this experiment was performed on January 2022 in order to address whether there is a difference in tissue accumulation of the 3 tomato accessions, M248, M058, LA1511. These samples were grown similar to RSA set-up , 4 d on germination/control plates, d5 to +/- 100 mM salt, and then tissues including stem, leaves, and roots were harvested after 10 d on salt.
getwd()
## [1] "C:/Users/Julkowska Lab/Desktop/R codes by Maryam/20220617_ICP-MS_FW_DW_3tissues_M248M058LA1511_Plate_Grown"
setwd( "C:/Users/Julkowska Lab/Desktop/R codes by Maryam/20220617_ICP-MS_FW_DW_3tissues_M248M058LA1511_Plate_Grown/")
list.files(pattern = ".csv")
## [1] "20220124_root_leaf_stem_separated_ICP_LA1511_M058_M248_freshWeight v2.csv"
## [2] "Eric04122022Rack 1 and 2 _3tomato_accessions_3tissue_types_plate_analyzed for R.csv"
ICP<- read.csv("Eric04122022Rack 1 and 2 _3tomato_accessions_3tissue_types_plate_analyzed for R.csv")
ICP
library(ggplot2)
## Warning: package 'ggplot2' was built under R version 4.0.5
library(ggpubr)
## Warning: package 'ggpubr' was built under R version 4.0.5
library(multcompView)
## Warning: package 'multcompView' was built under R version 4.0.5
ICP$All.ID <- paste(ICP$Accession,ICP$Condition, ICP$Tissue, sep="_")
ICP
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 280614.03 23341.32
## Deg. of Freedom 17 240
##
## Residual standard error: 9.861821
## 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
## LA1511_C_R-LA1511_C_L -0.28488585 -13.9292039 13.359432 1.0000000
## LA1511_C_S-LA1511_C_L 2.05162953 -11.5926885 15.695948 1.0000000
## LA1511_S_L-LA1511_C_L 28.63130032 14.9869823 42.275618 0.0000000
## LA1511_S_R-LA1511_C_L 29.84774507 16.2034270 43.492063 0.0000000
## LA1511_S_S-LA1511_C_L 75.40693021 61.7626122 89.051248 0.0000000
## M058_C_L-LA1511_C_L -0.21686102 -13.3985246 12.964803 1.0000000
## M058_C_R-LA1511_C_L -0.25547190 -13.4371354 12.926192 1.0000000
## M058_C_S-LA1511_C_L 2.27743473 -10.9042288 15.459098 1.0000000
## M058_S_L-LA1511_C_L 36.49229585 23.3106323 49.673959 0.0000000
## M058_S_R-LA1511_C_L 39.18417564 26.0025121 52.365839 0.0000000
## M058_S_S-LA1511_C_L 89.27833259 76.0966690 102.459996 0.0000000
## M248_C_L-LA1511_C_L 0.60734875 -12.5743148 13.789012 1.0000000
## M248_C_R-LA1511_C_L 0.46494316 -12.7167204 13.646607 1.0000000
## M248_C_S-LA1511_C_L 2.76074996 -10.4209136 15.942414 0.9999992
## M248_S_L-LA1511_C_L 54.09213468 40.9104711 67.273798 0.0000000
## M248_S_R-LA1511_C_L 41.23183183 28.0501683 54.413495 0.0000000
## M248_S_S-LA1511_C_L 102.77657585 89.5949123 115.958239 0.0000000
## LA1511_C_S-LA1511_C_R 2.33651538 -11.3078027 15.980833 1.0000000
## LA1511_S_L-LA1511_C_R 28.91618617 15.2718681 42.560504 0.0000000
## LA1511_S_R-LA1511_C_R 30.13263092 16.4883129 43.776949 0.0000000
## LA1511_S_S-LA1511_C_R 75.69181606 62.0474980 89.336134 0.0000000
## M058_C_L-LA1511_C_R 0.06802483 -13.1136387 13.249688 1.0000000
## M058_C_R-LA1511_C_R 0.02941395 -13.1522496 13.211078 1.0000000
## M058_C_S-LA1511_C_R 2.56232058 -10.6193430 15.743984 0.9999998
## M058_S_L-LA1511_C_R 36.77718170 23.5955182 49.958845 0.0000000
## M058_S_R-LA1511_C_R 39.46906149 26.2873979 52.650725 0.0000000
## M058_S_S-LA1511_C_R 89.56321844 76.3815549 102.744882 0.0000000
## M248_C_L-LA1511_C_R 0.89223460 -12.2894289 14.073898 1.0000000
## M248_C_R-LA1511_C_R 0.74982901 -12.4318345 13.931493 1.0000000
## M248_C_S-LA1511_C_R 3.04563581 -10.1360277 16.227299 0.9999966
## M248_S_L-LA1511_C_R 54.37702053 41.1953570 67.558684 0.0000000
## M248_S_R-LA1511_C_R 41.51671768 28.3350541 54.698381 0.0000000
## M248_S_S-LA1511_C_R 103.06146170 89.8797982 116.243125 0.0000000
## LA1511_S_L-LA1511_C_S 26.57967079 12.9353527 40.223989 0.0000000
## LA1511_S_R-LA1511_C_S 27.79611554 14.1517975 41.440434 0.0000000
## LA1511_S_S-LA1511_C_S 73.35530068 59.7109826 86.999619 0.0000000
## M058_C_L-LA1511_C_S -2.26849055 -15.4501541 10.913173 1.0000000
## M058_C_R-LA1511_C_S -2.30710143 -15.4887650 10.874562 1.0000000
## M058_C_S-LA1511_C_S 0.22580520 -12.9558583 13.407469 1.0000000
## M058_S_L-LA1511_C_S 34.44066632 21.2590028 47.622330 0.0000000
## M058_S_R-LA1511_C_S 37.13254611 23.9508826 50.314210 0.0000000
## M058_S_S-LA1511_C_S 87.22670306 74.0450395 100.408367 0.0000000
## M248_C_L-LA1511_C_S -1.44428078 -14.6259443 11.737383 1.0000000
## M248_C_R-LA1511_C_S -1.58668637 -14.7683499 11.594977 1.0000000
## M248_C_S-LA1511_C_S 0.70912043 -12.4725431 13.890784 1.0000000
## M248_S_L-LA1511_C_S 52.04050515 38.8588416 65.222169 0.0000000
## M248_S_R-LA1511_C_S 39.18020230 25.9985388 52.361866 0.0000000
## M248_S_S-LA1511_C_S 100.72494632 87.5432828 113.906610 0.0000000
## LA1511_S_R-LA1511_S_L 1.21644475 -12.4278733 14.860763 1.0000000
## LA1511_S_S-LA1511_S_L 46.77562990 33.1313119 60.419948 0.0000000
## M058_C_L-LA1511_S_L -28.84816134 -42.0298249 -15.666498 0.0000000
## M058_C_R-LA1511_S_L -28.88677221 -42.0684358 -15.705109 0.0000000
## M058_C_S-LA1511_S_L -26.35386559 -39.5355291 -13.172202 0.0000000
## M058_S_L-LA1511_S_L 7.86099553 -5.3206680 21.042659 0.8115864
## M058_S_R-LA1511_S_L 10.55287532 -2.6287882 23.734539 0.3053025
## M058_S_S-LA1511_S_L 60.64703227 47.4653687 73.828696 0.0000000
## M248_C_L-LA1511_S_L -28.02395157 -41.2056151 -14.842288 0.0000000
## M248_C_R-LA1511_S_L -28.16635716 -41.3480207 -14.984694 0.0000000
## M248_C_S-LA1511_S_L -25.87055036 -39.0522139 -12.688887 0.0000000
## M248_S_L-LA1511_S_L 25.46083436 12.2791708 38.642498 0.0000000
## M248_S_R-LA1511_S_L 12.60053151 -0.5811320 25.782195 0.0794857
## M248_S_S-LA1511_S_L 74.14527553 60.9636120 87.326939 0.0000000
## LA1511_S_S-LA1511_S_R 45.55918515 31.9148671 59.203503 0.0000000
## M058_C_L-LA1511_S_R -30.06460609 -43.2462696 -16.882943 0.0000000
## M058_C_R-LA1511_S_R -30.10321696 -43.2848805 -16.921553 0.0000000
## M058_C_S-LA1511_S_R -27.57031034 -40.7519739 -14.388647 0.0000000
## M058_S_L-LA1511_S_R 6.64455078 -6.5371128 19.826214 0.9475774
## M058_S_R-LA1511_S_R 9.33643057 -3.8452330 22.518094 0.5339759
## M058_S_S-LA1511_S_R 59.43058752 46.2489240 72.612251 0.0000000
## M248_C_L-LA1511_S_R -29.24039631 -42.4220599 -16.058733 0.0000000
## M248_C_R-LA1511_S_R -29.38280191 -42.5644655 -16.201138 0.0000000
## M248_C_S-LA1511_S_R -27.08699511 -40.2686587 -13.905332 0.0000000
## M248_S_L-LA1511_S_R 24.24438961 11.0627261 37.426053 0.0000001
## M248_S_R-LA1511_S_R 11.38408676 -1.7975768 24.565750 0.1872703
## M248_S_S-LA1511_S_R 72.92883078 59.7471672 86.110494 0.0000000
## M058_C_L-LA1511_S_S -75.62379124 -88.8054548 -62.442128 0.0000000
## M058_C_R-LA1511_S_S -75.66240211 -88.8440657 -62.480739 0.0000000
## M058_C_S-LA1511_S_S -73.12949549 -86.3111590 -59.947832 0.0000000
## M058_S_L-LA1511_S_S -38.91463437 -52.0962979 -25.732971 0.0000000
## M058_S_R-LA1511_S_S -36.22275458 -49.4044181 -23.041091 0.0000000
## M058_S_S-LA1511_S_S 13.87140237 0.6897388 27.053066 0.0276694
## M248_C_L-LA1511_S_S -74.79958146 -87.9812450 -61.617918 0.0000000
## M248_C_R-LA1511_S_S -74.94198706 -88.1236506 -61.760324 0.0000000
## M248_C_S-LA1511_S_S -72.64618025 -85.8278438 -59.464517 0.0000000
## M248_S_L-LA1511_S_S -21.31479554 -34.4964591 -8.133132 0.0000051
## M248_S_R-LA1511_S_S -34.17509839 -47.3567619 -20.993435 0.0000000
## M248_S_S-LA1511_S_S 27.36964563 14.1879821 40.551309 0.0000000
## M058_C_R-M058_C_L -0.03861087 -12.7407797 12.663558 1.0000000
## M058_C_S-M058_C_L 2.49429575 -10.2078731 15.196465 0.9999997
## M058_S_L-M058_C_L 36.70915687 24.0069880 49.411326 0.0000000
## M058_S_R-M058_C_L 39.40103666 26.6988678 52.103205 0.0000000
## M058_S_S-M058_C_L 89.49519361 76.7930248 102.197362 0.0000000
## M248_C_L-M058_C_L 0.82420977 -11.8779591 13.526379 1.0000000
## M248_C_R-M058_C_L 0.68180418 -12.0203646 13.383973 1.0000000
## M248_C_S-M058_C_L 2.97761098 -9.7245578 15.679780 0.9999958
## M248_S_L-M058_C_L 54.30899570 41.6068269 67.011165 0.0000000
## M248_S_R-M058_C_L 41.44869285 28.7465240 54.150862 0.0000000
## M248_S_S-M058_C_L 102.99343687 90.2912680 115.695606 0.0000000
## M058_C_S-M058_C_R 2.53290662 -10.1692622 15.235075 0.9999996
## M058_S_L-M058_C_R 36.74776774 24.0455989 49.449937 0.0000000
## M058_S_R-M058_C_R 39.43964753 26.7374787 52.141816 0.0000000
## M058_S_S-M058_C_R 89.53380448 76.8316357 102.235973 0.0000000
## M248_C_L-M058_C_R 0.86282065 -11.8393482 13.564989 1.0000000
## M248_C_R-M058_C_R 0.72041505 -11.9817538 13.422584 1.0000000
## M248_C_S-M058_C_R 3.01622186 -9.6859470 15.718391 0.9999949
## M248_S_L-M058_C_R 54.34760657 41.6454377 67.049775 0.0000000
## M248_S_R-M058_C_R 41.48730372 28.7851349 54.189473 0.0000000
## M248_S_S-M058_C_R 103.03204774 90.3298789 115.734217 0.0000000
## M058_S_L-M058_C_S 34.21486112 21.5126923 46.917030 0.0000000
## M058_S_R-M058_C_S 36.90674091 24.2045721 49.608910 0.0000000
## M058_S_S-M058_C_S 87.00089786 74.2987290 99.703067 0.0000000
## M248_C_L-M058_C_S -1.67008598 -14.3722548 11.032083 1.0000000
## M248_C_R-M058_C_S -1.81249157 -14.5146604 10.889677 1.0000000
## M248_C_S-M058_C_S 0.48331523 -12.2188536 13.185484 1.0000000
## M248_S_L-M058_C_S 51.81469995 39.1125311 64.516869 0.0000000
## M248_S_R-M058_C_S 38.95439710 26.2522283 51.656566 0.0000000
## M248_S_S-M058_C_S 100.49914112 87.7969723 113.201310 0.0000000
## M058_S_R-M058_S_L 2.69187979 -10.0102890 15.394049 0.9999991
## M058_S_S-M058_S_L 52.78603674 40.0838679 65.488206 0.0000000
## M248_C_L-M058_S_L -35.88494710 -48.5871159 -23.182778 0.0000000
## M248_C_R-M058_S_L -36.02735269 -48.7295215 -23.325184 0.0000000
## M248_C_S-M058_S_L -33.73154589 -46.4337147 -21.029377 0.0000000
## M248_S_L-M058_S_L 17.59983883 4.8976700 30.302008 0.0002648
## M248_S_R-M058_S_L 4.73953598 -7.9626328 17.441705 0.9977106
## M248_S_S-M058_S_L 66.28428000 53.5821112 78.986449 0.0000000
## M058_S_S-M058_S_R 50.09415695 37.3919881 62.796326 0.0000000
## M248_C_L-M058_S_R -38.57682689 -51.2789957 -25.874658 0.0000000
## M248_C_R-M058_S_R -38.71923248 -51.4214013 -26.017064 0.0000000
## M248_C_S-M058_S_R -36.42342568 -49.1255945 -23.721257 0.0000000
## M248_S_L-M058_S_R 14.90795904 2.2057902 27.610128 0.0059976
## M248_S_R-M058_S_R 2.04765619 -10.6545126 14.749825 1.0000000
## M248_S_S-M058_S_R 63.59240021 50.8902314 76.294569 0.0000000
## M248_C_L-M058_S_S -88.67098384 -101.3731527 -75.968815 0.0000000
## M248_C_R-M058_S_S -88.81338943 -101.5155583 -76.111221 0.0000000
## M248_C_S-M058_S_S -86.51758263 -99.2197515 -73.815414 0.0000000
## M248_S_L-M058_S_S -35.18619791 -47.8883667 -22.484029 0.0000000
## M248_S_R-M058_S_S -48.04650076 -60.7486696 -35.344332 0.0000000
## M248_S_S-M058_S_S 13.49824326 0.7960744 26.200412 0.0244897
## M248_C_R-M248_C_L -0.14240560 -12.8445744 12.559763 1.0000000
## M248_C_S-M248_C_L 2.15340121 -10.5487676 14.855570 1.0000000
## M248_S_L-M248_C_L 53.48478593 40.7826171 66.186955 0.0000000
## M248_S_R-M248_C_L 40.62448308 27.9223143 53.326652 0.0000000
## M248_S_S-M248_C_L 102.16922709 89.4670583 114.871396 0.0000000
## M248_C_S-M248_C_R 2.29580680 -10.4063620 14.997976 0.9999999
## M248_S_L-M248_C_R 53.62719152 40.9250227 66.329360 0.0000000
## M248_S_R-M248_C_R 40.76688867 28.0647198 53.469057 0.0000000
## M248_S_S-M248_C_R 102.31163269 89.6094639 115.013802 0.0000000
## M248_S_L-M248_C_S 51.33138472 38.6292159 64.033554 0.0000000
## M248_S_R-M248_C_S 38.47108187 25.7689130 51.173251 0.0000000
## M248_S_S-M248_C_S 100.01582588 87.3136571 112.717995 0.0000000
## M248_S_R-M248_S_L -12.86030285 -25.5624717 -0.158134 0.0436072
## M248_S_S-M248_S_L 48.68444117 35.9822723 61.386610 0.0000000
## M248_S_S-M248_S_R 61.54474402 48.8425752 74.246913 0.0000000
P9 = Output$All.ID[,'p adj']
