
## [1] "sh"
test$Accession <- "none"
test$Condition<- "none"
test$Tissue<- "none"
test
for(i in 1:nrow(test)){
  test$Accession[i] <- test$info[[i]][1]
  test$Condition[i] <- test$info[[i]][2]
  test$Tissue[i] <- test$info[[i]][3]
  
}

test2 <- test[,c(5:7,1)]
test2$group1 <- test2$Accession
test2$group2 <- test2$Accession


ICP_wd
ICP_wd3 <- subset(ICP_wd, ICP_wd$K.con..mg.mg.dry.weight < 100)


k_content_wd <- ggplot(data = ICP_wd3, mapping = aes(x = Accession, y = K.con..mg.mg.dry.weight, colour = Accession)) 
k_content_wd <- k_content_wd + geom_boxplot(alpha=0.2) + geom_jitter(width=0.1,alpha=0.2)

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

k_content_wd <- k_content_wd + stat_summary(fun=mean, geom="point", shape=95, size=6, color="black", fill="black")
k_content_wd <- k_content_wd + scale_color_manual(values = c("blue", "plum", "rosybrown1", "hotpink","red"))
k_content_wd <- k_content_wd + ylab("K content, mg/mg dry weight") + xlab("")+stat_pvalue_manual(test2, label = "Tukey", y.position = 70)
k_content_wd <- k_content_wd + theme(axis.text.x = element_text(angle=90, hjust=0.9, vjust=0.5))
k_content_wd <- k_content_wd + rremove("legend")
k_content_wd

