Final draft stage for initial submission

code/3D_landscapes.Rmd

@@ -1,7 +1,7 @@
 ---
 title: "3D Landscapes"
 author: "Antonia Netzl"
-date: "2024-03-11"
+date: "2024-07-31"
 output: html_document
 ---
 
@@ -20,7 +20,7 @@ library(htmlwidgets)
 set.seed(100)
 # set optimization nr to fit BA.4/5 position; optimization nr 56 gives upper BA.4/5
 
-map <- read.acmap(file.path("data", "maps", "map_threshold20_all_ags_singleTP_woXBBBQ11conv_alphaJN1ba286_adjScan.ace"))
+map <- read.acmap(file.path("data", "maps", "map_threshold20_all_ags_singleTP_woXBBBQ11conv_woXBB15conv_woJN1BA286_alpha_adj.ace"))
 lims <- Racmacs:::mapPlotLims(map, sera = FALSE)
 
 lndscp_list <- readRDS(file.path("data", "landscape_fit", "biv_boosts_ags_all.rds"))

code/ablandscape_fit_multi.R

@@ -16,7 +16,6 @@ library(patchwork)
 set.seed(100)
 
 fit_ags <- "all" # options are "all", "sub"
-sub_ags <- c('CB.1', 'BR.3', 'CH.1.1','BA.5.2.1', 'BE.1.1', 'BF.7', 'BQ.1.3', 'BQ.1.1', 'BQ.1.18', 'XBB.1', 'XBB.1.5', 'XBF')
 
 source("./functions/map_longinfo.R")
 source("./functions/sams_landscape_functions.R")
@@ -27,7 +26,7 @@ suppressWarnings(dir.create(figure_dir, recursive = T))
 # if you want to exclude some antigens in the fit
 ags_to_exclude <- c("")
 # Read the base map
-map <- read.acmap("./data/maps/map_threshold20_all_ags_singleTP_woXBBBQ11conv_alphaJN1ba286_adjScan.ace")
+map <- read.acmap("./data/maps/map_threshold20_all_ags_singleTP_woXBBBQ11conv_woXBB15conv_woJN1BA286_alpha_adj.ace")
 
 sr_group_gmt <- read.csv("./data/titer_data/sr_group_gmt_threshold20.csv") %>%
   select(!X)
@@ -103,7 +102,7 @@ titerdata %>%
 # angle for html page
 # angle for html page
 angle <- list(
-  rotation = c(-1.3594,0.0060, -0.0626), #c(-1.3365, 0.0055, -0.0576),# c(-1.4592, 0.0045, -0.0144)
+  rotation = c(-1.3973,0.0060, -0.4106), #c(-1.3365, 0.0055, -0.0576),# c(-1.4592, 0.0045, -0.0144)
   translation = c(0, 0,0), #translation = c(0.0344, 0.0459, 0.1175),
   zoom = 1.5
   # zoom = 1.1646 # higher is more zoomed out
@@ -115,8 +114,8 @@ data3js <- base_plot_data3js(map, lndscp_fits, agNames(map), lims, agNames(map))
 two_dose_groups <- grep("two doses", titertables_groups$sr_group)
 
 two_dose_landscapes <- plot_landscapes_from_list(data3js, titertables_groups[two_dose_groups, ], lndscp_fits[two_dose_groups], map, gmt_data, highlighted_ags = agNames(map),
-                                                 ag_plot_names =  c("Wuhan", "BA.1", "JN.1", "HK.3"),
-                                                 ag_labelled = c("Wuhan", "BA.1", "JN.1", "HK.3"),
+                                                 ag_plot_names =  c("Delta", "BA.1", "DV.7.1",  "HK.3", "KZ.1.1.1"),
+                                                 ag_labelled = c("Delta", "BA.1","DV.7.1", "HK.3", "KZ.1.1.1"),
                                                 lndscp_colors = sr_colors,
                                                  add_ag_label = TRUE)
 
