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Merge pull request #261 from DataINCITE/xuz16 
updated charts on main page
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@erickj4
erickj4 committed Dec 6, 2022
2 parents a85f779 + 5e9db27 commit f6a05a356a527fd5994b2fc1f7e93b9dffef7c19
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Showing 3 changed files with 1,113 additions and 1,448 deletions.
87 app/app.R
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@@ -85,16 +85,47 @@ disease2gene <- readRDS("data/disease2gene.Rds")

genedata <- readRDS("data/genedata/genedata.Rds")
diseases <- disease2gene$Disease
studydata <- readRDS("data/studydata/studydata.Rds")
levels(studydata$Type) <- c(levels(studydata$Type), "phytochemicals")
studydata$Type[studydata$Type=="polyphenol"] <- "phytochemicals"
studydata <- readRDS("data/studydata/studydata.Rds")
levels(studydata$Type) <- c(levels(studydata$Type), "phytochemical")
studydata$Type[studydata$Type=="polyphenol"] <- "phytochemical"
studydata$Type[grepl('extract', studydata$Type)] <- "whole food extract"
studydata$Type[grepl('extract', studydata$Nutrient)] <- "whole food extract"
studydata$Type[grepl('blackberry', studydata$Nutrient)] <- "whole food extract"
studydata$Type[studydata$Nutrient=="egg yolks"] <- "whole food"


levels(studydata$Nutrient) <- c(levels(studydata$Nutrient), "soy extract")
levels(studydata$Nutrient) <- c(levels(studydata$Nutrient), "rosemary extract")
levels(studydata$Nutrient) <- c(levels(studydata$Nutrient), "yellow onion extract")
levels(studydata$Nutrient) <- c(levels(studydata$Nutrient), "aspera leaves extract")
levels(studydata$Nutrient) <- c(levels(studydata$Nutrient), "passionfruit extract")

studydata$Nutrient[studydata$Nutrient=="rosemary"] <- "rosemary extract"
studydata$Nutrient[studydata$Nutrient=="yellow onion"] <- "yellow onion extract"
studydata$Nutrient[studydata$Nutrient=="aaspera leaves"] <- "aspera leaves extract"
studydata$Nutrient[studydata$Nutrient=="passionfruit juice"] <- "passionfruit extract"
studydata$Type[studydata$Nutrient=="aspera leaves extract"] <- "whole food extract"
studydata$Type[studydata$Nutrient=="cinnamon"] <- "phytochemical"
studydata$Nutrient[studydata$Nutrient=="soy"] <- "soy extract"
studydata$Type[studydata$Nutrient=="soy extract"] <- "whole food extract"
print(studydata$Nutrient)

studydata <- studydata %>% drop_na(Nutrient)

nutrient_info <- read_csv("data/nutrient_info_lesscategories.csv")

nutrient_info$Category[grepl('extract', nutrient_info$Nutrient)] <- "whole food extract"
nutrient_info$Description[nutrient_info$Nutrient=="orange juice"] <- "Orange juice is a popular beverage that is enjoyed worldwide. Nutritionally, it is high in potassium, folate, and vitamin C as well as other antioxidants and important nutrients. At least some studies have associated its regular consumption with numerous health benefits including anti-inflammation, heart health, prevention of kidney stones, and wound healing. However, it is also high in sugar and calories and so should be taken in moderation.
"
levels(nutrient_info$Nutrient) <- c(levels(nutrient_info$Nutrient), "grape extract")
nutrient_info$Type[nutrient_info$Nutrient=="grape"] <- "grape extract"
levels(nutrient_info$Nutrient) <- c(levels(nutrient_info$Nutrient), "casei")
nutrient_info$Type[nutrient_info$Nutrient=="casei"] <- "l. casei"


levels(nutrient_info$Nutrient) <- c(levels(nutrient_info$Nutrient), "rosemary extract")
nutrient_info$Nutrient[nutrient_info$Nutrient=="rosemary"] <- "rosemary extract"