aov(Na.K.ratio ~ All.ID2, data = ICP_wd)
## Call:
##    aov(formula = Na.K.ratio ~ All.ID2, data = ICP_wd)
## 
## Terms:
##                  All.ID2 Residuals
## Sum of Squares  14.30638  22.58079
## Deg. of Freedom       19       113
## 
## Residual standard error: 0.4470235
## Estimated effects may be unbalanced
Output <- TukeyHSD(aov(Na.K.ratio ~ All.ID2, data = ICP_wd))
Output
##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = Na.K.ratio ~ All.ID2, data = ICP_wd)
## 
## $All.ID2
##                           diff          lwr         upr     p adj
## a_125_sh-a_125_ro  0.658073608 -0.489224076  1.80537129 0.8587919
## a_75_ro-a_125_ro  -0.167855892 -1.184826595  0.84911481 1.0000000
## a_75_sh-a_125_ro  -0.209308774 -1.156658657  0.73804111 0.9999993
## b_125_ro-a_125_ro -0.052234227 -1.199531911  1.09506346 1.0000000
## b_125_sh-a_125_ro  0.813163361 -0.334134323  1.96046104 0.5322225
## b_75_ro-a_125_ro  -0.047149071 -1.022164617  0.92786648 1.0000000
## b_75_sh-a_125_ro  -0.013654212 -0.961004095  0.93369567 1.0000000
## c_125_ro-a_125_ro -0.021223839 -1.260446972  1.21799929 1.0000000
## c_125_sh-a_125_ro  1.090069993  0.001647842  2.17849214 0.0491922
## c_75_ro-a_125_ro  -0.257045353 -1.274016055  0.75992535 0.9999937
## c_75_sh-a_125_ro  -0.032165396 -0.992063507  0.92773271 1.0000000
## d_125_ro-a_125_ro -0.110655843 -1.349878975  1.12856729 1.0000000
## d_125_sh-a_125_ro  0.513038831 -0.726184301  1.75226196 0.9936994
## d_75_ro-a_125_ro  -0.065456535 -1.059045475  0.92813241 1.0000000
## d_75_sh-a_125_ro  -0.127768998 -1.087667108  0.83212911 1.0000000
## e_125_ro-a_125_ro -0.163576080 -1.310873764  0.98372160 1.0000000
## e_125_sh-a_125_ro  0.443556793 -0.644865357  1.53197894 0.9947642
## e_75_ro-a_125_ro  -0.123105420 -1.083003531  0.83679269 1.0000000
## e_75_sh-a_125_ro  -0.227517224 -1.174867107  0.71983266 0.9999972
## a_75_ro-a_125_sh  -0.825929501 -1.842900203  0.19104120 0.2789658
## a_75_sh-a_125_sh  -0.867382382 -1.814732265  0.07996750 0.1170209
## b_125_ro-a_125_sh -0.710307835 -1.857605519  0.43698985 0.7649387
## b_125_sh-a_125_sh  0.155089752 -0.992207931  1.30238744 1.0000000
## b_75_ro-a_125_sh  -0.705222679 -1.680238226  0.26979287 0.4931355
## b_75_sh-a_125_sh  -0.671727820 -1.619077703  0.27562206 0.5314223
## c_125_ro-a_125_sh -0.679297448 -1.918520580  0.55992568 0.8998593
## c_125_sh-a_125_sh  0.431996385 -0.656425766  1.52041854 0.9961841
## c_75_ro-a_125_sh  -0.915118961 -1.932089663  0.10185174 0.1353101
## c_75_sh-a_125_sh  -0.690239004 -1.650137115  0.26965911 0.5044312
## d_125_ro-a_125_sh -0.768729451 -2.007952583  0.47049368 0.7621119
## d_125_sh-a_125_sh -0.145034777 -1.384257909  1.09418836 1.0000000
## d_75_ro-a_125_sh  -0.723530143 -1.717119083  0.27005880 0.4800729
## d_75_sh-a_125_sh  -0.785842606 -1.745740717  0.17405550 0.2657399
## e_125_ro-a_125_sh -0.821649688 -1.968947372  0.32564800 0.5122632
## e_125_sh-a_125_sh -0.214516815 -1.302938966  0.87390534 0.9999999
## e_75_ro-a_125_sh  -0.781179028 -1.741077139  0.17871908 0.2755478
## e_75_sh-a_125_sh  -0.885590832 -1.832940716  0.06175905 0.0974286
## a_75_sh-a_75_ro   -0.041452881 -0.825933114  0.74302735 1.0000000
## b_125_ro-a_75_ro   0.115621666 -0.901349037  1.13259237 1.0000000
## b_125_sh-a_75_ro   0.981019253 -0.035951449  1.99798996 0.0724040
## b_75_ro-a_75_ro    0.120706821 -0.696968389  0.93838203 1.0000000
## b_75_sh-a_75_ro    0.154201681 -0.630278552  0.93868191 0.9999999
## c_125_ro-a_75_ro   0.146632053 -0.973015841  1.26627995 1.0000000
## c_125_sh-a_75_ro   1.257925885  0.307873143  2.20797863 0.0007903
## c_75_ro-a_75_ro   -0.089189461 -0.956464990  0.77808607 1.0000000
## c_75_sh-a_75_ro    0.135690496 -0.663898033  0.93527903 1.0000000
## d_125_ro-a_75_ro   0.057200050 -1.062447844  1.17684794 1.0000000
## d_125_sh-a_75_ro   0.680894724 -0.438753170  1.80054262 0.7897458
## d_75_ro-a_75_ro    0.102399357 -0.737336563  0.94213528 1.0000000
## d_75_sh-a_75_ro    0.040086895 -0.759501635  0.83967542 1.0000000
## e_125_ro-a_75_ro   0.004279812 -1.012690890  1.02125051 1.0000000
## e_125_sh-a_75_ro   0.611412686 -0.338640056  1.56146543 0.7056817
## e_75_ro-a_75_ro    0.044750472 -0.754838057  0.84433900 1.0000000
## e_75_sh-a_75_ro   -0.059661332 -0.844141564  0.72481890 1.0000000
## b_125_ro-a_75_sh   0.157074547 -0.790275337  1.10442443 1.0000000
## b_125_sh-a_75_sh   1.022472134  0.075122251  1.96982202 0.0203762
## b_75_ro-a_75_sh    0.162159703 -0.567110578  0.89142998 0.9999992
## b_75_sh-a_75_sh    0.195654562 -0.496191973  0.88750110 0.9999640
## c_125_ro-a_75_sh   0.188084934 -0.868728104  1.24489797 1.0000000
## c_125_sh-a_75_sh   1.299378766  0.424254430  2.17450310 0.0000691
## c_75_ro-a_75_sh   -0.047736579 -0.832216812  0.73674365 1.0000000
## c_75_sh-a_75_sh    0.177143377 -0.531788360  0.88607512 0.9999947
## d_125_ro-a_75_sh   0.098652931 -0.958160107  1.15546597 1.0000000
## d_125_sh-a_75_sh   0.722347605 -0.334465433  1.77916064 0.6006345
## d_75_ro-a_75_sh    0.143852239 -0.610070044  0.89777452 0.9999999
## d_75_sh-a_75_sh    0.081539776 -0.627391962  0.79047151 1.0000000
## e_125_ro-a_75_sh   0.045732694 -0.901617190  0.99308258 1.0000000
## e_125_sh-a_75_sh   0.652865567 -0.222258769  1.52798990 0.4334335
## e_75_ro-a_75_sh    0.086203354 -0.622728384  0.79513509 1.0000000
## e_75_sh-a_75_sh   -0.018208450 -0.710054985  0.67363808 1.0000000
## b_125_sh-b_125_ro  0.865397587 -0.281900096  2.01269527 0.4123656
## b_75_ro-b_125_ro   0.005085156 -0.969930391  0.98010070 1.0000000
## b_75_sh-b_125_ro   0.038580015 -0.908769868  0.98592990 1.0000000
## c_125_ro-b_125_ro  0.031010387 -1.208212745  1.27023352 1.0000000
## c_125_sh-b_125_ro  1.142304220  0.053882069  2.23072637 0.0288462
## c_75_ro-b_125_ro  -0.204811126 -1.221781828  0.81215958 0.9999998
## c_75_sh-b_125_ro   0.020068831 -0.939829280  0.97996694 1.0000000
## d_125_ro-b_125_ro -0.058421616 -1.297644748  1.18080152 1.0000000
## d_125_sh-b_125_ro  0.565273058 -0.673950074  1.80449619 0.9815819
## d_75_ro-b_125_ro  -0.013222308 -1.006811248  0.98036663 1.0000000
## d_75_sh-b_125_ro  -0.075534771 -1.035432882  0.88436334 1.0000000
## e_125_ro-b_125_ro -0.111341853 -1.258639537  1.03595583 1.0000000
## e_125_sh-b_125_ro  0.495791020 -0.592631131  1.58421317 0.9818496
## e_75_ro-b_125_ro  -0.070871193 -1.030769304  0.88902692 1.0000000
## e_75_sh-b_125_ro  -0.175282997 -1.122632881  0.77206689 1.0000000
## b_75_ro-b_125_sh  -0.860312432 -1.835327978  0.11470311 0.1581688
## b_75_sh-b_125_sh  -0.826817572 -1.774167456  0.12053231 0.1718851
## c_125_ro-b_125_sh -0.834387200 -2.073610332  0.40483593 0.6280628
## c_125_sh-b_125_sh  0.276906632 -0.811515519  1.36532878 0.9999930
## c_75_ro-b_125_sh  -1.070208714 -2.087179416 -0.05323801 0.0279190
## c_75_sh-b_125_sh  -0.845328757 -1.805226868  0.11456935 0.1605572
## d_125_ro-b_125_sh -0.923819203 -2.163042336  0.31540393 0.4348325
## d_125_sh-b_125_sh -0.300124529 -1.539347662  0.93909860 0.9999968
## d_75_ro-b_125_sh  -0.878619896 -1.872208836  0.11496904 0.1555089
## d_75_sh-b_125_sh  -0.940932358 -1.900830469  0.01896575 0.0616432
## e_125_ro-b_125_sh -0.976739441 -2.124037125  0.17055824 0.2056841
## e_125_sh-b_125_sh -0.369606567 -1.458028718  0.71881558 0.9994929
## e_75_ro-b_125_sh  -0.936268781 -1.896166891  0.02362933 0.0648391
## e_75_sh-b_125_sh  -1.040680585 -1.988030468 -0.09333070 0.0161815
## b_75_sh-b_75_ro    0.033494859 -0.695775421  0.76276514 1.0000000
## c_125_ro-b_75_ro   0.025925232 -1.055757398  1.10760786 1.0000000
## c_125_sh-b_75_ro   1.137219064  0.232218446  2.04221968 0.0020602
## c_75_ro-b_75_ro   -0.209896282 -1.027571492  0.60777893 0.9999920
## c_75_sh-b_75_ro    0.014983675 -0.730514630  0.76048198 1.0000000
## d_125_ro-b_75_ro  -0.063506772 -1.145189402  1.01817586 1.0000000
## d_125_sh-b_75_ro   0.560187902 -0.521494728  1.64187053 0.9376108
## d_75_ro-b_75_ro   -0.018307464 -0.806712387  0.77009746 1.0000000
## d_75_sh-b_75_ro   -0.080619927 -0.826118232  0.66487838 1.0000000
## e_125_ro-b_75_ro  -0.116427009 -1.091442556  0.85858854 1.0000000
## e_125_sh-b_75_ro   0.490705864 -0.414294753  1.39570648 0.9082239
## e_75_ro-b_75_ro   -0.075956349 -0.821454654  0.66954196 1.0000000
## e_75_sh-b_75_ro   -0.180368153 -0.909638433  0.54890213 0.9999955
## c_125_ro-b_75_sh  -0.007569628 -1.064382666  1.04924341 1.0000000
## c_125_sh-b_75_sh   1.103724204  0.228599868  1.97884854 0.0019319
## c_75_ro-b_75_sh   -0.243391141 -1.027871374  0.54108909 0.9998579
## c_75_sh-b_75_sh   -0.018511185 -0.727442922  0.69042055 1.0000000
## d_125_ro-b_75_sh  -0.097001631 -1.153814669  0.95981141 1.0000000
## d_125_sh-b_75_sh   0.526693043 -0.530119995  1.58350608 0.9558506
## d_75_ro-b_75_sh   -0.051802323 -0.805724606  0.70211996 1.0000000
## d_75_sh-b_75_sh   -0.114114786 -0.823046524  0.59481695 1.0000000
## e_125_ro-b_75_sh  -0.149921868 -1.097271752  0.79742801 1.0000000
## e_125_sh-b_75_sh   0.457211005 -0.417913331  1.33233534 0.9326740
## e_75_ro-b_75_sh   -0.109451208 -0.818382946  0.59948053 1.0000000
## e_75_sh-b_75_sh   -0.213863012 -0.905709547  0.47798352 0.9998653
## c_125_sh-c_125_ro  1.111293832 -0.073630121  2.29621778 0.0945792
## c_75_ro-c_125_ro  -0.235821514 -1.355469407  0.88382638 0.9999997
## c_75_sh-c_125_ro  -0.010941557 -1.079017574  1.05713446 1.0000000
## d_125_ro-c_125_ro -0.089432003 -1.414217257  1.23535325 1.0000000
## d_125_sh-c_125_ro  0.534262671 -0.790522583  1.85904792 0.9953764
## d_75_ro-c_125_ro  -0.044232696 -1.142686599  1.05422121 1.0000000
## d_75_sh-c_125_ro  -0.106545158 -1.174621176  0.96153086 1.0000000
## e_125_ro-c_125_ro -0.142352241 -1.381575373  1.09687089 1.0000000
## e_125_sh-c_125_ro  0.464780633 -0.720143320  1.64970459 0.9966955
## e_75_ro-c_125_ro  -0.101881580 -1.169957598  0.96619444 1.0000000
## e_75_sh-c_125_ro  -0.206293385 -1.263106423  0.85051965 0.9999999
## c_75_ro-c_125_sh  -1.347115346 -2.297168087 -0.39706260 0.0001951
## c_75_sh-c_125_sh  -1.122235389 -2.010928354 -0.23354242 0.0018900
## d_125_ro-c_125_sh -1.200725835 -2.385649788 -0.01580188 0.0432661
## d_125_sh-c_125_sh -0.577031161 -1.761955114  0.60789279 0.9645104
## d_75_ro-c_125_sh  -1.155526528 -2.080507492 -0.23054556 0.0022810
## d_75_sh-c_125_sh  -1.217838990 -2.106531955 -0.32914603 0.0003999
## e_125_ro-c_125_sh -1.253646073 -2.342068223 -0.16522392 0.0083373
## e_125_sh-c_125_sh -0.646513199 -1.672687444  0.37966105 0.7391223
## e_75_ro-c_125_sh  -1.213175413 -2.101868377 -0.32448245 0.0004324
## e_75_sh-c_125_sh  -1.317587217 -2.192711553 -0.44246288 0.0000497
## c_75_sh-c_75_ro    0.224879957 -0.574708573  1.02446849 0.9999669
## d_125_ro-c_75_ro   0.146389510 -0.973258383  1.26603740 1.0000000
## d_125_sh-c_75_ro   0.770084184 -0.349563709  1.88973208 0.5890713
## d_75_ro-c_75_ro    0.191588818 -0.648147102  1.03132474 0.9999988
## d_75_sh-c_75_ro    0.129276355 -0.670312174  0.92886488 1.0000000
## e_125_ro-c_75_ro   0.093469273 -0.923501429  1.11043998 1.0000000
## e_125_sh-c_75_ro   0.700602146 -0.249450595  1.65065489 0.4557257
## e_75_ro-c_75_ro    0.133939933 -0.665648597  0.93352846 1.0000000
## e_75_sh-c_75_ro    0.029528129 -0.754952104  0.81400836 1.0000000
## d_125_ro-c_75_sh  -0.078490447 -1.146566464  0.98958557 1.0000000
## d_125_sh-c_75_sh   0.545204227 -0.522871790  1.61328024 0.9450926
## d_75_ro-c_75_sh   -0.033291139 -0.802921822  0.73633954 1.0000000
## d_75_sh-c_75_sh   -0.095603602 -0.821218369  0.63001117 1.0000000
## e_125_ro-c_75_sh  -0.131410684 -1.091308795  0.82848743 1.0000000
## e_125_sh-c_75_sh   0.475722189 -0.412970775  1.36441515 0.9173528
## e_75_ro-c_75_sh   -0.090940024 -0.816554791  0.63467474 1.0000000
## e_75_sh-c_75_sh   -0.195351828 -0.904283566  0.51357991 0.9999758
## d_125_sh-d_125_ro  0.623694674 -0.701090579  1.94847993 0.9745372
## d_75_ro-d_125_ro   0.045199308 -1.053254596  1.14365321 1.0000000
## d_75_sh-d_125_ro  -0.017113155 -1.085189172  1.05096286 1.0000000
## e_125_ro-d_125_ro -0.052920237 -1.292143370  1.18630289 1.0000000
## e_125_sh-d_125_ro  0.554212636 -0.630711317  1.73913659 0.9761634
## e_75_ro-d_125_ro  -0.012449577 -1.080525595  1.05562644 1.0000000
## e_75_sh-d_125_ro  -0.116861381 -1.173674419  0.93995166 1.0000000
## d_75_ro-d_125_sh  -0.578495366 -1.676949270  0.51995854 0.9279101
## d_75_sh-d_125_sh  -0.640807829 -1.708883846  0.42726819 0.8073565
## e_125_ro-d_125_sh -0.676614911 -1.915838044  0.56260822 0.9029581
## e_125_sh-d_125_sh -0.069482038 -1.254405991  1.11544191 1.0000000
## e_75_ro-d_125_sh  -0.636144251 -1.704220269  0.43193177 0.8164573
## e_75_sh-d_125_sh  -0.740556055 -1.797369093  0.31625698 0.5539487
## d_75_sh-d_75_ro   -0.062312463 -0.831943146  0.70731822 1.0000000
## e_125_ro-d_75_ro  -0.098119545 -1.091708485  0.89546940 1.0000000
## e_125_sh-d_75_ro   0.509013328 -0.415967636  1.43399429 0.8967461
## e_75_ro-d_75_ro   -0.057648885 -0.827279568  0.71198180 1.0000000
## e_75_sh-d_75_ro   -0.162060689 -0.915982971  0.59186159 0.9999995
## e_125_ro-d_75_sh  -0.035807082 -0.995705193  0.92409103 1.0000000
## e_125_sh-d_75_sh   0.571325791 -0.317367174  1.46001876 0.7073785
## e_75_ro-d_75_sh    0.004663578 -0.720951189  0.73027834 1.0000000
## e_75_sh-d_75_sh   -0.099748226 -0.808679964  0.60918351 1.0000000
## e_125_sh-e_125_ro  0.607132873 -0.481289277  1.69555502 0.8852893
## e_75_ro-e_125_ro   0.040470660 -0.919427451  1.00036877 1.0000000
## e_75_sh-e_125_ro  -0.063941144 -1.011291027  0.88340874 1.0000000
## e_75_ro-e_125_sh  -0.566662213 -1.455355178  0.32203075 0.7204885
## e_75_sh-e_125_sh  -0.671074017 -1.546198354  0.20405032 0.3812275
## e_75_sh-e_75_ro   -0.104411804 -0.813343542  0.60451993 1.0000000
P9 = Output$All.ID2[,'p adj']
stat.test<- multcompLetters(P9)
stat.test
## a_125_sh  a_75_ro  a_75_sh b_125_ro b_125_sh  b_75_ro  b_75_sh c_125_ro 
##    "abc"     "ab"      "a"     "ab"     "bc"     "ab"     "ab"    "abc" 
## c_125_sh  c_75_ro  c_75_sh d_125_ro d_125_sh  d_75_ro  d_75_sh e_125_ro 
##      "c"      "a"     "ab"     "ab"    "abc"     "ab"     "ab"     "ab" 
## e_125_sh  e_75_ro  e_75_sh a_125_ro 
##    "abc"     "ab"      "a"     "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] "125"
test$info[[1]][3]
## [1] "sh"
test$Accession <- "none"
test$Condition<- "none"
test$Tissue<- "none"
test
for(i in 1:nrow(test)){
  test$Accession[i] <- test$info[[i]][1]
  test$Condition[i] <- test$info[[i]][2]
  test$Tissue[i] <- test$info[[i]][3]
  