@@ -171,6 +170,4 @@ save_name <- file.path(figure_dir, paste0(fit_ags, "_all_gmt_landscapes"))
 plot_single_landscape_panel(lndscp, label = "", save_name = save_name, delete_html = FALSE)
 
 lndscp_list[["all"]] <- lndscp
-saveRDS(lndscp_list, paste0("data/landscape_fit/biv_boosts_ags_",fit_ags,".rds"))
-
-
+saveRDS(lndscp_list, paste0("data/landscape_fit/biv_boosts_ags_",fit_ags,".rds"))

code/make_map_final.R

@@ -93,28 +93,38 @@ for(map_f in map_files){
 
 }
 
-# optimise reactivity for Alpha. reduce alpha by 2 fold
+# remove all XBB.1.5 conv sera
 map_files <- list.files(map_dir, pattern = ".ace", full.names = TRUE)
 map_files <- map_files[grepl("woXBBBQ11conv.ace", map_files)]
-
-
 for(map_f in map_files){
 
   map <- read.acmap(map_f)
-  ag_names <- agNames(map)
+  map <- removeSera(map, srNames(map)[srGroups(map) == "XBB.1.5 conv."])
+  map <- optimize_and_realign_map(map, alignment_map, 1000, 2, option_list = list(ignore_disconnected = TRUE,
+                                                                             dim_annealing = TRUE))
 
-  start_react <- rep(0, length(ag_names))
-  start_react[ag_names == "Alpha"] <- -1
+  save.acmap(map, gsub(".ace", "_woXBB15conv.ace", map_f))
 
-  agReactivityAdjustments(map) <- start_react
-  map <- optimizeMap(map, 2, 1000, options = list(ignore_disconnected = TRUE,
-                                                  dim_annealing = TRUE))
-  map <- realignMap(map, alignment_map)
+}
+
+# remove JN.1 and BA.2.86
+map_files <- list.files(map_dir, pattern = ".ace", full.names = TRUE)
+map_files <- map_files[grepl("woXBBBQ11conv", map_files)]
+for(map_f in map_files){
 
-  save.acmap(map, gsub(".ace", "_alpha_adjM1.ace", map_f))
+  map <- read.acmap(map_f)
+  map <- removeAntigens(map, c("JN.1", "BA.2.86"))
+  map <- optimize_and_realign_map(map, alignment_map, 1000, 2, option_list = list(ignore_disconnected = TRUE,
+                                                                             dim_annealing = TRUE))
+
+  save.acmap(map, gsub(".ace", "_woJN1BA286.ace", map_f))
 
 }
 
+# optimise reactivity for Alpha. reduce alpha by 2 fold
+map_files <- list.files(map_dir, pattern = ".ace", full.names = TRUE)
+map_files <- map_files[grepl("woXBBBQ11conv", map_files)]
+
 # down here automated alpha adjust
 for(map_f in map_files){
 
@@ -125,7 +135,7 @@ for(map_f in map_files){
   start_react[ag_names == "Alpha"] <- NA
 
   map <- optimizeAgReactivity(map, fixed_ag_reactivities = start_react, reoptimize = FALSE, options = list(ignore_disconnected = TRUE, dim_annealing = TRUE))
-  print(paste(map_f, agReactivityAdjustments(map)))
+  #print(paste(map_f, agReactivityAdjustments(map)))
   map <- optimize_and_realign_map(map, alignment_map, 1000, 2, option_list = list(ignore_disconnected = TRUE,
                                                                                   dim_annealing = TRUE))
 
