How to get the significance level in plot R

Question

I want to add the signifiacnce level for each points of my plot and then, separate the different level of significance by color I have this data :

tframe	trimSlope	trimSD
5	1.2138196	0.05958077
10	1.2118020	0.05748510
20	1.1903467	0.05208732
...	...	...

to reproduce the data frame easily :

structure(list(tframe = c(5, 10, 15, 20, 30, 40, 50, 60, 90, 
120, 180, 240, 300, 480, 900, 1800, 3600, 28800), species = c("Barbar", 
"Barbar", "Barbar", "Barbar", "Barbar", "Barbar", "Barbar", "Barbar", 
"Barbar", "Barbar", "Barbar", "Barbar", "Barbar", "Barbar", "Barbar", 
"Barbar", "Barbar", "Barbar"), ineqMean = c(0.53104647399313, 
0.529297808367612, 0.525839141416682, 0.523942046846265, 0.52015928420821, 
0.518572691198356, 0.51511657232463, 0.516568872398126, 0.511999139793283, 
0.511939221736915, 0.508740279266857, 0.505224606372793, 0.501518089116363, 
0.499808187352849, 0.491227360987496, 0.4848439609884, 0.469461408463629, 
0.414520902218365), ineqSD = c(0.240454548676913, 0.242024196245511, 
0.243296542621781, 0.244848758571896, 0.246346408286188, 0.246855066968381, 
0.24874025357451, 0.248373465513351, 0.249666296730884, 0.249737396611995, 
0.250617197261608, 0.252642650344299, 0.254532366888185, 0.255779214784082, 
0.258922307090312, 0.261528662624724, 0.271358143507595, 0.31225287692273
), trimSlope = c(1.21381956965976, 1.21180197611039, 1.20025777497667, 
1.19034669771223, 1.18015387908413, 1.16704208709911, 1.15485377092914, 
1.15004735545657, 1.13037958715777, 1.1207384447301, 1.11122218773119, 
1.10897233423084, 1.09343555562548, 1.07597987336347, 1.0552313502822, 
1.02714867784966, 1.01874318671967, 0.997267460326558), trimSD = c(0.0595807674313792, 
0.0574850962929153, 0.0553699352357688, 0.0520873210646193, 0.0511378415143001, 
0.0480448502673866, 0.0466519422226488, 0.0454344459587024, 0.0422792122257447, 
0.0406831265017169, 0.038142436210773, 0.0379194407048026, 0.036217855188957, 
0.0327675134394643, 0.0300492301761473, 0.0279263379108475, 0.0297584207536629, 
0.0321719581188545), trimTrend = c("Strong increase (p<0.05)", 
"Strong increase (p<0.05)", "Strong increase (p<0.05)", "Strong increase (p<0.05)", 
"Strong increase (p<0.05)", "Moderate increase (p<0.05)", "Moderate increase (p<0.05)", 
"Moderate increase (p<0.05)", "Moderate increase (p<0.05)", "Moderate increase (p<0.05)", 
"Moderate increase (p<0.05)", "Moderate increase (p<0.05)", "Moderate increase (p<0.05)", 
"Uncertain", "Uncertain", "Uncertain", "Uncertain", "Uncertain"
), col = c("#006400", "#006400", "#006400", "#006400", "#006400", 
"#00CD00", "#00CD00", "#00CD00", "#00CD00", "#00CD00", "#00CD00", 
"#00CD00", "#00CD00", "#BEBEBE", "#BEBEBE", "#BEBEBE", "#BEBEBE", 
"#BEBEBE")), row.names = c(NA, -18L), class = c("tbl_df", "tbl", 
"data.frame"))

And I want a result like this :

I alreday try to use the geom_signif function but that doesn't work and I have theis error meassage :

Error in geom_signif(): ! Problem while computing stat. ℹ Error occurred in the 4th layer. Caused by error in setup_params(): ! Can only handle data with groups that are plotted on the x-axis my code is : using ggplot2 and ggsignif packages

p <-
ggplot(df, aes(x = tframe, y = trimSlope)) + 

geom_smooth(aes(x = tframe, y = trimSlope),
  method = "loess", col = "black"
) +
geom_errorbar(aes(ymin = trimSlope - trimSD, ymax = trimSlope + trimSD),
  width = .2
) +
geom_point(aes(x = tframe, y = trimSlope)) +
# add significance
geom_signif(comparisons = list(c(5, 10)), 
            map_signif_level=TRUE) +

# rtrim horizontal line at 1
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
# set x scale as log
scale_x_log10() +
labs(
  x = "time frame in seconds (log scale)",
  y = "mean indice values (trim slope) ± SE"
) +
# background and facetting
theme(panel.background = element_rect(
  fill = "antiquewhite1",
  colour = "blue"
)) 

I precise that my x axis is in log scale. So what I can do ?

Answer 1

I think this is what you want, using the siginificance levels already in your data. If you want to calculate which groups of points are different from each other that's another question.

(I'm not sure about the wisdom of classifying the points in this way, but that's up to you and not a question for this site.)

If you already have the groups calculated (as in your dataset) then you don't need to use geom_signif, you can just add labels with geom_text.

I used col=col in the main aesthetic mapping to map the colours for everything, then used scale_col_identity to make sure that the specific colours were actually used rather than the default colour scale.

To create the labels I made a named vector with values "A", "B", "C", etc, and named it according to the unique levels of your significance variable. Then in the aesthetic mapping for the geom_text I could use this vector to convert the categories into letters.

signifLabels <- LETTERS
names(signifLabels) <- unique(df$trimTrend)

ggplot(df, aes(x = tframe, y = trimSlope,col=col)) + 
  
  geom_smooth(aes(x = tframe, y = trimSlope),
              method = "loess", col = "black"
  ) +
  scale_color_identity()+
  geom_errorbar(aes(ymin = trimSlope - trimSD, ymax = trimSlope + trimSD),
                width = .2
  ) +
  geom_point(aes(x = tframe, y = trimSlope)) +
  # add significance 
  geom_text(aes(label=signifLabels[trimTrend], y=trimSlope + trimSD), vjust=-1)+
  # rtrim horizontal line at 1
  geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
  # set x scale as log
  scale_x_log10() +
  labs(
    x = "time frame in seconds (log scale)",
    y = "mean indice values (trim slope) ± SE"
  ) +
  # background and facetting
  theme(panel.background = element_rect(
    fill = "antiquewhite1",
    colour = "blue"
  ))