stat.test<- multcompLetters(P9)
stat.test
## LA1511_C_R LA1511_C_S LA1511_S_L LA1511_S_R LA1511_S_S M058_C_L M058_C_R
## "a" "a" "b" "b" "c" "a" "a"
## M058_C_S M058_S_L M058_S_R M058_S_S M248_C_L M248_C_R M248_C_S
## "a" "b" "b" "d" "a" "a" "a"
## M248_S_L M248_S_R M248_S_S LA1511_C_L
## "e" "b" "f" "a"
test <- as.data.frame(stat.test$Letters)
test$group1 <- rownames(test)
test$group2 <- rownames(test)
colnames(test)[1] <- "Tukey"
test
ICP$Tissue <- factor(ICP$Tissue, levels = c("L", "S", "R"))
Na_content <- ggplot(data = ICP, mapping = aes(x = All.ID, y = Na.con.mg.mg.dry.weight, colour = Condition))
Na_content <- Na_content + geom_boxplot(alpha=0.2) + geom_jitter(width=0.1,alpha=0.2)
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","red"))
Na_content <- Na_content + ylab("Na content, mg/mg dry weight") + xlab("") #+ ggtitle("")
Na_content <- Na_content + theme(axis.text.x = element_text(angle=90, hjust=0.9, vjust=0.5))
Na_content <- Na_content + stat_pvalue_manual(test, label = "Tukey", y.position = 150)
Na_content
Na_content <- ggplot(data = ICP, mapping = aes(x = Condition, y = Na.con.mg.mg.dry.weight, colour = Condition))
Na_content <- Na_content + geom_boxplot(alpha=0.2) + geom_jitter(width=0.1,alpha=0.2)
Na_content <- Na_content + facet_grid(Tissue ~ Accession)
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","red"))
Na_content <- Na_content + ylab("Na content, mg/mg dry weight") + xlab("")
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
Na_content <- ggplot(data = ICP, mapping = aes(x = Tissue, y = Na.con.mg.mg.dry.weight, colour = Condition))
Na_content <- Na_content + geom_boxplot(alpha=0.2) + geom_jitter(width=0.1,alpha=0.2)
Na_content <- Na_content + facet_grid(Condition ~ Accession)
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","red"))
Na_content <- Na_content + ylab("Na content, mg/mg dry weight") + xlab("")
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
Na_content <- ggplot(data = ICP, mapping = aes(x = Accession, y = Na.con.mg.mg.dry.weight, colour = Condition))
Na_content <- Na_content + geom_boxplot(alpha=0.2) + geom_jitter(width=0.1,alpha=0.2)
Na_content <- Na_content + facet_grid(Condition ~ Tissue)
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","red"))
Na_content <- Na_content + ylab("Na content, mg/mg dry weight") + xlab("")
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 299308.12 57248.52
## Deg. of Freedom 17 240
##
## Residual standard error: 15.44459
## 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
## LA1511_C_R-LA1511_C_L 27.1733169 5.804954 48.5416800 0.0015122
## LA1511_C_S-LA1511_C_L 68.2161069 46.847744 89.5844699 0.0000000
## LA1511_S_L-LA1511_C_L -16.9970909 -38.365454 4.3712721 0.3165340
## LA1511_S_R-LA1511_C_L -2.7674902 -24.135853 18.6008729 1.0000000
## LA1511_S_S-LA1511_C_L 10.3291329 -11.039230 31.6974960 0.9640016
## M058_C_L-LA1511_C_L 1.8854339 -18.758366 22.5292338 1.0000000
## M058_C_R-LA1511_C_L 28.7669697 8.123170 49.4107697 0.0002333
## M058_C_S-LA1511_C_L 95.2409643 74.597164 115.8847643 0.0000000
## M058_S_L-LA1511_C_L -24.5712108 -45.215011 -3.9274108 0.0047902
## M058_S_R-LA1511_C_L -1.4976554 -22.141455 19.1461446 1.0000000
## M058_S_S-LA1511_C_L -18.3548887 -38.998689 2.2889112 0.1502011
## M248_C_L-LA1511_C_L 2.5718172 -18.071983 23.2156172 1.0000000
## M248_C_R-LA1511_C_L 14.0676534 -6.576147 34.7114533 0.6057841
## M248_C_S-LA1511_C_L 77.2001131 56.556313 97.8439130 0.0000000
## M248_S_L-LA1511_C_L -21.9299732 -42.573773 -1.2861732 0.0245973
## M248_S_R-LA1511_C_L -0.8760233 -21.519823 19.7677767 1.0000000
## M248_S_S-LA1511_C_L -11.6714824 -32.315282 8.9723176 0.8691940
## LA1511_C_S-LA1511_C_R 41.0427900 19.674427 62.4111530 0.0000000
## LA1511_S_L-LA1511_C_R -44.1704079 -65.538771 -22.8020448 0.0000000
## LA1511_S_R-LA1511_C_R -29.9408071 -51.309170 -8.5724441 0.0002063
## LA1511_S_S-LA1511_C_R -16.8441840 -38.212547 4.5241791 0.3325433
## M058_C_L-LA1511_C_R -25.2878831 -45.931683 -4.6440831 0.0029591
## M058_C_R-LA1511_C_R 1.5936528 -19.050147 22.2374528 1.0000000
## M058_C_S-LA1511_C_R 68.0676474 47.423847 88.7114473 0.0000000
## M058_S_L-LA1511_C_R -51.7445277 -72.388328 -31.1007278 0.0000000
## M058_S_R-LA1511_C_R -28.6709723 -49.314772 -8.0271724 0.0002513
## M058_S_S-LA1511_C_R -45.5282057 -66.172006 -24.8844057 0.0000000
## M248_C_L-LA1511_C_R -24.6014997 -45.245300 -3.9576997 0.0046951
## M248_C_R-LA1511_C_R -13.1056636 -33.749464 7.5381364 0.7252190
## M248_C_S-LA1511_C_R 50.0267961 29.382996 70.6705961 0.0000000
## M248_S_L-LA1511_C_R -49.1032901 -69.747090 -28.4594902 0.0000000
## M248_S_R-LA1511_C_R -28.0493402 -48.693140 -7.4055403 0.0004043
## M248_S_S-LA1511_C_R -38.8447993 -59.488599 -18.2009993 0.0000000
## LA1511_S_L-LA1511_C_S -85.2131978 -106.581561 -63.8448348 0.0000000
## LA1511_S_R-LA1511_C_S -70.9835971 -92.351960 -49.6152340 