join.gene <- inner_join(disease2gene, genedata, c('Gene'='Gene', 'Expression'='Expression'))
diseases_with_matches <- as.factor(unique(as.character(join.gene$Disease)))
@@ -155,10 +186,10 @@ ui <- fluidPage(theme = Eat4Genes_theme,
sidebarPanel(
tags$style(".well {background-color:#818589;}"),
h1("Our Mission:", style = "color:white"),
p("Almost half of the world’s population has one or more chronic diseases with resultant
p("Much of the world’s population has one or more chronic diseases with resultant
pain and suffering as well as the vast majority of health care spending. Drug
treatments are often expensive and can include a wide range of side- and long term- effects. Alternative approaches such as diet that reduce cost and improve health thus have major potential value in health care.", style = "color:white"),
p("Eat4Genes is a dietary guide for patients, community, and healthcare providers to aid in the
p("Eat4Genes is a dietary guide for patients, community, healthcare providers, and researchers to aid in the
selection of healthy diet to help treat and prevent numerous pathologies and
conditions. It is based on the evaluation of clinically-relevant gene expression in
response to healthy diet with an emphasis on whole foods and whole food extracts.", style = "color:white"),
@@ -178,8 +209,7 @@ nutrition in the form of personalized confirmation of our suggested diet.", styl
img(src = "picOfWholeFoodsTweak.jpg", width = 450),
br(),
br(),
h3("Almost half of the world’s population has one or
more chronic diseases with the vast majority of health care spending."),
h3("Sixty percent of Americans have at least one chronic disease and a third of the world’s population has more than one. These are responsible for the vast majority of health care spending."),
h3("Eat4Genes is a dietary guide that aids in
the selection of healthy diet to help treat and prevent
numerous pathologies and conditions.")
@@ -215,7 +245,7 @@ nutrition in the form of personalized confirmation of our suggested diet.", styl
h3("Navigate Page:", style = "color:white"),
p("The plots to the right relate the nutrients with their associated ranking.", style = "color:white"),
p("The ranking represents the strength of the evidence
prensented for that dietary nutrient based on the details of the study(s) the
presented for that dietary nutrient based on the details of the study(s) the
data is from.", style = "color:white"),
p("Click the 'Toggle Plot/Bubble View' button to switch between a Bar graph and a Bubble Plot.", style = "color:white"),
p("For more information about each dietary nutrient, see table below.", style = "color:white"),
@@ -243,8 +273,8 @@ nutrition in the form of personalized confirmation of our suggested diet.", styl
br(),
DTOutput("foodstable"),
p("The Ranking represents the strength of the evidence
prensented for that dietary nutrient based on the study the
data is from."),
presented for that dietary nutrient based on the study the
data is from. See “Ranking System” under homepage “About” menu for details."),
#actionButton("jump2genes","Next"),
),

@@ -262,11 +292,11 @@ nutrition in the form of personalized confirmation of our suggested diet.", styl
p(icon("arrow-down"),
strong("Downregulation"),
"is the process by which a cell decreases the quantity
of a cellular component.", style = "color:white"),
of a gene product, most commonly RNA.", style = "color:white"),
p(icon("arrow-up"),
strong("Upregulation"),
"is the process by which a cell increases the quantity
of a cellular component.", style = "color:white"),
of a gene product, most commonly RNA.", style = "color:white"),
br(),
h5(textOutput("riskgene_string"), style = "color:white"),
br(),
@@ -302,7 +332,7 @@ nutrition in the form of personalized confirmation of our suggested diet.", styl
downloadButton("report", "Download A Detailed Report"),
br(),
br(),
h2(" Target Genes"),
h2(" Targeted Genes and Desired Expressions"),
br(),
p("The key genes analyzed for this selected disease or condition include:"),
uiOutput("genes"),
@@ -389,7 +419,7 @@ nutrition in the form of personalized confirmation of our suggested diet.", styl
h3("Navigate Page:", style = "color:white"),
p("The plots to the right relate the nutrients with their associated ranking.", style = "color:white"),
p("The ranking represents the strength of the evidence
prensented for that dietary nutrient based on the details of the study(s) the
presented for that dietary nutrient based on the details of the study(s) the
data is from.", style = "color:white"),
p("Click the 'Toggle Plot/Bubble View' button to switch between a Bar graph and a Bubble Plot.", style = "color:white"),
p("For more information about each dietary nutrient, see table below.", style = "color:white"),
@@ -417,8 +447,8 @@ nutrition in the form of personalized confirmation of our suggested diet.", styl
br(),
DTOutput("foodstable_g"),
p("The Ranking represents the strength of the evidence
prensented for that dietary nutrient based on the study the
data is from.")
presented for that dietary nutrient based on the study the
data is from. See “Ranking System” under homepage “About” menu for details.")
),

tabPanel("Data Sources", value = "studies",
@@ -517,8 +547,8 @@ server <- function(input,output, session){
#render home-page plots

