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K6_STRUCTURE_plot.R
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K6_STRUCTURE_plot.R
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library(tidyverse)
library(patchwork)
library(sf)
library(RColorBrewer)
library(ggh4x)
#library(ggrepel)
#library(ggspatial)
### For Evanno method ###
# Clear environment and restart session before running Pophelper
#library(pophelper)
#library(pophelperShiny)
#runPophelper()
#devtools::install_github("Tom-Jenkins/mapmixture")
library(mapmixture)
#launch_mapmixture()
# Prep 2111 data to work with plotting
Samples_2111 <- read_delim("X:/2111_F1F2D_BKT/2111analysis/Thometz_scripts/Samples_2111.csv") %>%
filter(Cohort == "Domestic") %>%
mutate(WaterbodyName = "St. Croix Falls Strain",
HUC_2 = "Hatchery",
HUC_8 = "Hatchery",
.keep = "unused") %>%
select(SampleID, WaterbodyName, HUC_8, HUC_2)
# Read in 2205 metadata data
Samples_2205 <- read_delim("X:/2205_BKT_feral_broodstock_ID/Thometz_scripts/Samples_2205.csv") %>%
select(SampleID, WaterbodyName, HUC_8, HUC_2, Latitude, Longitude) %>%
bind_rows(Samples_2111)
#########################################################
#### Plot most supported number of clusters (K = 6) ####
# K = 6 STRUCTURE run
K6 <- read_delim("X:/2205_BKT_feral_broodstock_ID/Thometz_scripts/Analyses/Structure_relatedness/STRUCTURE/Final_run_2205/AssProbs_CleanedUp/K6_AssProbs_CleanedUp.txt") %>%
select(-c(n, percent_miss)) %>%
mutate(C6 = as.numeric(C6)) %>%
rename(K1 = C4,
K2 = C6,
K3 = C3,
K4 = C1,
K5 = C5,
K6 = C2)
K6_longer <- K6 %>%
pivot_longer(cols = 2:7,
names_to = "Cluster",
values_to = "Probability") %>%
left_join(Samples_2205) %>%
mutate(Cluster = str_replace(Cluster, "K", ""),
Cluster = str_replace(Cluster, "1", "1 (St. Croix Falls Strain)"),
Cluster = fct_relevel(Cluster, c("1 (St. Croix Falls Strain)", "2", "3", "4", "5", "6")),
HUC_8 = fct_relevel(HUC_8, "Hatchery", after = Inf))
brewer.pal(n = 6, name = "Set1")
K6_colors <- c("#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "yellow3")
#K6_colors <- c("#984EA3", "#FF7F00", "#4DAF4A", "#E41A1C", "yellow3", "#377EB8")
# Plot
K6_1 <- K6_longer %>%
filter(HUC_2 == "Upper Mississippi Region") %>%
ggplot(aes(x = SampleID, y = Probability, fill = Cluster)) +
geom_col(show.legend = FALSE) +
facet_nested(cols = vars(HUC_8, WaterbodyName),
switch = "x",
nest_line = element_line(linewidth = 1, lineend = "round"),
solo_line = TRUE,
resect = unit(0.05, "in"),
scales = "free",
space = "free") +
labs(x = "",
y = "Admixture\nproportion",
title = "Upper Mississippi Region (HUC 2)") +
scale_y_continuous(expand = c(0, 0),
position = "left",
breaks = seq(0, 1, by = 0.5)) +
scale_fill_manual(values = K6_colors) +
#scale_fill_brewer(palette = "Set1") +
theme_minimal() +
theme(panel.spacing = unit(0.1, "line"),
axis.text.x = element_blank(),
strip.text.x = element_text(angle = -90,
hjust = 0))
K6_2 <- K6_longer %>%
filter(HUC_2 == "Great Lakes Region" |
HUC_2 == "Hatchery") %>%
ggplot(aes(x = SampleID, y = Probability, fill = Cluster)) +
geom_col(show.legend = TRUE) +
facet_nested(cols = vars(HUC_8, WaterbodyName),
switch = "x",
nest_line = element_line(linewidth = 1, lineend = "round"),
solo_line = TRUE,
resect = unit(0.05, "in"),
scales = "free",
space = "free") +
labs(x = "",
y = "Admixture\nproportion",
title = "Great Lakes Region (HUC 2)",
fill = "Cluster (STRUCTURE)") +
scale_y_continuous(expand = c(0, 0),
position = "left",
breaks = seq(0, 1, by = 0.5)) +
scale_fill_manual(values = K6_colors) +
#scale_fill_brewer(palette = "Set1") +
theme_minimal() +