0.0000000
## LA1511_S_S-LA1511_C_S -57.8869739 -79.255337 -36.5186109 0.0000000
## M058_C_L-LA1511_C_S -66.3306730 -86.974473 -45.6868731 0.0000000
## M058_C_R-LA1511_C_S -39.4491372 -60.092937 -18.8053372 0.0000000
## M058_C_S-LA1511_C_S 27.0248574 6.381057 47.6686574 0.0008666
## M058_S_L-LA1511_C_S -92.7873177 -113.431118 -72.1435177 0.0000000
## M058_S_R-LA1511_C_S -69.7137623 -90.357562 -49.0699623 0.0000000
## M058_S_S-LA1511_C_S -86.5709956 -107.214796 -65.9271957 0.0000000
## M248_C_L-LA1511_C_S -65.6442897 -86.288090 -45.0004897 0.0000000
## M248_C_R-LA1511_C_S -54.1484535 -74.792253 -33.5046536 0.0000000
## M248_C_S-LA1511_C_S 8.9840062 -11.659794 29.6278061 0.9871833
## M248_S_L-LA1511_C_S -90.1460801 -110.789880 -69.5022801 0.0000000
## M248_S_R-LA1511_C_S -69.0921302 -89.735930 -48.4483302 0.0000000
## M248_S_S-LA1511_C_S -79.8875893 -100.531389 -59.2437893 0.0000000
## LA1511_S_R-LA1511_S_L 14.2296007 -7.138762 35.5979638 0.6467476
## LA1511_S_S-LA1511_S_L 27.3262239 5.957861 48.6945869 0.0013612
## M058_C_L-LA1511_S_L 18.8825248 -1.761275 39.5263247 0.1188905
## M058_C_R-LA1511_S_L 45.7640606 25.120261 66.4078606 0.0000000
## M058_C_S-LA1511_S_L 112.2380552 91.594255 132.8818552 0.0000000
## M058_S_L-LA1511_S_L -7.5741199 -28.217920 13.0696801 0.9981294
## M058_S_R-LA1511_S_L 15.4994355 -5.144364 36.1432355 0.4226951
## M058_S_S-LA1511_S_L -1.3577978 -22.001598 19.2860021 1.0000000
## M248_C_L-LA1511_S_L 19.5689082 -1.074892 40.2127081 0.0861348
## M248_C_R-LA1511_S_L 31.0647443 10.420944 51.7085443 0.0000370
## M248_C_S-LA1511_S_L 94.1972040 73.553404 114.8410040 0.0000000
## M248_S_L-LA1511_S_L -4.9328823 -25.576682 15.7109177 0.9999944
## M248_S_R-LA1511_S_L 16.1210676 -4.522732 36.7648676 0.3494476
## M248_S_S-LA1511_S_L 5.3256085 -15.318191 25.9694085 0.9999829
## LA1511_S_S-LA1511_S_R 13.0966231 -8.271740 34.4649862 0.7762704
## M058_C_L-LA1511_S_R 4.6529241 -15.990876 25.2967240 0.9999977
## M058_C_R-LA1511_S_R 31.5344599 10.890660 52.1782599 0.0000250
## M058_C_S-LA1511_S_R 98.0084545 77.364655 118.6522545 0.0000000
## M058_S_L-LA1511_S_R -21.8037206 -42.447521 -1.1599207 0.0264421
## M058_S_R-LA1511_S_R 1.2698348 -19.373965 21.9136347 1.0000000
## M058_S_S-LA1511_S_R -15.5873986 -36.231199 5.0564014 0.4119733
## M248_C_L-LA1511_S_R 5.3393074 -15.304493 25.9831074 0.9999823
## M248_C_R-LA1511_S_R 16.8351436 -3.808656 37.4789435 0.2739931
## M248_C_S-LA1511_S_R 79.9676033 59.323803 100.6114032 0.0000000
## M248_S_L-LA1511_S_R -19.1624830 -39.806283 1.4813170 0.1044999
## M248_S_R-LA1511_S_R 1.8914669 -18.752333 22.5352669 1.0000000
## M248_S_S-LA1511_S_R -8.9039922 -29.547792 11.7398078 0.9883290
## M058_C_L-LA1511_S_S -8.4436991 -29.087499 12.2001009 0.9934181
## M058_C_R-LA1511_S_S 18.4378368 -2.205963 39.0816367 0.1449010
## M058_C_S-LA1511_S_S 84.9118314 64.268031 105.5556313 0.0000000
## M058_S_L-LA1511_S_S -34.9003438 -55.544144 -14.2565438 0.0000013
## M058_S_R-LA1511_S_S -11.8267884 -32.470588 8.8170116 0.8562932
## M058_S_S-LA1511_S_S -28.6840217 -49.327822 -8.0402217 0.0002488
## M248_C_L-LA1511_S_S -7.7573157 -28.401116 12.8864843 0.9975103
## M248_C_R-LA1511_S_S 3.7385204 -16.905280 24.3823204 0.9999999
## M248_C_S-LA1511_S_S 66.8709801 46.227180 87.5147801 0.0000000
## M248_S_L-LA1511_S_S -32.2591061 -52.902906 -11.6153062 0.0000135
## M248_S_R-LA1511_S_S -11.2051562 -31.848956 9.4386437 0.9035825
## M248_S_S-LA1511_S_S -22.0006153 -42.644415 -1.3568154 0.0236160
## M058_C_R-M058_C_L 26.8815359 6.988672 46.7743993 0.0004539
## M058_C_S-M058_C_L 93.3555305 73.462667 113.2483939 0.0000000
## M058_S_L-M058_C_L -26.4566447 -46.349508 -6.5637813 0.0006311
## M058_S_R-M058_C_L -3.3830893 -23.275953 16.5097741 1.0000000
## M058_S_S-M058_C_L -20.2403226 -40.133186 -0.3474592 0.0412387
## M248_C_L-M058_C_L 0.6863834 -19.206480 20.5792468 1.0000000
## M248_C_R-M058_C_L 12.1822195 -7.710644 32.0750829 0.7773945
## M248_C_S-M058_C_L 75.3146792 55.421816 95.2075426 0.0000000
## M248_S_L-M058_C_L -23.8154070 -43.708270 -3.9225436 0.0043559
## M248_S_R-M058_C_L -2.7614572 -22.654321 17.1314062 1.0000000
## M248_S_S-M058_C_L -13.5569162 -33.449780 6.3359472 0.6056522
## M058_C_S-M058_C_R 66.4739946 46.581131 86.3668580 0.0000000
## M058_S_L-M058_C_R -53.3381805 -73.231044 -33.4453171 0.0000000
## M058_S_R-M058_C_R -30.2646251 -50.157489 -10.3717617 0.0000278
## M058_S_S-M058_C_R -47.1218585 -67.014722 -27.2289951 0.0000000
## M248_C_L-M058_C_R -26.1951525 -46.088016 -6.3022891 0.0007712
## M248_C_R-M058_C_R -14.6993164 -34.592180 5.1935470 0.4530977
## M248_C_S-M058_C_R 48.4331434 28.540280 68.3260068 0.0000000
## M248_S_L-M058_C_R -50.6969429 -70.589806 -30.8040795 0.0000000
## M248_S_R-M058_C_R -29.6429930 -49.535856 -9.7501296 0.0000474
## M248_S_S-M058_C_R -40.4384521 -60.331315 -20.5455887 0.0000000
## M058_S_L-M058_C_S -119.8121751 -139.705039 -99.9193117 0.0000000
## M058_S_R-M058_C_S -96.7386197 -116.631483 -76.8457563 0.0000000
## M058_S_S-M058_C_S -113.5958531 -133.488716 -93.7029897 0.0000000
## M248_C_L-M058_C_S -92.6691471 -112.562010 -72.7762837 0.0000000
## M248_C_R-M058_C_S -81.1733109 -101.066174 -61.2804475 0.0000000
## M248_C_S-M058_C_S -18.0408512 -37.933715 1.8520122 0.1278286
## M248_S_L-M058_C_S -117.1709375 -137.063801 -97.2780741 0.0000000
## M248_S_R-M058_C_S -96.1169876 -116.009851 -76.2241242 0.0000000
## M248_S_S-M058_C_S -106.9124467 -126.805310 -87.0195833 0.0000000
## M058_S_R-M058_S_L 23.0735554 3.180692 42.9664188 0.0072072
