---
title: "04-venn"
format: html
editor: visual
---

```{r}
# Install and load the necessary packages
#install.packages("VennDiagram")
library(VennDiagram)
library(grid)

# Create a list containing 20 themes or keywords for each project
project_themes <- list(
  Project1 = c("marine", "corals", "epigenetics", "environment", "stressors", "inheritance", "reef_building", "physiology", "ecology", "evolution", "symbiosis", "education", "energetics", "metabolic", "phenotype", "E5_platform", "STEM", "open_science", "quantitative_approaches", "research_reproducibility"),
  Project2 = c("marine", "oysters", "epigenetics", "environment", "stressors", "inheritance", "aquaculture", "DNA_methylation", "Crassostrea_virginica", "ocean_acidification", "intergenerational_response", "genomics", "adaptation", "bioinformatics", "biogeochemistry", "E2O", "girls_in_STEM", "low_income_schools", "open_science", "reproducibility"),
  Project3 = c("marine", "oysters", "epigenetics", "environment", "stressors", "inheritance", "climate_change", "physiology", "Crassostrea_gigas", "tetraploid", "triploid", "temperature", "salinity", "low_pH", "oxygen_consumption", "shell_morphology", "survival_rates", "proteomics", "DNA_methylation", "environmental_conditions"),
  Project4 = c("marine", "oysters", "epigenetics", "environment", "stressors", "inheritance", "genomics", "Olympia_oyster", "Puget_Sound", "restoration", "protection", "environmental_change", "ecological_interactions", "population_structure", "genetic_variation", "RAD-Seq", "BS-Seq", "web-based_platform", "discovery", "collaboration")
)

# Generate the Venn diagram to visualize the relationships
venn.plot <- venn.diagram(
  x = project_themes,
  category.names = c("Project 1", "Project 2", "Project 3", "Project 4"),
  filename = NULL,
  output = TRUE
)

grid.draw(venn.plot)


```

```{r}
# Install and load the necessary packages
#install.packages("eulerr")
library(eulerr)

# Create a data frame containing 20 themes or keywords for each project
project_themes <- data.frame(
  themes = c(rep("Project1", 20), rep("Project2", 20), rep("Project3", 20), rep("Project4", 20)),
  keywords = c("marine", "corals", "epigenetics", "environment", "stressors", "inheritance", "reef_building", "physiology", "ecology", "evolution", "symbiosis", "education", "energetics", "metabolic", "phenotype", "E5_platform", "STEM", "open_science", "quantitative_approaches", "research_reproducibility",
               "marine", "oysters", "epigenetics", "environment", "stressors", "inheritance", "aquaculture", "DNA_methylation", "Crassostrea_virginica", "ocean_acidification", "intergenerational_response", "genomics", "adaptation", "bioinformatics", "biogeochemistry", "E2O", "girls_in_STEM", "low_income_schools", "open_science", "reproducibility",
               "marine", "oysters", "epigenetics", "environment", "stressors", "inheritance", "climate_change", "physiology", "Crassostrea_gigas", "tetraploid", "triploid", "temperature", "salinity", "low_pH", "oxygen_consumption", "shell_morphology", "survival_rates", "proteomics", "DNA_methylation", "environmental_conditions",
               "marine", "oysters", "epigenetics", "environment", "stressors", "inheritance", "genomics", "Olympia_oyster", "Puget_Sound", "restoration", "protection", "environmental_change", "ecological_interactions", "population_structure", "genetic_variation", "RAD-Seq", "BS-Seq", "web-based_platform", "discovery", "collaboration")
)

# Create an euler diagram
project_euler <- euler(project_themes, input = "binary")

# Plot the diagram
plot(project_euler, quantities = TRUE)

```

```{r}
# Install and load the necessary packages
install.packages("venn")
library(venn)

# Create a list containing 20 themes or keywords for each project
project_themes <- list(
  Project1 = c("marine", "corals", "epigenetics", "environment", "stressors", "inheritance", "reef_building", "physiology", "ecology", "evolution", "symbiosis", "education", "energetics", "metabolic", "phenotype", "E5_platform", "STEM", "open_science", "quantitative_approaches", "research_reproducibility"),
  Project2 = c("marine", "oysters", "epigenetics", "environment", "stressors", "inheritance", "aquaculture", "DNA_methylation", "Crassostrea_virginica", "ocean_acidification", "intergenerational_response", "genomics", "adaptation", "bioinformatics", "biogeochemistry", "E2O", "girls_in_STEM", "low_income_schools", "open_science", "reproducibility"),
  Project3 = c("marine", "oysters", "epigenetics", "environment", "stressors", "inheritance", "climate_change", "physiology", "Crassostrea_gigas", "tetraploid", "triploid", "temperature", "salinity", "low_pH", "oxygen_consumption", "shell_morphology", "survival_rates", "proteomics", "DNA_methylation", "environmental_conditions"),
  Project4 = c("marine", "oysters", "epigenetics", "environment", "stressors", "inheritance", "genomics", "Olympia_oyster", "Puget_Sound", "restoration", "protection", "environmental_change", "ecological_interactions", "population_structure", "genetic_variation", "RAD-Seq", "BS-Seq", "web-based_platform", "discovery", "collaboration")
)

# Plot the Venn diagram with keywords
venn(project_themes, ilab = TRUE, zcolor = "style", cexil = 0.6)

```

```{r}
# Install and load the necessary packages
install.packages("igraph")
library(igraph)

# Create a list containing 20 themes or keywords for each project
project_themes <- list(
  Project1 = c("marine", "corals", "epigenetics", "environment", "stressors", "inheritance", "reef_building", "physiology", "ecology", "evolution", "symbiosis", "education", "energetics", "metabolic", "phenotype", "E5_platform", "STEM", "open_science", "quantitative_approaches", "research_reproducibility"),
  Project2 = c("marine", "oysters", "epigenetics", "environment", "stressors", "inheritance", "aquaculture", "DNA_methylation", "Crassostrea_virginica", "ocean_acidification", "intergenerational_response", "genomics", "adaptation", "bioinformatics", "biogeochemistry", "E2O", "girls_in_STEM", "low_income_schools", "open_science", "reproducibility"),
  Project3 = c("marine", "oysters", "epigenetics", "environment", "stressors", "inheritance", "climate_change", "physiology", "Crassostrea_gigas", "tetraploid", "triploid", "temperature", "salinity", "low_pH", "oxygen_consumption", "shell_morphology", "survival_rates", "proteomics", "DNA_methylation", "environmental_conditions"),
  Project4 = c("marine", "oysters", "epigenetics", "environment", "stressors", "inheritance", "genomics", "Olympia_oyster", "Puget_Sound", "restoration", "protection", "environmental_change", "ecological_interactions", "population_structure", "genetic_variation", "RAD-Seq", "BS-Seq", "web-based_platform", "discovery", "collaboration")
)

# Create edges between project nodes and theme nodes
edges <- do.call(rbind, lapply(names(project_themes), function(project) {
  cbind(project, project_themes[[project]])
}))

# Create the graph object
g <- graph_from_edgelist(edges)

# Set vertex attributes
V(g)$type <- bipartite_mapping(g)$type
V(g)$color <- ifelse(V(g)$type, "lightblue", "gold")
V(g)$label.color <- "black"
V(g)$label.font <- 2
V(g)$label.cex <- 0.8
V(g)$size <- ifelse(V(g)$type, 15, 5)

# Set edge attributes
E(g)$color <- "gray"

# Plot the network diagram
plot(g, layout = layout_as_bipartite, vertex.label.dist = 1, main = "Project Keyword Network Diagram")

```