@@ -134,16 +144,3 @@ for(map_f in map_files){
 
 }
 
-if(!file.exists("data/maps/map_threshold20_all_ags_singleTP_woXBBBQ11conv_alphaJN1ba286_adjScan.ace")){
-
-  og_map <- read.acmap("data/maps/map_threshold20_all_ags_singleTP_woXBBBQ11conv_alpha_adj.ace")
-
-  ag_names <- agNames(og_map)
-  start_react <- agReactivityAdjustments(og_map)
-
-  start_react[ag_names %in% c("JN.1", "BA.2.86")] <- -0.685
-  adj_map_optim <- optimizeAgReactivity(og_map, fixed_ag_reactivities = start_react, reoptimize = TRUE, options = list(ignore_disconnected = TRUE, dim_annealing = TRUE))
-
-  save.acmap(adj_map_optim, "data/maps/map_threshold20_all_ags_singleTP_woXBBBQ11conv_alphaJN1ba286_adjScan.ace")
-
-}

figures/labelled_map/human_map_procrustes.R

@@ -44,7 +44,7 @@ sr_group_colors <- read.csv(file = "./data/metadata/sr_group_colors.csv", header
 mapColors <- read.csv(file = './data/metadata/map-colors.csv', row.names = 'Variable', header = TRUE)
 mapColors[rownames(sr_group_colors), "Color"] <- sr_group_colors$Color 
 
-target_map <- "map_threshold20_all_ags_singleTP_woXBBBQ11conv_alphaJN1ba286_adjScan.ace"
+target_map <- "map_threshold20_all_ags_singleTP_woXBBBQ11conv_woXBB15conv_woJN1BA286_alpha_adj.ace"
 full_map <-read.acmap(file.path("./data/maps", target_map))
 full_map <- change_map_colors(full_map, mapColors)
 
@@ -127,10 +127,10 @@ if(file.exists("data/maps/Wilks_et_al_subNHP.ace")){
 }
 
 xlim_no_zoom <- read.csv("./data/metadata/xlim_no_zoom.csv")$x
-xlim_no_zoom[1] <- xlim_no_zoom[1] + 2 
+#xlim_no_zoom[1] <- xlim_no_zoom[1] + 2 
 ylim_no_zoom <- read.csv("./data/metadata/ylim_no_zoom.csv")$x
-ylim_no_zoom[1] <- ylim_no_zoom[1] + 1
-ylim_no_zoom[2] <- ylim_no_zoom[2] - 1
+#ylim_no_zoom[1] <- ylim_no_zoom[1] + 1
+#ylim_no_zoom[2] <- ylim_no_zoom[2] - 1
 
 # Setup plotting function
 doplot <- function(map, xlims, ylims, show_labels = TRUE) {
@@ -189,58 +189,18 @@ doplot <- function(map, xlims, ylims, show_labels = TRUE) {
 
 
 