## M058_S_S-M058_S_L 6.2163221 -13.676541 26.1091855 0.9997564
## M248_C_L-M058_S_L 27.1430280 7.250165 47.0358914 0.0003696
## M248_C_R-M058_S_L 38.6388642 18.746001 58.5317276 0.0000000
## M248_C_S-M058_S_L 101.7713239 81.878460 121.6641873 0.0000000
## M248_S_L-M058_S_L 2.6412376 -17.251626 22.5341010 1.0000000
## M248_S_R-M058_S_L 23.6951875 3.802324 43.5880509 0.0047321
## M248_S_S-M058_S_L 12.8997284 -6.993135 32.7925918 0.6915751
## M058_S_S-M058_S_R -16.8572333 -36.750097 3.0356301 0.2140527
## M248_C_L-M058_S_R 4.0694726 -15.823391 23.9623361 0.9999995
## M248_C_R-M058_S_R 15.5653088 -4.327555 35.4581722 0.3458727
## M248_C_S-M058_S_R 78.6977685 58.804905 98.5906319 0.0000000
## M248_S_L-M058_S_R -20.4323178 -40.325181 -0.5394544 0.0369961
## M248_S_R-M058_S_R 0.6216321 -19.271231 20.5144955 1.0000000
## M248_S_S-M058_S_R -10.1738270 -30.066690 9.7190364 0.9406068
## M248_C_L-M058_S_S 20.9267060 1.033843 40.8195694 0.0277848
## M248_C_R-M058_S_S 32.4225421 12.529679 52.3154055 0.0000041
## M248_C_S-M058_S_S 95.5550018 75.662138 115.4478652 0.0000000
## M248_S_L-M058_S_S -3.5750844 -23.467948 16.3177790 0.9999999
## M248_S_R-M058_S_S 17.4788654 -2.413998 37.3717289 0.1647031
## M248_S_S-M058_S_S 6.6834064 -13.209457 26.5762698 0.9993737
## M248_C_R-M248_C_L 11.4958361 -8.397027 31.3886995 0.8473448
## M248_C_S-M248_C_L 74.6282958 54.735432 94.5211592 0.0000000
## M248_S_L-M248_C_L -24.5017904 -44.394654 -4.6089270 0.0026908
## M248_S_R-M248_C_L -3.4478405 -23.340704 16.4450229 1.0000000
## M248_S_S-M248_C_L -14.2432996 -34.136163 5.6495638 0.5133905
## M248_C_S-M248_C_R 63.1324597 43.239596 83.0253231 0.0000000
## M248_S_L-M248_C_R -35.9976266 -55.890490 -16.1047632 0.0000001
## M248_S_R-M248_C_R -14.9436767 -34.836540 4.9491867 0.4216728
## M248_S_S-M248_C_R -25.7391357 -45.631999 -5.8462723 0.0010887
## M248_S_L-M248_C_S -99.1300863 -119.022950 -79.2372229 0.0000000
## M248_S_R-M248_C_S -78.0761364 -97.969000 -58.1832730 0.0000000
## M248_S_S-M248_C_S -88.8715954 -108.764459 -68.9787320 0.0000000
## M248_S_R-M248_S_L 21.0539499 1.161086 40.9468133 0.0257709
## M248_S_S-M248_S_L 10.2584908 -9.634373 30.1513542 0.9362862
## M248_S_S-M248_S_R -10.7954591 -30.688322 9.0974043 0.9037278
P8 = Output$All.ID[,'p adj']
stat.test<- multcompLetters(P8)
stat.test
## LA1511_C_R LA1511_C_S LA1511_S_L LA1511_S_R LA1511_S_S M058_C_L M058_C_R
## "a" "b" "cdef" "cdeg" "ag" "cg" "a"
## M058_C_S M058_S_L M058_S_R M058_S_S M248_C_L M248_C_R M248_C_S
## "h" "f" "cdg" "def" "cg" "ag" "bh"
## M248_S_L M248_S_R M248_S_S LA1511_C_L
## "ef" "cdg" "cdef" "cdg"
test <- as.data.frame(stat.test$Letters)
test$group1 <- rownames(test)
test$group2 <- rownames(test)
colnames(test)[1] <- "Tukey"
test
K_content <- ggplot(data = ICP, mapping = aes(x = All.ID, y = K.con..mg.mg.dry.weight, colour = Condition))
K_content <- K_content + geom_boxplot(alpha=0.2) + geom_jitter(width=0.1,alpha=0.2)
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","red"))
K_content <- K_content + ylab("K content, mg/mg dry weight") + xlab("")
K_content <- K_content + theme(axis.text.x = element_text(angle=90, hjust=0.9, vjust=0.5))
K_content <- K_content + stat_pvalue_manual(test, label = "Tukey", y.position = 80)
K_content
k_content <- ggplot(data = ICP, mapping = aes(x = Condition, y = K.con..mg.mg.dry.weight, colour = Condition))
k_content <- k_content + geom_boxplot(alpha=0.2) + geom_jitter(width=0.1,alpha=0.2)
k_content <- k_content + facet_grid(Tissue ~ Accession)
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","red"))
k_content <- k_content + ylab("K content, mg/mg dry weight") + xlab("")
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
k_content <- ggplot(data = ICP, mapping = aes(x = Tissue, y = K.con..mg.mg.dry.weight, colour = Condition))
k_content <- k_content + geom_boxplot(alpha=0.2) + geom_jitter(width=0.1,alpha=0.2)
k_content <- k_content + facet_grid(Condition ~ Accession)
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","red"))
k_content <- k_content + ylab("K content, mg/mg dry weight") + xlab("")
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
k_content <- ggplot(data = ICP, mapping = aes(x = Accession, y = K.con..mg.mg.dry.weight, colour = Condition))
k_content <- k_content + geom_boxplot(alpha=0.2) + geom_jitter(width=0.1,alpha=0.2)
k_content <- k_content + facet_grid(Condition ~ Tissue)
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","red"))
k_content <- k_content + ylab("K content, mg/mg dry weight") + xlab("")
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(DW.mg ~ All.ID, data = ICP)
## Call:
## aov(formula = DW.mg ~ All.ID, data = ICP)
##
## Terms:
## All.ID Residuals
## Sum of Squares 11031.735 6450.923
## Deg. of Freedom 17 240
##
## Residual standard error: 5.184481
## 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
## LA1511_C_R-LA1511_C_L -15.45384615 -22.62683293 -8.28085937 0.0000000
## LA1511_C_S-LA1511_C_L -12.65384615 -19.82683293 -5.48085937 0.0000003
## LA1511_S_L-LA1511_C_L -7.25384615 -14.42683293 -0.08085937 0.0441794
## LA1511_S_R-LA1511_C_L -18.86153846 -26.03452524 -11.68855168 0.0000000
## LA1511_S_S-LA1511_C_L -17.26923077 -24.44221755 -10.09624399 0.0000000
## M058_C_L-LA1511_C_L -8.86461538 -15.79437897 -1.93485180 0.0013534
## M058_C_R-LA1511_C_L -19.28461538 -26.21437897 -12.35485180 0.0000000
## M058_C_S-LA1511_C_L -17.32461538 -24.25437897 -10.39485180 0.0000000
## M058_S_L-LA1511_C_L -15.93128205 -22.86104564 -9.00151846 0.0000000