#render pie chart
piedata <- data.frame(typePie = c('With Chronic Conditions', 'Without Chronic Conditions'),percentPie = c(48,52))
output$piePlot <- renderPlot({ ggplot(data = data.frame(typePie = c('With Chronic Conditions', 'Without Chronic Conditions'),percentPie = c(48,52)),
piedata <- data.frame(typePie = c('With Chronic Conditions', 'Without Chronic Conditions'),percentPie = c(100*1/3,100*2/3))
output$piePlot <- renderPlot({ ggplot(data = data.frame(typePie = c('With Chronic Conditions', 'Without Chronic Conditions'),percentPie = c(100*1/3,100*2/3)),
aes(x="", y=percentPie, fill=typePie)) +
geom_bar(width = 1, stat = "identity", color = "white") +
coord_polar("y", start = 0) +
@@ -529,9 +559,10 @@ server <- function(input,output, session){
plot.title = element_text(size = 20,
face = "bold",
hjust = 0.5,
lineheight = 0.9)) +
labs(title = "Percent of World Population \nwith a Chronic Condition",
caption = "data source TODO")
lineheight = 0.9),
plot.caption = element_text(hjust = 0.5)) +
labs(title = "Percent of World Population \nwith Multiple Chronic Conditions",
caption = "From: Hajat C, Stein E. The global burden of multiple chronic conditions: \n A narrative review. Prev Med Rep. 2018 Oct 19;12:284-293.")
},
height = 300)

@@ -546,7 +577,8 @@ server <- function(input,output, session){
plot.title = element_text(size = 20,
face = "bold",
hjust = 0.5,
lineheight = 0.9))+
lineheight = 0.9),
plot.caption = element_text(hjust = 0.5))+
labs(x = "",
y = "U.S.Health Care Costs (% GDP)" )+
scale_fill_viridis(discrete = TRUE, option = "D") +
@@ -566,7 +598,8 @@ server <- function(input,output, session){
plot.title = element_text(size = 20,
face = "bold",
hjust = 0.5,
lineheight = 0.9)) +
lineheight = 0.9),
plot.caption = element_text(hjust = 0.5)) +
labs(x = "",
y = "U.S.Health Care Costs (% GDP)" ) +
labs(title ="Rising U.S. Health Care Costs",
@@ -893,7 +926,7 @@ server <- function(input,output, session){
mutate(Expression = ifelse(Expression == "up",
as.character(icon("arrow-up")),
as.character(icon("arrow-down"))
)) )
)))


# Output risk genes
@@ -1056,7 +1089,7 @@ server <- function(input,output, session){
# even_body = "#E9F3FC") %>%
font(fontname = "Arial", part = "all") %>%
autofit() %>%
add_header_lines(values = "Target Genes", top = TRUE) %>%
add_header_lines(values = "Targeted Genes and Desired Expressions", top = TRUE) %>%
htmltools_value()})

output$p_table <- renderUI({
@@ -1389,14 +1422,14 @@ server <- function(input,output, session){
options = list( order = list(0, "desc"),
dom = 'Bfrtip',
buttons = c('csv', 'excel', 'pdf')),
caption = htmltools::tags$caption(
caption = htmltools::tags$caption(
style = 'caption-side: top;
text-align: center;
color:black;
font-size:200% ;',
'Studies Referenced for Food Guide'),
extensions = "Buttons",
colnames = c("Ranking", "Nutrient", "Study Name", "Link", "Summary", "In vitro / In vivo", "Type of Nutrient", "Concentration", "Sample Size"),
colnames = c("Ranking", "Nutrient", "Study Name", "Link", "Summary", "In vitro / vivo", "Type of Nutrient", "Concentration", "Sample Size"),
escape = FALSE,
rownames = FALSE)

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