-#ylim_no_zoom[1] <- ylim_no_zoom[1] -1
-# 
-# 
-# png(file.path(figure_dir, "proc_map_threshold20_all_ags_singleTP_woXBBBQ11conv_alpha_adj_wSubset.png"), width = 8, height = 9, units = 'in', res=300, pointsize = 18)
-# layout(matrix(c(1:6), ncol = 2, byrow = T))
-# par(mar = rep(0.5, 4))
-# doplot(procrustesMap(alignment_map, full_map, scaling = TRUE), xlim_no_zoom, ylim_no_zoom, FALSE)
-# text(xlim_no_zoom[1]+0.4, ylim_no_zoom[2]-0.4, "A", cex = 1.2)
-# doplot(procrustesMap(move_coords(duke_map, at = 1, by = -3), full_map, scaling = TRUE), xlim_no_zoom-3, ylim_no_zoom, FALSE)
-# text(xlim_no_zoom[1]-3+0.4, ylim_no_zoom[2]-0.4, "B", cex = 1.2)
-# doplot(procrustesMap(sub_align, nhp_kimpel, scaling = TRUE), xlim_no_zoom, ylim_no_zoom, FALSE)
-# text(xlim_no_zoom[1]+0.4, ylim_no_zoom[2]-0.4, "C", cex = 1.2)
-# doplot(procrustesMap(sub_duke, nhp_duke, scaling = TRUE), xlim_no_zoom, ylim_no_zoom, FALSE)
-# text(xlim_no_zoom[1]+0.4, ylim_no_zoom[2]-0.4, "D", cex = 1.2)
-# doplot(procrustesMap(nhp_kimpel, full_map, scaling = FALSE, sera = FALSE), xlim_no_zoom, ylim_no_zoom, FALSE)
-# text(xlim_no_zoom[1]+0.4, ylim_no_zoom[2]-0.4, "E", cex = 1.2)
-# doplot(procrustesMap(nhp_duke, full_map, scaling = FALSE, sera = FALSE), xlim_no_zoom, ylim_no_zoom, FALSE)
-# text(xlim_no_zoom[1]+0.4, ylim_no_zoom[2]-0.4, "F", cex = 1.2)
-# dev.off()
-# 
-# png(file.path(figure_dir, "proc_map_threshold20_all_ags_singleTP_woXBBBQ11conv_alpha_adj.png"), width = 12, height = 5, units = 'in', res=300, pointsize = 18)
-# layout(matrix(c(1:2), ncol = 2, byrow = T))
-# par(mar = rep(0.5, 4))
-# doplot(procrustesMap(alignment_map, full_map, scaling = TRUE), xlim_no_zoom, ylim_no_zoom, FALSE)
-# text(xlim_no_zoom[1]+0.4, ylim_no_zoom[2]-0.4, "A", cex = 1.2)
-# text(xlim_no_zoom[2]-0.2, ylim_no_zoom[1]+ 0.2, "Human data set 1", cex = 0.8, adj = c(1, 0), col = "grey30")
-# doplot(procrustesMap(move_coords(duke_map, at = 1, by = -3), full_map, scaling = TRUE), xlim_no_zoom-3, ylim_no_zoom, FALSE)
-# text(xlim_no_zoom[1]-3+0.4, ylim_no_zoom[2]-0.4, "B", cex = 1.2)
-# text(xlim_no_zoom[2]-3- 0.2, ylim_no_zoom[1] + 0.2, "Human data set 2", cex = 0.8, adj = c(1, 0), col = "grey30")
-# dev.off()
-
-ylim_no_zoom[2] <-ylim_no_zoom[2] + 1
+ylim_no_zoom[2] <-ylim_no_zoom[2] - 2
+xlim_no_zoom[2] <-xlim_no_zoom[2] - 2
+ylim_no_zoom[1] <-ylim_no_zoom[1] +1
+
 png(file.path(figure_dir, paste0("proc_", gsub(".ace", "", target_map), "_show_only_commonAgs.png")), width = 12, height = 5, units = 'in', res=300, pointsize = 18)
 layout(matrix(c(1:2), ncol = 2, byrow = T))
 par(mar = rep(0.5, 4))
 doplot(procrustesMap(removeAntigens(alignment_map, agNames(alignment_map)[!agNames(alignment_map) %in% agNames(full_map)]), full_map, scaling = TRUE), xlim_no_zoom, ylim_no_zoom, FALSE)
 text(xlim_no_zoom[1]+0.4, ylim_no_zoom[2]-0.4, "A", cex = 1.2)
 text(xlim_no_zoom[2]-0.2, ylim_no_zoom[1]+ 0.2, "Human data set 1", cex = 0.8, adj = c(1, 0), col = "grey30")
-doplot(procrustesMap(move_coords(move_coords(removeAntigens(duke_map, agNames(duke_map)[!agNames(duke_map) %in% agNames(full_map)]), at = 1, by = -2), at =2, by = +2), full_map, scaling = TRUE), xlim_no_zoom-1, ylim_no_zoom+2, FALSE)
-text(xlim_no_zoom[1]-1+0.4, ylim_no_zoom[2]+2-0.4, "B", cex = 1.2)
-text(xlim_no_zoom[2]-1- 0.2, ylim_no_zoom[1]+2 + 0.2, "Human data set 2", cex = 0.8, adj = c(1, 0), col = "grey30")
+doplot(procrustesMap(move_coords(move_coords(removeAntigens(duke_map, agNames(duke_map)[!agNames(duke_map) %in% agNames(full_map)]), at = 1, by = -2), at =2, by = 0), full_map, scaling = TRUE), xlim_no_zoom, ylim_no_zoom, FALSE)
+text(xlim_no_zoom[1]+0.4, ylim_no_zoom[2]-0.4, "B", cex = 1.2)
+text(xlim_no_zoom[2]- 0.2, ylim_no_zoom[1] + 0.2, "Human data set 2", cex = 0.8, adj = c(1, 0), col = "grey30")
 dev.off()
 