## M058_S_R-LA1511_C_L -20.71128205 -27.64104564 -13.78151846 0.0000000
## M058_S_S-LA1511_C_L -21.52461538 -28.45437897 -14.59485180 0.0000000
## M248_C_L-LA1511_C_L 0.29538462 -6.63437897 7.22514820 1.0000000
## M248_C_R-LA1511_C_L -14.65128205 -21.58104564 -7.72151846 0.0000000
## M248_C_S-LA1511_C_L -8.58461538 -15.51437897 -1.65485180 0.0024319
## M248_S_L-LA1511_C_L -11.07128205 -18.00104564 -4.14151846 0.0000073
## M248_S_R-LA1511_C_L -20.32461538 -27.25437897 -13.39485180 0.0000000
## M248_S_S-LA1511_C_L -20.29128205 -27.22104564 -13.36151846 0.0000000
## LA1511_C_S-LA1511_C_R 2.80000000 -4.37298678 9.97298678 0.9961152
## LA1511_S_L-LA1511_C_R 8.20000000 1.02701322 15.37298678 0.0089780
## LA1511_S_R-LA1511_C_R -3.40769231 -10.58067909 3.76529447 0.9693783
## LA1511_S_S-LA1511_C_R -1.81538462 -8.98837139 5.35760216 0.9999871
## M058_C_L-LA1511_C_R 6.58923077 -0.34053282 13.51899436 0.0836446
## M058_C_R-LA1511_C_R -3.83076923 -10.76053282 3.09899436 0.8891468
## M058_C_S-LA1511_C_R -1.87076923 -8.80053282 5.05899436 0.9999674
## M058_S_L-LA1511_C_R -0.47743590 -7.40719949 6.45232769 1.0000000
## M058_S_R-LA1511_C_R -5.25743590 -12.18719949 1.67232769 0.4029730
## M058_S_S-LA1511_C_R -6.07076923 -13.00053282 0.85899436 0.1684696
## M248_C_L-LA1511_C_R 15.74923077 8.81946718 22.67899436 0.0000000
## M248_C_R-LA1511_C_R 0.80256410 -6.12719949 7.73232769 1.0000000
## M248_C_S-LA1511_C_R 6.86923077 -0.06053282 13.79899436 0.0549534
## M248_S_L-LA1511_C_R 4.38256410 -2.54719949 11.31232769 0.7310576
## M248_S_R-LA1511_C_R -4.87076923 -11.80053282 2.05899436 0.5484674
## M248_S_S-LA1511_C_R -4.83743590 -11.76719949 2.09232769 0.5613578
## LA1511_S_L-LA1511_C_S 5.40000000 -1.77298678 12.57298678 0.4175966
## LA1511_S_R-LA1511_C_S -6.20769231 -13.38067909 0.96529447 0.1844604
## LA1511_S_S-LA1511_C_S -4.61538462 -11.78837139 2.55760216 0.7041356
## M058_C_L-LA1511_C_S 3.78923077 -3.14053282 10.71899436 0.8979426
## M058_C_R-LA1511_C_S -6.63076923 -13.56053282 0.29899436 0.0787315
## M058_C_S-LA1511_C_S -4.67076923 -11.60053282 2.25899436 0.6254844
## M058_S_L-LA1511_C_S -3.27743590 -10.20719949 3.65232769 0.9706478
## M058_S_R-LA1511_C_S -8.05743590 -14.98719949 -1.12767231 0.0069407
## M058_S_S-LA1511_C_S -8.87076923 -15.80053282 -1.94100564 0.0013358
## M248_C_L-LA1511_C_S 12.94923077 6.01946718 19.87899436 0.0000000
## M248_C_R-LA1511_C_S -1.99743590 -8.92719949 4.93232769 0.9999185
## M248_C_S-LA1511_C_S 4.06923077 -2.86053282 10.99899436 0.8298042
## M248_S_L-LA1511_C_S 1.58256410 -5.34719949 8.51232769 0.9999971
## M248_S_R-LA1511_C_S -7.67076923 -14.60053282 -0.74100564 0.0142687
## M248_S_S-LA1511_C_S -7.63743590 -14.56719949 -0.70767231 0.0151524
## LA1511_S_R-LA1511_S_L -11.60769231 -18.78067909 -4.43470553 0.0000050
## LA1511_S_S-LA1511_S_L -10.01538462 -17.18837139 -2.84239784 0.0002232
## M058_C_L-LA1511_S_L -1.61076923 -8.54053282 5.31899436 0.9999963
## M058_C_R-LA1511_S_L -12.03076923 -18.96053282 -5.10100564 0.0000006
## M058_C_S-LA1511_S_L -10.07076923 -17.00053282 -3.14100564 0.0000881
## M058_S_L-LA1511_S_L -8.67743590 -15.60719949 -1.74767231 0.0020068
## M058_S_R-LA1511_S_L -13.45743590 -20.38719949 -6.52767231 0.0000000
## M058_S_S-LA1511_S_L -14.27076923 -21.20053282 -7.34100564 0.0000000
## M248_C_L-LA1511_S_L 7.54923077 0.61946718 14.47899436 0.0177355
## M248_C_R-LA1511_S_L -7.39743590 -14.32719949 -0.46767231 0.0231244
## M248_C_S-LA1511_S_L -1.33076923 -8.26053282 5.59899436 0.9999998
## M248_S_L-LA1511_S_L -3.81743590 -10.74719949 3.11232769 0.8920205
## M248_S_R-LA1511_S_L -13.07076923 -20.00053282 -6.14100564 0.0000000
## M248_S_S-LA1511_S_L -13.03743590 -19.96719949 -6.10767231 0.0000000
## LA1511_S_S-LA1511_S_R 1.59230769 -5.58067909 8.76529447 0.9999981
## M058_C_L-LA1511_S_R 9.99692308 3.06715949 16.92668666 0.0001051
## M058_C_R-LA1511_S_R -0.42307692 -7.35284051 6.50668666 1.0000000
## M058_C_S-LA1511_S_R 1.53692308 -5.39284051 8.46668666 0.9999982
## M058_S_L-LA1511_S_R 2.93025641 -3.99950718 9.86002000 0.9905443
## M058_S_R-LA1511_S_R -1.84974359 -8.77950718 5.08002000 0.9999722
## M058_S_S-LA1511_S_R -2.66307692 -9.59284051 4.26668666 0.9967589
## M248_C_L-LA1511_S_R 19.15692308 12.22715949 26.08668666 0.0000000
## M248_C_R-LA1511_S_R 4.21025641 -2.71950718 11.14002000 0.7879850
## M248_C_S-LA1511_S_R 10.27692308 3.34715949 17.20668666 0.0000535
## M248_S_L-LA1511_S_R 7.79025641 0.86049282 14.72002000 0.0114726
## M248_S_R-LA1511_S_R -1.46307692 -8.39284051 5.46668666 0.9999991
## M248_S_S-LA1511_S_R -1.42974359 -8.35950718 5.50002000 0.9999994
## M058_C_L-LA1511_S_S 8.40461538 1.47485180 15.33437897 0.0035077
## M058_C_R-LA1511_S_S -2.01538462 -8.94514820 4.91437897 0.9999078
## M058_C_S-LA1511_S_S -0.05538462 -6.98514820 6.87437897 1.0000000
## M058_S_L-LA1511_S_S 1.33794872 -5.59181487 8.26771231 0.9999998
## M058_S_R-LA1511_S_S -3.44205128 -10.37181487 3.48771231 0.9539503
## M058_S_S-LA1511_S_S -4.25538462 -11.18514820 2.67437897 0.7736503
## M248_C_L-LA1511_S_S 17.56461538 10.63485180 24.49437897 0.0000000
## M248_C_R-LA1511_S_S 2.61794872 -4.31181487 9.54771231 0.9973478
## M248_C_S-LA1511_S_S 8.68461538 1.75485180 15.61437897 0.0019770
## M248_S_L-LA1511_S_S 6.19794872 -0.73181487 13.12771231 0.1432766
## M248_S_R-LA1511_S_S -3.05538462 -9.98514820 3.87437897 0.9853300
## M248_S_S-LA1511_S_S -3.02205128 -9.95181487 3.90771231 0.9869028
## M058_C_R-M058_C_L -10.42000000 -17.09768728 -3.74231272 0.0000141
## M058_C_S-M058_C_L -8.46000000 -15.13768728 -1.78231272 0.0016211
## M058_S_L-M058_C_L -7.06666667 -13.74435395 -0.38897939 0.0258064
## M058_S_R-M058_C_L -11.84666667 -18.52435395 -5.16897939 0.0000003
## M058_S_S-M058_C_L -12.66000000 -19.33768728 -5.98231272 0.0000000
## M248_C_L-M058_C_L 9.16000000 2.48231272 15.83768728 0.0003297
## M248_C_R-M058_C_L -5.78666667 -12.46435395 0.89102061 0.1826910
## M248_C_S-M058_C_L 0.28000000 -6.39768728 6.95768728 1.0000000
## M248_S_L-M058_C_L -2.20666667 -8.88435395 4.47102061 0.9994936
## M248_S_R-M058_C_L -11.46000000 -18.13768728 -4.78231272 0.0000008
## M248_S_S-M058_C_L -11.42666667 -18.10435395 -4.74897939 0.0000009
## M058_C_S-M058_C_R 1.96000000 -4.71768728 8.63768728 0.9998954
## M058_S_L-M058_C_R 3.35333333 -3.32435395 10.03102061 0.9492827
## M058_S_R-M058_C_R -1.42666667 -8.10435395 5.25102061 0.9999990
## M058_S_S-M058_C_R -2.24000000 -8.91768728 4.43768728 0.9993861
## M248_C_L-M058_C_R 19.58000000 12.90231272 26.25768728 0.0000000
## M248_C_R-M058_C_R 4.63333333 -2.04435395 11.31102061 0.5726472
## M248_C_S-M058_C_R 10.70000000 4.02231272 17.37768728 0.0000067
## M248_S_L-M058_C_R 8.21333333 1.53564605 14.89102061 0.0027572
## M248_S_R-M058_C_R -1.04000000 -7.71768728 5.63768728 1.0000000
## M248_S_S-M058_C_R -1.00666667 -7.68435395 5.67102061 1.0000000
## M058_S_L-M058_C_S 1.39333333 -5.28435395 8.07102061 0.9999993
## M058_S_R-M058_C_S -3.38666667 -10.06435395 3.29102061 0.9447283
## M058_S_S-M058_C_S -4.20000000 -10.87768728 2.47768728 0.7393317
## M248_C_L-M058_C_S 17.62000000 10.94231272 24.29768728 0.0000000
## M248_C_R-M058_C_S 2.67333333 -4.00435395 9.35102061 0.9948200
## M248_C_S-M058_C_S 8.74000000 2.06231272 15.41768728 0.0008700
## M248_S_L-M058_C_S 6.25333333 -0.42435395 12.93102061 0.0964919
## M248_S_R-M058_C_S -3.00000000 -9.67768728 3.67768728 0.9822443
## M248_S_S-M058_C_S -2.96666667 -9.64435395 3.71102061 0.9841451
## M058_S_R-M058_S_L -4.78000000 -11.45768728 1.89768728 0.5138799
## M058_S_S-M058_S_L -5.59333333 -12.27102061 1.08435395 0.2314169
## M248_C_L-M058_S_L 16.22666667 9.54897939 22.90435395 0.0000000
## M248_C_R-M058_S_L 1.28000000 -5.39768728 7.95768728 0.9999998
## M248_C_S-M058_S_L 7.34666667 0.66897939 14.02435395 0.0155226
## M248_S_L-M058_S_L 4.86000000 -1.81768728 11.53768728 0.4821483
## M248_S_R-M058_S_L -4.39333333 -11.07102061 2.28435395 0.6675043
## M248_S_S-M058_S_L -4.36000000 -11.03768728 2.31768728 0.6802805
## M058_S_S-M058_S_R -0.81333333 -7.49102061 5.86435395 1.0000000
## M248_C_L-M058_S_R 21.00666667 14.32897939 27.68435395 0.0000000
## M248_C_R-M058_S_R 6.06000000 -0.61768728 12.73768728 0.1271224
## M248_C_S-M058_S_R 12.12666667 5.44897939 18.80435395 0.0000001
## M248_S_L-M058_S_R 9.64000000 2.96231272 16.31768728 0.0001033
## M248_S_R-M058_S_R 0.38666667 -6.29102061 7.06435395 1.0000000
## M248_S_S-M058_S_R 0.42000000 -6.25768728 7.09768728 1.0000000
## M248_C_L-M058_S_S 21.82000000 15.14231272 28.49768728 0.0000000
## M248_C_R-M058_S_S 6.87333333 0.19564605 13.55102061 0.0360922
## M248_C_S-M058_S_S 12.94000000 6.26231272 19.61768728 0.0000000
## M248_S_L-M058_S_S 10.45333333 3.77564605 17.13102061 0.0000129
## M248_S_R-M058_S_S 1.20000000 -5.47768728 7.87768728 0.9999999
## M248_S_S-M058_S_S 1.23333333 -5.44435395 7.91102061 0.9999999
## M248_C_R-M248_C_L -14.94666667 -21.62435395 -8.26897939 0.0000000
## M248_C_S-M248_C_L -8.88000000 -15.55768728 -2.20231272 0.0006326
## M248_S_L-M248_C_L -11.36666667 -18.04435395 -4.68897939 0.0000011
## M248_S_R-M248_C_L -20.62000000 -27.29768728 -13.94231272 0.0000000
## M248_S_S-M248_C_L -20.58666667 -27.26435395 -13.90897939 0.0000000
## M248_C_S-M248_C_R 6.06666667 -0.61102061 12.74435395 0.1259522
## M248_S_L-M248_C_R 3.58000000 -3.09768728 10.25768728 0.9124877
## M248_S_R-M248_C_R -5.67333333 -12.35102061 1.00435395 0.2102843
## M248_S_S-M248_C_R -5.64000000 -12.31768728 1.03768728 0.2189228
## M248_S_L-M248_C_S -2.48666667 -9.16435395 4.19102061 0.9977645
## M248_S_R-M248_C_S -11.74000000 -18.41768728 -5.06231272 0.0000004
## M248_S_S-M248_C_S -11.70666667 -18.38435395 -5.02897939 0.0000004
## M248_S_R-M248_S_L -9.25333333 -15.93102061 -2.57564605 0.0002642
## M248_S_S-M248_S_L -9.22000000 -15.89768728 -2.54231272 0.0002860
## M248_S_S-M248_S_R 0.03333333 -6.64435395 6.71102061 1.0000000
P7 = Output$All.ID[,'p adj']
stat.test<- multcompLetters(P7)
stat.test
## LA1511_C_R LA1511_C_S LA1511_S_L LA1511_S_R LA1511_S_S M058_C_L M058_C_R
## "abcde" "abcf" "f" "ade" "abde" "cf" "ade"
## M058_C_S M058_S_L M058_S_R M058_S_S M248_C_L M248_C_R M248_C_S
## "abde" "abde" "de" "d" "g" "abce" "cf"
## M248_S_L M248_S_R M248_S_S LA1511_C_L
## "bcf" "de" "de" "g"
test <- as.data.frame(stat.test$Letters)
test$group1 <- rownames(test)
test$group2 <- rownames(test)
colnames(test)[1] <- "Tukey"
test
DW <- ggplot(data = ICP, mapping = aes(x = All.ID, y = DW.mg, colour = Condition))
DW <- DW + geom_boxplot(alpha=0.2) + geom_jitter(width=0.1,alpha=0.2)
DW <- DW + stat_summary(fun=mean, geom="point", shape=95, size=6, color="black", fill="black")
DW <- DW + scale_color_manual(values = c("blue","red"))
DW <- DW + ylab("Dry weight, mg") + xlab("")
DW <- DW + theme(axis.text.x = element_text(angle=90, hjust=0.9, vjust=0.5))
DW <- DW + stat_pvalue_manual(test, label = "Tukey", y.position = 80)
DW
DW <- ggplot(data = ICP, mapping = aes(x = Condition, y = DW.mg, colour = Condition))
DW <- DW + geom_boxplot(alpha=0.2) + geom_jitter(width=0.1,alpha=0.2)
DW <- DW + facet_grid(Tissue ~ Accession)
