geposanui/ui.R

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R
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library(DT)
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library(plotly)
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library(shiny)
ui <- fluidPage(
titlePanel("TPE-OLD candidates"),
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column(
width = 3,
wellPanel(
h3("Filter criteria"),
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selectInput(
"species",
"Species to include",
choices = list(
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"Replicatively aging" = "replicative",
"All qualified" = "all"
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)
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)
),
wellPanel(
h3("Ranking"),
sliderInput(
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"clusteriness",
"Clustering of genes",
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post = "%",
min = 0,
max = 100,
step = 1,
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value = 58
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),
sliderInput(
"correlation",
"Correlation with known genes",
post = "%",
min = 0,
max = 100,
step = 1,
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value = 36
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),
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sliderInput(
"neural",
"Assessment by neural network",
post = "%",
min = 0,
max = 100,
step = 1,
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value = 6
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),
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sliderInput(
"cutoff",
"Cut-off score",
post = "%",
min = 0,
max = 100,
step = 1,
value = 50
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)
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),
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wellPanel(
h3("Results"),
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textOutput("synposis"),
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div(
style = "overflow-x: auto; overflow-y: auto; margin-top: 16px",
DTOutput("genes")
)
)
),
column(
width = 8,
wellPanel(
h3("Gene positions"),
p("This plot shows the selected genes' distance to the telomeres \
across species. It visualizes how certain genes have \
evolutionary conserved positions."),
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div(
style = "overflow-x: auto",
div(
style = "min-width: 1400px",
plotOutput(
"scatter",
width = "100%",
height = "600px"
)
)
)
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),
wellPanel(
h3("Gene set enrichment analysis"),
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checkboxInput(
"enable_gost",
"Perform a gene set enrichment analysis on the filtered result \
genes."
),
conditionalPanel(
"input.enable_gost == true",
plotlyOutput(
"gost",
width = "100%",
height = "600px"
)
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)
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)
)
)