-
-# 
-# png(file.path(figure_dir, "proc_map_threshold20_all_ags_singleTP_woXBBBQ11conv_alpha_adj_unscaled.png"), width = 12, height = 5, units = 'in', res=300, pointsize = 18)
-# layout(matrix(c(1:2), ncol = 2, byrow = T))
-# par(mar = rep(0.5, 4))
-# doplot(procrustesMap(alignment_map, full_map, scaling = FALSE), xlim_no_zoom, ylim_no_zoom, FALSE)
-# text(xlim_no_zoom[1]+0.4, ylim_no_zoom[2]-0.4, "A", cex = 1.2)
-# doplot(procrustesMap(duke_map, full_map, scaling = FALSE), xlim_no_zoom, ylim_no_zoom, FALSE)
-# text(xlim_no_zoom[1]+0.4, ylim_no_zoom[2]-0.4, "B", cex = 1.2)
-# dev.off()
-# 
-# 

figures/labelled_map/plot_labelled_map_final.R

@@ -20,8 +20,8 @@ move_coords <- function(map, at = 2, by = -0.5){
 # map_alpha_unadj <- move_coords(map_alpha_unadj, at = 2, by = -1)
 
 
-map <- read.acmap("data/maps/map_threshold20_all_ags_singleTP_woXBBBQ11conv_alphaJN1ba286_adjScan.ace")
-map_alpha_unadj <- read.acmap("./data/maps/map_threshold20_all_ags_singleTP_woXBBBQ11conv.ace")
+map <- read.acmap("data/maps/map_threshold20_all_ags_singleTP_woXBBBQ11conv_woXBB15conv_woJN1BA286_alpha_adj.ace")
+map_alpha_unadj <- read.acmap("data/maps/map_threshold20_all_ags_singleTP_woXBBBQ11conv_woXBB15conv_woJN1BA286.ace")
 
 lims <- Racmacs:::mapPlotLims(map, sera = FALSE)
 lims_no_zoom <- Racmacs:::mapPlotLims(map, sera = TRUE)
@@ -38,9 +38,6 @@ write.csv(xlim_no_zoom, "./data/metadata/xlim_no_zoom.csv")
 write.csv(ylim_zoom, "./data/metadata/ylim_zoom.csv")
 write.csv(xlim_zoom, "./data/metadata/xlim_zoom.csv")
 
-ylim_zoom[2] <- ylim_zoom[2] - 1
-xlim_zoom[1] <- xlim_zoom[1] + 1
-
 
 map <- move_coords(map, at = 2, by = -0.3)
 map <- move_coords(map, at = 1, by = 0.2)
@@ -109,13 +106,13 @@ par(mar = rep(0.5, 4))
 doplot(map, xlim_no_zoom, ylim_no_zoom, FALSE)
 dev.off()
 
-png("figures/labelled_map/map_zoom.png", 5, 4, units = 'in', res=300, pointsize = 12)
+png("figures/labelled_map/map_zoom.png", 4, 5, units = 'in', res=300, pointsize = 12)
 par(mar = rep(0.5, 4))
 doplot(map, xlim_zoom, ylim_zoom, FALSE)
 dev.off()
 