DW <- DW + stat_summary(fun=mean, geom="point", shape=95, size=6, color="black", fill="black")
DW <- DW + scale_color_manual(values = c("blue","red"))
DW <- DW + ylab("Dry weight, mg") + xlab("")
DW <- DW + theme(axis.text.x = element_text(angle=90, hjust=0.9, vjust=0.5))
DW <- DW + rremove("legend")
DW
DW <- ggplot(data = ICP, mapping = aes(x = Tissue, y = DW.mg, colour = Condition))
DW <- DW + geom_boxplot(alpha=0.2) + geom_jitter(width=0.1,alpha=0.2)
DW <- DW + facet_grid(Condition ~ Accession)
DW <- DW + stat_summary(fun=mean, geom="point", shape=95, size=6, color="black", fill="black")
DW <- DW + scale_color_manual(values = c("blue","red"))
DW <- DW + ylab("Dry weight, mg") + xlab("")
DW <- DW + theme(axis.text.x = element_text(angle=90, hjust=0.9, vjust=0.5))
DW <- DW + rremove("legend")
DW
DW <- ggplot(data = ICP, mapping = aes(x = Accession, y = DW.mg, colour = Condition))
DW <- DW + geom_boxplot(alpha=0.2) + geom_jitter(width=0.1,alpha=0.2)
DW <- DW + facet_grid(Condition ~ Tissue)
DW <- DW + stat_summary(fun=mean, geom="point", shape=95, size=6, color="black", fill="black")
DW <- DW + scale_color_manual(values = c("blue","red"))
DW <- DW + ylab("Dry weight, mg") + xlab("")
DW <- DW + theme(axis.text.x = element_text(angle=90, hjust=0.9, vjust=0.5))
DW <- DW + rremove("legend")
DW
FW<- read.csv("20220124_root_leaf_stem_separated_ICP_LA1511_M058_M248_freshWeight v2.csv")
FW
FW$All.ID <- paste(FW$ï..Genotype,FW$Condition, sep="_")
FW
for(i in 1:nrow(FW)){
FW$total.FW.g[i] <- sum(FW[i,3:5])
}
FW
FW$total.FW.mg <- FW$total.FW.g * 1000
FW
aov(total.FW.mg ~ All.ID, data = FW)
## Call:
## aov(formula = total.FW.mg ~ All.ID, data = FW)
##
## Terms:
## All.ID Residuals
## Sum of Squares 7602071 639878
## Deg. of Freedom 5 80
##
## Residual standard error: 89.43416
## Estimated effects may be unbalanced
## 2 observations deleted due to missingness
Output <- TukeyHSD(aov(total.FW.mg ~ All.ID, data = FW))
Output
## Tukey multiple comparisons of means
## 95% family-wise confidence level
##
## Fit: aov(formula = total.FW.mg ~ All.ID, data = FW)
##
## $All.ID
## diff lwr upr p adj
## LA1511_salt-LA1511_control -404.71538 -507.143679 -302.287090 0.0000000
## M058_control-LA1511_control -281.95487 -380.910006 -182.999738 0.0000000
## M058_salt-LA1511_control -605.36154 -704.316672 -506.406405 0.0000000
## M248_control-LA1511_control 241.93846 142.983328 340.893595 0.0000000
## M248_salt-LA1511_control -501.61487 -600.570006 -402.659738 0.0000000
## M058_control-LA1511_salt 122.76051 23.805379 221.715647 0.0065580
## M058_salt-LA1511_salt -200.64615 -299.601288 -101.691020 0.0000011
## M248_control-LA1511_salt 646.65385 547.698712 745.608980 0.0000000
## M248_salt-LA1511_salt -96.89949 -195.854621 2.055647 0.0584220
## M058_salt-M058_control -323.40667 -418.762220 -228.051114 0.0000000
## M248_control-M058_control 523.89333 428.537780 619.248886 0.0000000
## M248_salt-M058_control -219.66000 -315.015553 -124.304447 0.0000000
## M248_control-M058_salt 847.30000 751.944447 942.655553 0.0000000
## M248_salt-M058_salt 103.74667 8.391114 199.102220 0.0249242
## M248_salt-M248_control -743.55333 -838.908886 -648.197780 0.0000000
P8 = Output$All.ID[,'p adj']
stat.test<- multcompLetters(P8)
stat.test
## LA1511_salt M058_control M058_salt M248_control M248_salt
## "a" "b" "c" "d" "a"
## LA1511_control
## "e"
test <- as.data.frame(stat.test$Letters)
test$group1 <- rownames(test)
test$group2 <- rownames(test)
colnames(test)[1] <- "Tukey"
test
unique(FW$Condition)
## [1] "salt" "control" ""
FW <- na.omit(FW)
unique(FW$Condition)
## [1] "salt" "control"
FW_graph <- ggplot(data = FW, mapping = aes(x = All.ID, y = total.FW.mg, colour = Condition))
FW_graph <- FW_graph + geom_boxplot(alpha=0.2) + geom_jitter(width=0.1,alpha=0.2)
FW_graph <- FW_graph + stat_summary(fun=mean, geom="point", shape=95, size=6, color="black", fill="black")
FW_graph <- FW_graph + scale_color_manual(values = c("blue","red"))
FW_graph <- FW_graph + ylab("Total fresh weight, mg") + xlab("") #+ ggtitle("")
FW_graph <- FW_graph + theme(axis.text.x = element_text(angle=90, hjust=0.9, vjust=0.5))
FW_graph <- FW_graph + stat_pvalue_manual(test, label = "Tukey", y.position = 150)
FW_graph
FW_graph <- ggplot(data = FW, mapping = aes(x = Condition, y = total.FW.mg, colour = Condition))
FW_graph <- FW_graph + geom_boxplot(alpha=0.2) + geom_jitter(width=0.1,alpha=0.2)
FW_graph <- FW_graph + facet_grid(~ï..Genotype)
FW_graph <- FW_graph + stat_summary(fun=mean, geom="point", shape=95, size=6, color="black", fill="black")
FW_graph <- FW_graph + scale_color_manual(values = c("blue","red"))
FW_graph <- FW_graph + ylab("Fresh weight, mg") + xlab("")
FW_graph <- FW_graph + theme(axis.text.x = element_text(angle=90, hjust=0.9, vjust=0.5))
FW_graph <- FW_graph + rremove("legend")
FW_graph
FW_graph <- ggplot(data = FW, mapping = aes(x = ï..Genotype, y = total.FW.mg, colour = Condition))
FW_graph <- FW_graph + geom_boxplot(alpha=0.2) + geom_jitter(width=0.1,alpha=0.2)
FW_graph <- FW_graph + facet_grid(~Condition)
FW_graph <- FW_graph + stat_summary(fun=mean, geom="point", shape=95, size=6, color="black", fill="black")
FW_graph <- FW_graph + scale_color_manual(values = c("blue","red"))
FW_graph <- FW_graph + ylab("Fresh weight, mg") + xlab("")
FW_graph <- FW_graph + theme(axis.text.x = element_text(angle=90, hjust=0.9, vjust=0.5))
FW_graph <- FW_graph + rremove("legend")
FW_graph
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