Updated figures to R1 - added XW and SbM

03_Figures_Simulations.R

@@ -82,11 +82,10 @@ ggplot(data=outp.summary %>%
          dplyr::filter(stat.type=="XY") %>% 
          dplyr::filter(trait %in% c("1", "2", "1 2", "3", "1 3", "2 3")) %>% 
          mutate(trait=factor(trait, levels=c("1", "2", "3", "1 2", "1 3", "2 3"), 
-                             labels=c("t1", "t2", "tn", "t1 t2", "t1 tn", "t2 tn")))) + #%>%
-         #dplyr::filter(trait %in% c("1", "2", "1 2", "3")) %>%
-         #mutate(inter=as.factor(inter))) + 
-  geom_line(aes(x=main, y=power, group=trait, col=trait)) + 
-  #scale_colour_brewer(palette = "Dark2") + 
+                             labels=c("t1", "t2", "tn", "t1 t2", "t1 tn", "t2 tn"))) %>% 
+         mutate(linetype=as.factor(ifelse(grepl(pattern="tn", x = trait), 2, 1)))) + 
+  geom_line(aes(x=main, y=power, group=trait, col=trait, lty=linetype)) + 
+  guides(linetype = FALSE) + 
   scale_color_manual("Trait\ncomb.",
   values=c("#e41a1c",  #1 - red)
           "#e6ab02", #2 - yellow
@@ -102,7 +101,7 @@ ggplot(data=outp.summary %>%
   scale_y_continuous(name="Prop. of significant tests") + 
   theme(panel.grid = element_blank())
 
-ggsave(filename="_pics/Fig2_CorrInte_02March.png", width=6, height=5, device="png", dpi = 300, last_plot())
+ggsave(filename="_pics/R1/Fig2_CorrInte_02March.png", width=6, height=5, device="png", dpi = 300, last_plot())
 
 
 
@@ -137,7 +136,8 @@ outp.summary2 <- outp.summary %>%
 ### rename null trait to "tn"
 outp.summary2 <- outp.summary2 %>% 
   mutate(tn.name=paste0("t", ntraits)) %>% 
-  mutate(trait=str_replace(trait, pattern=tn.name, replacement="tn"))
+  mutate(trait=str_replace(trait, pattern=tn.name, replacement="tn")) %>% 
+  mutate(linetype=as.factor(ifelse(grepl(pattern="tn", x = trait), 2, 1)))
 
 #reorder factors
 outp.summary2$trait <- factor(outp.summary2$trait, levels= c('t1', 't2','t3', 't4', 'tn',
@@ -167,7 +167,8 @@ outp.summary2 <- outp.summary2 %>%
   left_join(hugepalette, by="trait")
 
 fig3 <- ggplot(data=outp.summary2) + 
-  geom_line(aes(x=main, y=power, group=trait, col=trait.col)) + 
+  geom_line(aes(x=main, y=power, group=trait, col=trait.col, lty=linetype)) + 
+  guides(linetype = FALSE) + 
   scale_x_continuous(name="Effect of factor e1 -> trait t1", n.breaks = 4) + 
   scale_y_continuous(name="Prop. of significant tests") + 
   facet_grid(sel.ntraits.lab~ntraits.lab) +
@@ -202,7 +203,7 @@ fig3.panel <- cowplot::plot_grid(fig3 + theme(legend.position = "none"),
                    nrow=1, rel_widths = c(0.6,.4))
 
 
-ggsave(filename="_pics/Fig3_TraitNumber.png", 
+ggsave(filename="_pics/R1/Fig3_TraitNumber.png", 
        width=9, height=7, device="png", dpi = 300, fig3.panel)
 
 
@@ -221,10 +222,10 @@ ggplot(data=outp.summary %>%
          dplyr::filter(stat.type=="XY") %>% 
          dplyr::filter(trait %in% c("1", "2", "3", "4")) %>% 
          mutate(trait=factor(trait, levels=c("1", "2", "3", "4"), 
-                             labels=c("t1", "t2", "t3","tn")))) + #%>%
-  #dplyr::filter(trait %in% c("1", "2", "1 2", "3")) %>%
-  #mutate(inter=as.factor(inter))) + 
-  geom_line(aes(x=main, y=power, group=trait, col=trait)) + 
+                             labels=c("t1", "t2", "t3","tn"))) %>% 
+  mutate(linetype=as.factor(ifelse(grepl(pattern="tn", x = trait), 2, 1)))) + 
+  geom_line(aes(x=main, y=power, group=trait, col=trait, lty=linetype)) + 
+  guides(linetype = FALSE) + 
   #scale_colour_brewer(palette = "Dark2") + 
   #scale_color_manual("Trait\ncomb.",
   scale_color_manual("Trait",
@@ -242,12 +243,14 @@ ggplot(data=outp.summary %>%
   scale_y_continuous(name="Prop. of significant tests") + 
   theme(panel.grid = element_blank())
 
