Argthtjtr

I have my data below and I would like to plot a multiple box plot with the ANOVA test result shown on the plot.

> combined

   SampleID     chao1 Samples Sgroup Bgroup Duration

1     BSS21 1275.1071   BSS20    BSS      S      20d

2     BSS22 1575.4972   BSS20    BSS      S      20d

3     BSS23 1381.2963   BSS20    BSS      S      20d

4     BSS41 1090.0254   BSS40    BSS      S      40d

5     BSS42 1103.6522   BSS40    BSS      S      40d

6     BSS43 1065.7177   BSS40    BSS      S      40d

7     BSS61 1077.8776   BSS60    BSS      S      60d

8     BSS62 1123.5759   BSS60    BSS      S      60d

9     BSS63 1201.3571   BSS60    BSS      S      60d

10    BSW21  937.0231   BSW20    BSW      W      20d

11    BSW22  970.0462   BSW20    BSW      W      20d

12    BSW23 1070.1560   BSW20    BSW      W      20d

13    BSW41 1894.8606   BSW40    BSW      W      40d

14    BSW42 1825.0271   BSW40    BSW      W      40d

15    BSW43 1869.3494   BSW40    BSW      W      40d

16    BSW61 1332.4078   BSW60    BSW      W      60d

17    BSW62 1354.4593   BSW60    BSW      W      60d

18    BSW63 1365.2961   BSW60    BSW      W      60d

19     BW21 1533.9137    BW20     BW      W      20d

20     BW22 1643.1564    BW20     BW      W      20d

21     BW23 1572.8900    BW20     BW      W      20d

22     BW41 1678.0270    BW40     BW      W      40d

23     BW42 1596.9105    BW40     BW      W      40d

24     BW43 1684.8433    BW40     BW      W      40d

25     BW61 1060.2059    BW60     BW      W      60d

26     BW62 1127.0738    BW60     BW      W      60d

27     BW63 1097.7083    BW60     BW      W      60d

28     SS21 1751.0145    SS20     SS      S      20d

29     SS22 1662.5932    SS20     SS      S      20d

30     SS23 1806.3628    SS20     SS      S      20d

31     SS41 1302.9245    SS40     SS      S      40d

32     SS42 1126.5082    SS40     SS      S      40d

33     SS43 1122.6136    SS40     SS      S      40d

34     SS61 1429.4972    SS60     SS      S      60d

35     SS62 1402.5714    SS60     SS      S      60d

36     SS63 1493.1477    SS60     SS      S      60d

37     SW21 1559.5000    SW20     SW      W      20d

38     SW22 1387.1173    SW20     SW      W      20d

39     SW23 1563.9524    SW20     SW      W      20d

40     SW41 1439.0355    SW40     SW      W      40d

41     SW42 1508.0054    SW40     SW      W      40d

42     SW43 1425.1602    SW40     SW      W      40d

43     SW61 1488.0000    SW60     SW      W      60d

44     SW62 1398.9880    SW60     SW      W      60d

45     SW63 1497.8553    SW60     SW      W      60d

46     W011 1377.8092    W010    WCW      W      10d

47     W012 1304.3725    W010    WCW      W      10d

48     W013 1413.2292    W010    WCW      W      10d

49     W021 1377.8092    W010     BW      W      10d

50     W022 1304.3725    W010     BW      W      10d

51     W023 1413.2292    W010     BW      W      10d

52     W031 1377.8092    W010     SW      W      10d

53     W032 1304.3725    W010     SW      W      10d

54     W033 1413.2292    W010     SW      W      10d

55     W041 1377.8092    W010    BSW      W      10d

56     W042 1304.3725    W010    BSW      W      10d

57     W043 1413.2292    W010    BSW      W      10d

58     W051 1377.8092    W010     SS      W      10d

59     W052 1304.3725    W010     SS      W      10d

60     W053 1413.2292    W010     SS      W      10d

61     W061 1377.8092    W010    BSS      W      10d

62     W062 1304.3725    W010    BSS      W      10d

63     W063 1413.2292    W010    BSS      W      10d

64    WCW21 1246.5794   WCW20    WCW      W      20d

65    WCW22 1249.2180   WCW20    WCW      W      20d

66    WCW23 1134.3462   WCW20    WCW      W      20d

67    WCW41 1074.9192   WCW40    WCW      W      40d

68    WCW42  887.7191   WCW40    WCW      W      40d

69    WCW43  990.3733   WCW40    WCW      W      40d

70    WCW61  864.2727   WCW60    WCW      W      60d

71    WCW62  934.5111   WCW60    WCW      W      60d

72    WCW63  801.5696   WCW60    WCW      W      60d

I tried the ggpubr package in r and apply the compare_means function.
For the anova test, I got:

> compare_means(chao1~Duration,data=combined,method="anova",group.by = "Sgroup")



# A tibble: 6 x 7

  Sgroup .y.             p      p.adj p.format p.signif method

  <fct>  <chr>       <dbl>      <dbl> <chr>    <chr>    <chr> 

1 BSS    chao1 0.00394     0.0079     0.00394  **       Anova 

2 BSW    chao1 0.000000164 0.00000098 1.6e-07  ****     Anova 

3 BW     chao1 0.00000283  0.000014   2.8e-06  ****     Anova 

4 SS     chao1 0.0000996   0.0004     1.0e-04  ****     Anova 

5 SW     chao1 0.160       0.16       0.16005  ns       Anova 

6 WCW    chao1 0.000118    0.0004     0.00012  ***      Anova 

Which is exactly what I wanted. Then I make the plot:

ggboxplot(combined,x="Samples", y="chao1",palette = "jco", add = "jitter",short.panel.labs = FALSE)+facet_wrap(~Sgroup,scales = "free")

and got:

I have tried so hard by the stat_compare_means function but I still cannot add my anova test result on the plot

Any suggestion will be helped!

I've had problems with facet_wrap in the past, it maybe that its not supported. Hopefully I'm proven wrong! If you want an alternative, you can use the cowplot package to build the grids yourself. It's more work, but allows more flexibility perhaps. Here is an example with the data used when you run ?stat_compare_means

# packages

library(cowplot)

library(ggpubr)



# data from ggpubr

data("ToothGrowth")

head(ToothGrowth)



# define groups, build plots in a list and subset

groups <- unique(ToothGrowth$supp)



pl <- lapply(groups, function(g){

  p <- ggboxplot(ToothGrowth[ToothGrowth$supp==g,], x = "dose", y = "len",

                 color = "dose", palette = "npg") + 

    stat_compare_means()

})



# use cowplot to bring together

cowplot::plot_grid(plotlist = pl, ncol = 2)