 
-png("figures/labelled_map/alpha_unadj_proc_map_zoom.png", 8, height = 3, units = 'in', res=300, pointsize = 12)
+png("figures/labelled_map/alpha_unadj_proc_map_zoom.png", 5, height = 3, units = 'in', res=300, pointsize = 12)
 layout(matrix(c(1:2), ncol = 2, byrow = T))
 par(mar = rep(0.5, 4))
 doplot(map_alpha_unadj, xlim_zoom, ylim_zoom, FALSE)

figures/titer_lineplots/titerlineplots.R

@@ -31,9 +31,8 @@ data_long %>%
 
 target_groups <- c('Wuhan vax. (single dose)','Beta vax. (single dose)','Wuhan vax. (two doses)', 'XBB.1.5 vax. (two doses)',
                    'Wuhan conv.', 'alpha conv.','beta conv.',
-                   'gamma conv.', 'delta conv.', 'BA.1 conv.', 'BA.2.12.1 conv.', 'BA.4 conv.', 'BA.5 conv.', 
-                 #  'BQ.1.1 conv.', 'XBB conv.', 
-                   'XBB.1.5 conv.')
+                   'gamma conv.', 'delta conv.', 'BA.1 conv.', 'BA.2.12.1 conv.', 'BA.4/5 conv.') 
+
 paste(target_groups, collapse = "', '")
 
 target_ags <- c('Wuhan', 'Alpha', 'Delta', 'Beta', 'BA.1', 'BA.2', 'BA.5', 'XBB.1.5', 'BA.2.86', 'JN.1', "KP.3", "KP.2", "KZ.1.1.1")
@@ -80,7 +79,7 @@ titerplot20_a <- do_titer_plot_fc_label(map, 4, thresh = 20, fc_label = FALSE, a
   theme(axis.text.x = element_text(angle = 90, vjust = 0.5))
 
 targets_b_main <- target_sr_groups_b
-titerplot20_b <- do_titer_plot_fc_label(map, 3, thresh = 20, fc_label = FALSE, adj_titers = FALSE,
+titerplot20_b <- do_titer_plot_fc_label(map, 4, thresh = 20, fc_label = FALSE, adj_titers = FALSE,
                                         sr_group_gmt_plotdata = sr_group_gmt %>%
                                           filter(sr_group %in% targets_b_main),
                                         fc_df = fc_df %>%
@@ -94,13 +93,15 @@ titerplot20_b <- do_titer_plot_fc_label(map, 3, thresh = 20, fc_label = FALSE, a
                                         facet_levels = targets_b_main) + 
   theme(axis.text.x = element_text(angle = 90, vjust = 0.5))
 
-(plot_spacer() + titerplot20_b + plot_spacer() + plot_layout(widths = c(0.25, 3, 0.4))) / titerplot20_a + plot_layout(heights = c(3.5, 1)) + plot_annotation(tag_levels = 'A') -> titerplot20
+# (plot_spacer() + titerplot20_b + plot_spacer() + plot_layout(widths = c(0.25, 3, 0.4))) / titerplot20_a + plot_layout(heights = c(3.5, 1)) + plot_annotation(tag_levels = 'A') -> titerplot20
+
+titerplot20_b / titerplot20_a + plot_layout(heights = c(2.2, 1)) + plot_annotation(tag_levels = 'A') -> titerplot20
 
-ggsave("figures/titer_lineplots/sr_group_titerlineplot_threshold20_map_unadj_noLabel.png", titerplot20, dpi = 300, width = 12, height = 10)
+ggsave("figures/titer_lineplots/sr_group_titerlineplot_threshold20_map_unadj_noLabel.png", titerplot20, dpi = 300, width = 12, height = 8)
 
 
 #--------------------------------------------- Load alpha adjusted data
-map <- read.acmap("./data/maps/map_threshold20_all_ags_singleTP_woXBBBQ11conv_alphaJN1ba286_adjScan.ace")
+map <- read.acmap("./data/maps/map_threshold20_all_ags_singleTP_woXBBBQ11conv_woXBB15conv_woJN1BA286_alpha_adj.ace")
 
 data_long <- long_map_info(remove_na_coords(map)) %>%
   mutate(titer = titer_adjusted,
@@ -130,7 +131,7 @@ sr_table_np[match(target_groups, sr_table_np$sr_group),] %>%
 write.csv(sr_table_np, "data/titer_data/sr_table.csv", row.names = FALSE)
 