}

test2 <- test[,c(5:7,1)]
test2$group1 <- test2$Accession
test2$group2 <- test2$Accession


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

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

Nak_ratio_wd <- Nak_ratio_wd + stat_summary(fun=mean, geom="point", shape=95, size=6, color="black", fill="black")
Nak_ratio_wd <- Nak_ratio_wd + scale_color_manual(values = c("blue", "plum", "rosybrown1", "hotpink","red"))
Nak_ratio_wd <- Nak_ratio_wd + ylab("Na+/K+ ratio") + xlab("")+stat_pvalue_manual(test2, label = "Tukey", y.position = 2)
Nak_ratio_wd <- Nak_ratio_wd + theme(axis.text.x = element_text(angle=90, hjust=0.9, vjust=0.5))
Nak_ratio_wd <- Nak_ratio_wd + rremove("legend")
Nak_ratio_wd

colnames(ICP_wd)
##  [1] "All.ID"                  "Accession"              
##  [3] "Condition"               "Tissue"                 
##  [5] "DW.g"                    "DW.mg"                  
##  [7] "K.con..mg.mg.dry.weight" "Na.con.mg.mg.dry.weight"
##  [9] "Na.K.ratio"              "All.ID2"
aov(DW.mg ~ All.ID2, data = ICP_wd)
## Call:
##    aov(formula = DW.mg ~ All.ID2, data = ICP_wd)
## 
## Terms:
##                  All.ID2 Residuals
## Sum of Squares  192.6765  120.9255
## Deg. of Freedom       19       113
## 
## Residual standard error: 1.034474
## Estimated effects may be unbalanced
Output <- TukeyHSD(aov(DW.mg ~ All.ID2, data = ICP_wd))
Output
##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = DW.mg ~ All.ID2, data = ICP_wd)
## 
## $All.ID2
##                           diff         lwr          upr     p adj
## a_125_sh-a_125_ro  1.975000000 -0.68000583  4.630005834 0.4389722
## a_75_ro-a_125_ro   0.667857143 -1.68555400  3.021268281 0.9999621
## a_75_sh-a_125_ro   2.597727273  0.40542836  4.790026188 0.0054280
## b_125_ro-a_125_ro  0.150000000 -2.50500583  2.805005834 1.0000000
## b_125_sh-a_125_ro  2.125000000 -0.53000583  4.780005834 0.3038242
## b_75_ro-a_125_ro   0.258333333 -1.99798776  2.514654426 1.0000000
## b_75_sh-a_125_ro   2.288636364  0.09633745  4.480935278 0.0307386
## c_125_ro-a_125_ro -0.041666667 -2.90940073  2.826067394 1.0000000
## c_125_sh-a_125_ro  2.025000000 -0.49375969  4.543759691 0.2961040
## c_75_ro-a_125_ro   0.353571429 -1.99983971  2.706982567 1.0000000
## c_75_sh-a_125_ro   2.395000000  0.17366275  4.616337252 0.0206481
## d_125_ro-a_125_ro  0.091666667 -2.77606739  2.959400728 1.0000000
## d_125_sh-a_125_ro  2.458333333 -0.40940073  5.326067394 0.1959396
## d_75_ro-a_125_ro   0.437500000 -1.86180250  2.736802500 0.9999999
## d_75_sh-a_125_ro   3.265000000  1.04366275  5.486337252 0.0000874
## e_125_ro-a_125_ro  0.100000000 -2.55500583  2.755005834 1.0000000
## e_125_sh-a_125_ro  1.673000000 -0.84575969  4.191759691 0.6522552
## e_75_ro-a_125_ro   0.455000000 -1.76633725  2.676337252 0.9999998
## e_75_sh-a_125_ro   3.461363636  1.26906472  5.653662551 0.0000152
## a_75_ro-a_125_sh  -1.307142857 -3.66055400  1.046268281 0.8890080
## a_75_sh-a_125_sh   0.622727273 -1.56957164  2.815026188 0.9999615
## b_125_ro-a_125_sh -1.825000000 -4.48000583  0.830005834 0.5901827
## b_125_sh-a_125_sh  0.150000000 -2.50500583  2.805005834 1.0000000
## b_75_ro-a_125_sh  -1.716666667 -3.97298776  0.539654426 0.3960114
## b_75_sh-a_125_sh   0.313636364 -1.87866255  2.505935278 1.0000000
## c_125_ro-a_125_sh -2.016666667 -4.88440073  0.851067394 0.5472188
## c_125_sh-a_125_sh  0.050000000 -2.46875969  2.568759691 1.0000000
## c_75_ro-a_125_sh  -1.621428571 -3.97483971  0.731982567 0.5858812
## c_75_sh-a_125_sh   0.420000000 -1.80133725  2.641337252 0.9999999
## d_125_ro-a_125_sh -1.883333333 -4.75106739  0.984400728 0.6718851
## d_125_sh-a_125_sh  0.483333333 -2.38440073  3.351067394 1.0000000
## d_75_ro-a_125_sh  -1.537500000 -3.83680250  0.761802500 0.6404221
## d_75_sh-a_125_sh   1.290000000 -0.93133725  3.511337252 0.8457181
## e_125_ro-a_125_sh -1.875000000 -4.53000583  0.780005834 0.5391265
## e_125_sh-a_125_sh -0.302000000 -2.82075969  2.216759691 1.0000000
## e_75_ro-a_125_sh  -1.520000000 -3.74133725  0.701337252 0.5985885
## e_75_sh-a_125_sh   1.486363636 -0.70593528  3.678662551 0.6155152
## a_75_sh-a_75_ro    1.929870130  0.11447416  3.745266102 0.0246638
## b_125_ro-a_75_ro  -0.517857143 -2.87126828  1.835553995 0.9999993
## b_125_sh-a_75_ro   1.457142857 -0.89626828  3.810553995 0.7648270
## b_75_ro-a_75_ro   -0.409523810 -2.30173756  1.482689941 0.9999995
## b_75_sh-a_75_ro    1.620779221 -0.19461675  3.436175193 0.1441964
## c_125_ro-a_75_ro  -0.709523810 -3.30054420  1.881496578 0.9999780
## c_125_sh-a_75_ro   1.357142857 -0.84141085  3.555696560 0.7691469
## c_75_ro-a_75_ro   -0.314285714 -2.32128148  1.692710048 1.0000000
## c_75_sh-a_75_ro    1.727142857 -0.12321581  3.577501522 0.0987578
## d_125_ro-a_75_ro  -0.576190476 -3.16721086  2.014829911 0.9999992
## d_125_sh-a_75_ro   1.790476190 -0.80054420  4.381496578 0.5802948
## d_75_ro-a_75_ro   -0.230357143 -2.17362243  1.712908148 1.0000000
## d_75_sh-a_75_ro    2.597142857  0.74678419  4.447501522 0.0002427
## e_125_ro-a_75_ro  -0.567857143 -2.92126828  1.785553995 0.9999970
## e_125_sh-a_75_ro   1.005142857 -1.19341085  3.203696560 0.9811418
## e_75_ro-a_75_ro   -0.212857143 -2.06321581  1.637501522 1.0000000
## e_75_sh-a_75_ro    2.793506494  0.97811052  4.608902466 0.0000292
## b_125_ro-a_75_sh  -2.447727273 -4.64002619 -0.255428358 0.0129852
## b_125_sh-a_75_sh  -0.472727273 -2.66502619  1.719571642 0.9999995
## b_75_ro-a_75_sh   -2.339393939 -4.02702643 -0.651761448 0.0003156
## b_75_sh-a_75_sh   -0.309090909 -1.91011967  1.291937849 0.9999999
## c_125_ro-a_75_sh  -2.639393939 -5.08500576 -0.193782115 0.0203909
## c_125_sh-a_75_sh  -0.572727273 -2.59788626  1.452431717 0.9999640
## c_75_ro-a_75_sh   -2.244155844 -4.05955182 -0.428759872 0.0027296
## c_75_sh-a_75_sh   -0.202727273 -1.84329356  1.437839013 1.0000000
## d_125_ro-a_75_sh  -2.506060606 -4.95167243 -0.060448782 0.0381617
## d_125_sh-a_75_sh  -0.139393939 -2.58500576  2.306217885 1.0000000
## d_75_ro-a_75_sh   -2.160227273 -3.90490791 -0.415546632 0.0026559
## d_75_sh-a_75_sh    0.667272727 -0.97329356  2.307839013 0.9948830
## e_125_ro-a_75_sh  -2.497727273 -4.69002619 -0.305428358 0.0097685
## e_125_sh-a_75_sh  -0.924727273 -2.94988626  1.100431717 0.9813832
## e_75_ro-a_75_sh   -2.142727273 -3.78329356 -0.502160987 0.0010243
## e_75_sh-a_75_sh    0.863636364 -0.73739239  2.464665122 0.9119857
## b_125_sh-b_125_ro  1.975000000 -0.68000583  4.630005834 0.4389722
## b_75_ro-b_125_ro   0.108333333 -2.14798776  2.364654426 1.0000000
## b_75_sh-b_125_ro   2.138636364 -0.05366255  4.330935278 0.0647459
## c_125_ro-b_125_ro -0.191666667 -3.05940073  2.676067394 1.0000000
## c_125_sh-b_125_ro  1.875000000 -0.64375969  4.393759691 0.4375875
## c_75_ro-b_125_ro   0.203571429 -2.14983971  2.556982567 1.0000000
## c_75_sh-b_125_ro   2.245000000  0.02366275  4.466337252 0.0445534
## d_125_ro-b_125_ro -0.058333333 -2.92606739  2.809400728 1.0000000
## d_125_sh-b_125_ro  2.308333333 -0.55940073  5.176067394 0.2940485
## d_75_ro-b_125_ro   0.287500000 -2.01180250  2.586802500 1.0000000
## d_75_sh-b_125_ro   3.115000000  0.89366275  5.336337252 0.0002474
## e_125_ro-b_125_ro -0.050000000 -2.70500583  2.605005834 1.0000000
## e_125_sh-b_125_ro  1.523000000 -0.99575969  4.041759691 0.7973188
## e_75_ro-b_125_ro   0.305000000 -1.91633725  2.526337252 1.0000000
## e_75_sh-b_125_ro   3.311363636  1.11906472  5.503662551 0.0000460
## b_75_ro-b_125_sh  -1.866666667 -4.12298776  0.389654426 0.2488673
## b_75_sh-b_125_sh   0.163636364 -2.02866255  2.355935278 1.0000000
## c_125_ro-b_125_sh -2.166666667 -5.03440073  0.701067394 0.4092393
## c_125_sh-b_125_sh -0.100000000 -2.61875969  2.418759691 1.0000000
## c_75_ro-b_125_sh  -1.771428571 -4.12483971  0.581982567 0.4163748
## c_75_sh-b_125_sh   0.270000000 -1.95133725  2.491337252 1.0000000
## d_125_ro-b_125_sh -2.033333333 -4.90106739  0.834400728 0.5314807
## d_125_sh-b_125_sh  0.333333333 -2.53440073  3.201067394 1.0000000
## d_75_ro-b_125_sh  -1.687500000 -3.98680250  0.611802500 0.4649536
## d_75_sh-b_125_sh   1.140000000 -1.08133725  3.361337252 0.9424024
## e_125_ro-b_125_sh -2.025000000 -4.68000583  0.630005834 0.3913463
## e_125_sh-b_125_sh -0.452000000 -2.97075969  2.066759691 1.0000000
## e_75_ro-b_125_sh  -1.670000000 -3.89133725  0.551337252 0.4186764
## e_75_sh-b_125_sh   1.336363636 -0.85593528  3.528662551 0.7865671
## b_75_sh-b_75_ro    2.030303030  0.34267054  3.717935522 0.0042706
## c_125_ro-b_75_ro  -0.300000000 -2.80316351  2.203163506 1.0000000
## c_125_sh-b_75_ro   1.766666667 -0.32763018  3.860963512 0.2190466
## c_75_ro-b_75_ro    0.095238095 -1.79697566  1.987451846 1.0000000
## c_75_sh-b_75_ro    2.136666667  0.41148028  3.861853057 0.0026438
## d_125_ro-b_75_ro  -0.166666667 -2.66983017  2.336496839 1.0000000
## d_125_sh-b_75_ro   2.200000000 -0.30316351  4.703163506 0.1630336
## d_75_ro-b_75_ro    0.179166667 -1.64531158  2.003644915 1.0000000
## d_75_sh-b_75_ro    3.006666667  1.28148028  4.731853057 0.0000010
## e_125_ro-b_75_ro  -0.158333333 -2.41465443  2.097987760 1.0000000
## e_125_sh-b_75_ro   1.414666667 -0.67963018  3.508963512 0.6222492
## e_75_ro-b_75_ro    0.196666667 -1.52851972  1.921853057 1.0000000
## e_75_sh-b_75_ro    3.203030303  1.51539781  4.890662795 0.0000001
## c_125_ro-b_75_sh  -2.330303030 -4.77591485  0.115308794 0.0815643
## c_125_sh-b_75_sh  -0.263636364 -2.28879535  1.761522626 1.0000000
## c_75_ro-b_75_sh   -1.935064935 -3.75046091 -0.119668963 0.0238538
## c_75_sh-b_75_sh    0.106363636 -1.53420265  1.746929922 1.0000000
## d_125_ro-b_75_sh  -2.196969697 -4.64258152  0.248642127 0.1371844
## d_125_sh-b_75_sh   0.169696970 -2.27591485  2.615308794 1.0000000
## d_75_ro-b_75_sh   -1.851136364 -3.59581700 -0.106455723 0.0252564
## d_75_sh-b_75_sh    0.976363636 -0.66420265  2.616929922 0.8174033
## e_125_ro-b_75_sh  -2.188636364 -4.38093528  0.003662551 0.0509047
## e_125_sh-b_75_sh  -0.615636364 -2.64079535  1.409522626 0.9998944
## e_75_ro-b_75_sh   -1.833636364 -3.47420265 -0.193070078 0.0127984
## e_75_sh-b_75_sh    1.172727273 -0.42830149  2.773756031 0.4687336
## c_125_sh-c_125_ro  2.066666667 -0.67541157  4.808744901 0.4138960
## c_75_ro-c_125_ro   0.395238095 -2.19578229  2.986258483 1.0000000
## c_75_sh-c_125_ro   2.436666667 -0.03500925  4.908342586 0.0581315
## d_125_ro-c_125_ro  0.133333333 -2.93240333  3.199070000 1.0000000
## d_125_sh-c_125_ro  2.500000000 -0.56573667  5.565736666 0.2721916
## d_75_ro-c_125_ro   0.479166667 -2.06280789  3.021141224 1.0000000
## d_75_sh-c_125_ro   3.306666667  0.83499075  5.778342586 0.0006467
## e_125_ro-c_125_ro  0.141666667 -2.72606739  3.009400728 1.0000000
## e_125_sh-c_125_ro  1.714666667 -1.02741157  4.456744901 0.7503946
## e_75_ro-c_125_ro   0.496666667 -1.97500925  2.968342586 0.9999999
## e_75_sh-c_125_ro   3.503030303  1.05741848  5.948642127 0.0001563
## c_75_ro-c_125_sh  -1.671428571 -3.86998227  0.527125132 0.3974656
## c_75_sh-c_125_sh   0.370000000 -1.68655868  2.426558676 1.0000000
## d_125_ro-c_125_sh -1.933333333 -4.67541157  0.808744901 0.5422463
## d_125_sh-c_125_sh  0.433333333 -2.30874490  3.175411568 1.0000000
## d_75_ro-c_125_sh  -1.587500000 -3.72803414  0.553034136 0.4447747
## d_75_sh-c_125_sh   1.240000000 -0.81655868  3.296558676 0.8010092
## e_125_ro-c_125_sh -1.925000000 -4.44375969  0.593759691 0.3875159
## e_125_sh-c_125_sh -0.352000000 -2.72670941  2.022709410 1.0000000
## e_75_ro-c_125_sh  -1.570000000 -3.62655868  0.486558676 0.3896172
## e_75_sh-c_125_sh   1.436363636 -0.58879535  3.461522626 0.5308821
## c_75_sh-c_75_ro    2.041428571  0.19106991  3.891787237 0.0152756
## d_125_ro-c_75_ro  -0.261904762 -2.85292515  2.329115625 1.0000000
## d_125_sh-c_75_ro   2.104761905 -0.48625848  4.695782292 0.2785904
## d_75_ro-c_75_ro    0.083928571 -1.85933672  2.027193862 1.0000000
## d_75_sh-c_75_ro    2.911428571  1.06106991  4.761787237 0.0000166
## e_125_ro-c_75_ro  -0.253571429 -2.60698257  2.099839709 1.0000000
## e_125_sh-c_75_ro   1.319428571 -0.87912513  3.517982275 0.8069973
## e_75_ro-c_75_ro    0.101428571 -1.74893009  1.951787237 1.0000000
## e_75_sh-c_75_ro    3.107792208  1.29239624  4.923188180 0.0000016
## d_125_ro-c_75_sh  -2.303333333 -4.77500925  0.168342586 0.1002174
## d_125_sh-c_75_sh   0.063333333 -2.40834259  2.535009253 1.0000000
## d_75_ro-c_75_sh   -1.957500000 -3.73853206 -0.176467942 0.0160712
## d_75_sh-c_75_sh    0.870000000 -0.80917313  2.549173128 0.9373721
## e_125_ro-c_75_sh  -2.295000000 -4.51633725 -0.073662748 0.0347256
## e_125_sh-c_75_sh  -0.722000000 -2.77855868  1.334558676 0.9992041
## e_75_ro-c_75_sh   -1.940000000 -3.61917313 -0.260826872 0.0079695
## e_75_sh-c_75_sh    1.066363636 -0.57420265  2.706929922 0.6892957
## d_125_sh-d_125_ro  2.366666667 -0.69907000  5.432403333 0.3687820
## d_75_ro-d_125_ro   0.345833333 -2.19614122  2.887807890 1.0000000
## d_75_sh-d_125_ro   3.173333333  0.70165741  5.645009253 0.0014056
## e_125_ro-d_125_ro  0.008333333 -2.85940073  2.876067394 1.0000000
## e_125_sh-d_125_ro  1.581333333 -1.16074490  4.323411568 0.8531902
## e_75_ro-d_125_ro   0.363333333 -2.10834259  2.835009253 1.0000000
## e_75_sh-d_125_ro   3.369696970  0.92408515  5.815308794 0.0003576
## d_75_ro-d_125_sh  -2.020833333 -4.56280789  0.521141224 0.3156233
## d_75_sh-d_125_sh   0.806666667 -1.66500925  3.278342586 0.9997076
## e_125_ro-d_125_sh -2.358333333 -5.22606739  0.509400728 0.2584301
## e_125_sh-d_125_sh -0.785333333 -3.52741157  1.956744901 0.9999564
## e_75_ro-d_125_sh  -2.003333333 -4.47500925  0.468342586 0.2823328
## e_75_sh-d_125_sh   1.003030303 -1.44258152  3.448642127 0.9943544
## d_75_sh-d_75_ro    2.827500000  1.04646794  4.608532058 0.0000132
## e_125_ro-d_75_ro  -0.337500000 -2.63680250  1.961802500 1.0000000
## e_125_sh-d_75_ro   1.235500000 -0.90503414  3.376034136 0.8522752
## e_75_ro-d_75_ro    0.017500000 -1.76353206  1.798532058 1.0000000
## e_75_sh-d_75_ro    3.023863636  1.27918300  4.768544277 0.0000011
## e_125_ro-d_75_sh  -3.165000000 -5.38633725 -0.943662748 0.0001756
## e_125_sh-d_75_sh  -1.592000000 -3.64855868  0.464558676 0.3636698
## e_75_ro-d_75_sh   -2.810000000 -4.48917313 -1.130826872 0.0000032
## e_75_sh-d_75_sh    0.196363636 -1.44420265  1.836929922 1.0000000
## e_125_sh-e_125_ro  1.573000000 -0.94575969  4.091759691 0.7522973
## e_75_ro-e_125_ro   0.355000000 -1.86633725  2.576337252 1.0000000
## e_75_sh-e_125_ro   3.361363636  1.16906472  5.553662551 0.0000319
## e_75_ro-e_125_sh  -1.218000000 -3.27455868  0.838558676 0.8232804
## e_75_sh-e_125_sh   1.788363636 -0.23679535  3.813522626 0.1571794
## e_75_sh-e_75_ro    3.006363636  1.36579735  4.646929922 0.0000002
P6 = Output$All.ID2[,'p adj']
stat.test<- multcompLetters(P6)
stat.test
## a_125_sh  a_75_ro  a_75_sh b_125_ro b_125_sh  b_75_ro  b_75_sh c_125_ro 
##   "abcd"    "abc"      "d"     "ab"   "abcd"      "a"    "bcd"    "abc" 
## c_125_sh  c_75_ro  c_75_sh d_125_ro d_125_sh  d_75_ro  d_75_sh e_125_ro 
##   "abcd"      "a"     "cd"    "abc"   "abcd"      "a"      "d"     "ab" 
## e_125_sh  e_75_ro  e_75_sh a_125_ro 
##   "abcd"      "a"      "d"      "a"
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] "125"
test$info[[1]][3]
## [1] "sh"
test$Accession <- "none"
test$Condition<- "none"
test$Tissue<- "none"
test
for(i in 1:nrow(test)){
  test$Accession[i] <- test$info[[i]][1]
  test$Condition[i] <- test$info[[i]][2]
  test$Tissue[i] <- test$info[[i]][3]
  
}

test2 <- test[,c(5:7,1)]
test2$group1 <- test2$Accession
test2$group2 <- test2$Accession


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

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

DW_wd <- DW_wd + stat_summary(fun=mean, geom="point", shape=95, size=6, color="black", fill="black")
DW_wd <- DW_wd + scale_color_manual(values = c("blue", "plum", "rosybrown1", "hotpink","red"))
DW_wd <- DW_wd + ylab("Dry weight, mg") + xlab("")+stat_pvalue_manual(test2, label = "Tukey", y.position = 3)
DW_wd <- DW_wd + theme(axis.text.x = element_text(angle=90, hjust=0.9, vjust=0.5))
DW_wd <- DW_wd + rremove("legend")
DW_wd

#library(cowplot)

#pdf("ICP-all-cyto.pdf", height = 5, width = 12)
#plot_grid(Na_content_cyto,K_content_cyto,Na.K_ratio, ncol=3,
          #align = "hv", labels=c("AUTO"), 
          #label_size = 24)
#dev.off()