theme(panel.spacing = unit(0.1, "line"),
axis.text.x = element_blank(),
strip.text.x = element_text(angle = -90,
hjust = 0),
legend.position = "bottom",
legend.direction = "horizontal") +
guides(fill = guide_legend(nrow = 1))
K6_plots <- K6_1 / K6_2
ggsave(filename = "K6_str_plot.pdf",
plot = K6_plots,
device = "pdf",
path = "X:/2205_BKT_feral_broodstock_ID/Thometz_scripts/Polished_plots_figures/Genetic_structure/STRUCTURE",
height = 10,
width = 14,
units = "in")
ggsave(filename = "K6_str_plot.png",
plot = K6_plots,
device = "png",
path = "X:/2205_BKT_feral_broodstock_ID/Thometz_scripts/Polished_plots_figures/Genetic_structure/STRUCTURE",
height = 10,
width = 14,
units = "in")
############################
#### Plot them on a map ####
# Read in necessary shape files
HUC8_shp <- read_sf("X:/2205_BKT_feral_broodstock_ID/Mapping_shapefiles/Hydrologic_Units_-_8_digit_(Subbasins)/Hydrologic_Units_-_8_digit_(Subbasins).shp")
HUC2_shp <- read_sf("X:/2205_BKT_feral_broodstock_ID/Mapping_shapefiles/Major_Basins/Major_Basins.shp")
WMU_shp <- read_sf("X:/2205_BKT_feral_broodstock_ID/Mapping_shapefiles/Water_Management_Units/Water_Management_Units.shp")
# Figure out cluster for each pop
# Prep admixture df and lat long df for mapmixture function
K6_mapmixture <- K6 %>%
left_join(Samples_2205) %>%
select(WaterbodyName, SampleID, K1, K2, K3, K4, K5, K6) %>%
filter(WaterbodyName != "St. Croix Falls Strain")
# These are intentionally incorrect, revised for ease of viewing
Lats_Longs <- Samples_2205 %>%
select(WaterbodyName, Latitude, Longitude) %>%
filter(WaterbodyName != "St. Croix Falls Strain") %>%
distinct() %>%
mutate(Longitude = case_when(WaterbodyName == "Swan Creek" ~ -91.1,
WaterbodyName == "Marshall Creek - West Branch" ~ -90.7,
WaterbodyName == "Unnamed trib to Dell Creek (b)" ~ -89.97,
WaterbodyName == "Fourmile Creek" ~ -89.4,
WaterbodyName == "Lunch Creek" ~ -89.55,
WaterbodyName == "Lowery Creek" ~ -90.1,
WaterbodyName == "Knapp Creek" ~ -90.75,
WaterbodyName == "Tagatz Creek" ~ -89.75,
WaterbodyName == "Plover River" ~ -89.4,
WaterbodyName == "Marshall Creek" ~ -90.45,
WaterbodyName == "Flume Creek" ~ -89.15, .default = Longitude),
Latitude = case_when(WaterbodyName == "Bruce Creek" ~ 43.99,
WaterbodyName == "Marshall Creek" ~ 43.34,
WaterbodyName == "Little Willow Creek" ~ 45.7,
WaterbodyName == "Alvin Creek" ~ 45.91, .default = Latitude))
# Plot using mapmixture function
K6_map <- mapmixture(admixture_df = K6_mapmixture,
coords_df = Lats_Longs,
basemap = HUC2_shp,
boundary = c(xmin = -93.5,
xmax = -86.5,
ymin = 42,
ymax = 47.5),
cluster_names = c("1 (St. Croix Falls Strain)", "2", "3", "4", "5", "6"),
cluster_cols = K6_colors,
pie_size = 0.25,
pie_border = 0.05,
land_colour = "grey80",
sea_colour = NA,
arrow_size = 2,
arrow_position = "tr",
scalebar_size = 1,
scalebar_position = "tr",
axis_title_size = 8,
axis_text_size = 6,
plot_title = "STRUCTURE (K = 6)",
plot_title_size = 10) +
theme_classic() +
guides(fill = guide_legend(override.aes = list(size = 5, alpha = 1))) +
labs(fill = "Cluster") +
theme(legend.title = element_text(size = 10),
legend.text = element_text(size = 8),
axis.text = element_text(size = 6))
ggsave(filename = "K6_map.pdf",
plot = K6_map,
device = "pdf",
path = "X:/2205_BKT_feral_broodstock_ID/Thometz_scripts/Polished_plots_figures/Genetic_structure/STRUCTURE",
height = 5,
width = 5,
units = "in")
ggsave(filename = "K6_map.png",
plot = K6_map,
device = "png",
path = "X:/2205_BKT_feral_broodstock_ID/Thometz_scripts/Polished_plots_figures/Genetic_structure/STRUCTURE",
height = 5,
width = 5,
units = "in")