-ggsave(filename="_pics/FigS4_Extra_CorrInte_08Jul20.png", width=6, height=5, device="png", dpi = 300, last_plot())
+ggsave(filename="_pics/R1/FigS4_Extra_CorrInte_08Jul20.png", width=6, height=5, device="png", dpi = 300, last_plot())
+
 
 
+### Additional Figures for JVS R1 ####
 
 
-### FIGURE SXXX ####
+#### FIGURE SXXX - XW ####
 mypath <- "_data/Experiment_30Oct2020_FactorInteraction&TraitCorr_XW"
 myfiles <- list.files(path=mypath, pattern = "Summary.txt", recursive = T)
 outp.summary <- FormatData(myfiles) 
@@ -267,8 +270,10 @@ ggplot(data=outp.summary %>%
          dplyr::filter(stat.type=="XY") %>% 
          dplyr::filter(trait %in% c("1", "2", "1 2", "3", "1 3", "2 3")) %>% 
          mutate(trait=factor(trait, levels=c("1", "2", "3", "1 2", "1 3", "2 3"), 
-                             labels=c("t1", "t2", "tn", "t1 t2", "t1 tn", "t2 tn")))) + 
-  geom_line(aes(x=main, y=power, group=trait, col=trait)) + 
+                             labels=c("t1", "t2", "tn", "t1 t2", "t1 tn", "t2 tn"))) %>% 
+         mutate(linetype=as.factor(ifelse(grepl(pattern="tn", x = trait), 2, 1)))) + 
+  geom_line(aes(x=main, y=power, group=trait, col=trait, lty=linetype)) + 
+  guides(linetype = FALSE) + 
   scale_color_manual("Trait\ncomb.",
                      values=c("#e41a1c",  #1 - red)
                               "#e6ab02", #2 - yellow
@@ -283,9 +288,51 @@ ggplot(data=outp.summary %>%
   scale_y_continuous(name="Prop. of significant tests") + 
   theme(panel.grid = element_blank())
 
-ggsave(filename="_pics/FigSXXX_CorrInte_30November_XW.png", width=6, height=5, device="png", dpi = 300, last_plot())
+ggsave(filename="_pics/R1/FigSXXX_CorrInte_30November_XW.png", width=6, height=5, device="png", dpi = 300, last_plot())
+
+
+
+
+### FIGURE SXXY - SBM ####
+mypath <- "_data/Experiment_30Oct2020_FactorInteraction&TraitCorr_XW"
+myfiles <- list.files(path=mypath, pattern = "Summary.txt", recursive = T)
+outp.summary <- FormatData(myfiles) 
+
+mypalette <- palette(c("#e41a1c",  #1 - red)
+                       "#ff7f00", #12 - orange
+                       "#984ea3", #13 - violet
+                       "##ffed6f", #2 - yellow
+                       "#4daf4a", #23 - green
+                       "#377eb8")) #3 - blue
 
+ggplot(data=outp.summary %>% 
+         mutate(main=main/100) %>% 
+         mutate(corr=factor(corr/10, levels=c(0, 0.4, 0.8), labels=paste0("Correlation = ", c(0, 0.4, 0.8)))) %>% 
+         mutate(inter=factor(inter/10, levels=c(0, 0.3, 0.5), labels=paste0("Interaction = ", c(0, 0.3, 0.5)))) %>% 
+         ungroup() %>% 
+         dplyr::filter(stat.type=="SbM") %>% 
+         dplyr::filter(envir==1) %>% 
+         dplyr::filter(trait %in% c("1", "2", "1 2", "3", "1 3", "2 3")) %>% 
+         mutate(trait=factor(trait, levels=c("1", "2", "3", "1 2", "1 3", "2 3"), 
+                             labels=c("t1", "t2", "tn", "t1 t2", "t1 tn", "t2 tn"))) %>% 
+         mutate(linetype=as.factor(ifelse(grepl(pattern="tn", x = trait), 2, 1)))) + 
+  geom_line(aes(x=main, y=power, group=trait, col=trait, lty=linetype)) + 
+  guides(linetype = FALSE) + 
+  scale_color_manual("Trait\ncomb.",
+                     values=c("#e41a1c",  #1 - red)
+                              "#e6ab02", #2 - yellow
+                              "#377eb8", #3 - blue
+                              "#d95f02", #12 - orange
+                              "#984ea3", #13 - violet
+                              "#4daf4a" #23 - green
+                     )) +
+  facet_grid(corr~inter) + 
+  theme_bw() + 
+  scale_x_continuous(name="Effect of factor e1 -> trait t1") + 
+  scale_y_continuous(name="Prop. of significant tests") + 
+  theme(panel.grid = element_blank())
 
+ggsave(filename="_pics/R1/FigSXXX_CorrInte_30November_SbM.png", width=6, height=5, device="png", dpi = 300, last_plot())