 
-map <- read.acmap("./data/maps/map_threshold20_all_ags_singleTP_woXBBBQ11conv_alphaJN1ba286_adjScan.ace")
+map <- read.acmap("./data/maps/map_threshold20_all_ags_singleTP_woXBBBQ11conv_woXBB15conv_woJN1BA286_alpha_adj.ace")
 
 srGroups(map) <- gsub("BA.4 conv.|BA.5 conv.", 'BA.4/5 conv.', srGroups(map))
 
@@ -160,6 +161,7 @@ if(file.exists("data/titer_data/fc_from_homologous_threshold20.csv")){
 }
 
 
+ag_order <- ag_order[!grepl("JN.1|BA.2.86", ag_order)]
 
 titerplot20_a <- do_titer_plot_fc_label(map, 4, thresh = 20, fc_label = FALSE, adj_titers = TRUE,
                                         sr_group_gmt_plotdata = sr_group_gmt %>%
@@ -175,7 +177,7 @@ titerplot20_a <- do_titer_plot_fc_label(map, 4, thresh = 20, fc_label = FALSE, a
                                         show_gmt = TRUE) + 
   theme(axis.text.x = element_text(angle = 90, vjust = 0.5))
 
-titerplot20_b <- do_titer_plot_fc_label(map, 3, thresh = 20, fc_label = FALSE, adj_titers = TRUE,
+titerplot20_b <- do_titer_plot_fc_label(map, 4, thresh = 20, fc_label = FALSE, adj_titers = TRUE,
                                         sr_group_gmt_plotdata = sr_group_gmt %>%
                                           filter(sr_group %in% target_sr_groups_b),
                                         fc_df = fc_df %>%
@@ -188,6 +190,6 @@ titerplot20_b <- do_titer_plot_fc_label(map, 3, thresh = 20, fc_label = FALSE, a
                                         show_gmt_conf = TRUE)+ 
   theme(axis.text.x = element_text(angle = 90, vjust = 0.5))
 
-(plot_spacer() + titerplot20_b + plot_spacer() + plot_layout(widths = c(0.25, 3, 0.4))) / titerplot20_a + plot_layout(heights = c(3.5, 1)) + plot_annotation(tag_levels = 'A') -> titerplot20
+titerplot20_b / titerplot20_a + plot_layout(heights = c(2.2, 1)) + plot_annotation(tag_levels = 'A') -> titerplot20
 
-ggsave("figures/titer_lineplots/sr_group_titerlineplot_threshold20_map_noLabel.png", titerplot20, dpi = 300, width = 12, height = 10)
+ggsave("figures/titer_lineplots/sr_group_titerlineplot_threshold20_map_noLabel.png", titerplot20, dpi = 300, width = 12, height = 8)

functions/sams_landscape_functions.R

@@ -285,11 +285,11 @@ plot_landscapes_from_list <- function(data3js, titertables_groups, lndscp_fits,m
 
       )
       }
-      text_x <- c(c(agCoords(map)[agNames(map) %in% ag_labelled, 1] - agSize(map)[agNames(map) %in% ag_labelled]*0.05))
-      text_x[3] <- text_x[3] + 1.1
-      text_x[1] <- text_x[1] -0.4
+      text_x <- c(agCoords(map)[agNames(map) %in% ag_labelled, 1]) - 0.3
+      text_x[4:5] <- text_x[4:5] + 0.6
+    #  text_x[1] <- text_x[1] -0.4
       text_y <- c(c(agCoords(map)[agNames(map) %in% ag_labelled, 2]))
-
+      text_y[1:3] <- text_y[1:3]- 0.5
       # set points and coordinates of highlighted ags