-
Notifications
You must be signed in to change notification settings - Fork 6
/
Copy pathui.R
executable file
·291 lines (279 loc) · 17.6 KB
/
ui.R
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
#
# This is the user-interface definition of a Shiny web application. You can
# run the application by clicking 'Run App' above.
#
# Find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com/
#
# add for testing
#
#Melanoma was sox10 in the study for tumor stroma
#nicks plotly sort
ui = dashboardPage(
dashboardHeader(title = "iTIME"),
dashboardSidebar(
sidebarMenu(
menuItem("Importing Data", tabName = 'import', icon = icon('upload')),
menuItem("Univariate Summary", tabName = 'univariate', icon = icon('angle-right')),
menuItem("Multivariate Summary", tabName = 'multivariate', icon = icon('angle-double-right')),
menuItem("Spatial", tabName = 'spatial', icon = icon('braille')),
menuItem("About", tabName = 'about', icon = icon('glasses')),
tags$br(),
fluidRow(column(12, align="center",
tags$br(),
tags$img(src = "moffitt-logo.png",
position = "absolute",
bottom = "25px",
width = "100px",
height = "100px")
)
)
)
),
dashboardBody(
custom_blue,
tabItems(
tabItem(tabName = 'import',
h1("iTIME", align="center"),
fluidRow(
box(width = 12, status = "primary",
fluidRow(
column(width = 8,
uiOutput("getting_started"),
),
column(width = 4,
fluidRow(
column(
width = 12,
div(style="float:right", actionButton("exampleData", "Load Example Data"))
)
),
fileInput("summaryData", "Choose a Summary File",
multiple = FALSE,
accept = c("csv",
"HALO summary data file",
c(".csv"))),
uiOutput("choose_summary_merge"),
#div(style = 'overflow-x: scroll; overflow-y: scroll; height:200px', tableOutput('summary_preview')),
fileInput("clinicalData", "Choose a Clinical Data File",
multiple = FALSE,
accept = c("csv",
"HALO summary data file",
c(".csv"))),
uiOutput("choose_clinical_merge"),
#div(style = 'overflow-x: scroll; overflow-y: scroll; height:200px', tableOutput('clinical_preview')),
fileInput("spatialData", "Choose a Spatial Data File",
multiple = FALSE,
accept = c("csv",
"HALO summary data file",
c(".csv"))),
#div(style = 'overflow-x: scroll; overflow-y: scroll; height:200px', tableOutput('spatial_preview'))
),
),
fluidRow(
column(width = 6),
column(width = 6, h2("", style = "font-size:12pt;font-weight:bold;margin-bottom:1.55em"),
),style = "height:118px"
),
),
),
),
tabItem(tabName = 'univariate',
h1("Univariate Summary and Visualization", align="center"),
fluidRow(
box(status = "primary", width = 12,
column(h2("Select Variables",align="center", style = "font-size:14pt"), status = "primary",
width = 3,
uiOutput("choose_marker"),
selectInput("choose_cont_thresh", "Select Contingency Threshold",
choices = c("1%" = 1,
"2%" = 2,
"3%" = 3,
"4%" = 4,
"5%" = 5),
selected = 1),
uiOutput("choose_clinical"),
selectInput("summaryPlotType", "Select Plot Type",
choices = c("Boxplot" = 1,
"Violin Plot" = 2,
"Histogram" = 3,
"Scatter Plot" = 4,
"Stacked Bar Plot" = 5),
selected = 1),
selectInput("summaryPlotColors", "Select Color Scheme",
choices = c("Magma" = "magma",
"Viridis" = "viridis",
"Plasma" = "plasma",
"Inferno" = "inferno"),
selected = "viridis"),
selectInput("uni_transformation", "Select Transformation",
choices = c("None" = "none",
"Square Root" = "sqrt_transform"
,
#"Log 2 Tranformation (0.0001)" = "log2_transform",
"Logit Tranformation (0.0001)" = "logit_transform"
)
)
),
column(width = 9,
column(width = 7,h2("Summary Plot",align="center", style = "font-size:14pt"),
plotOutput("boxplot", height = 520),
downloadButton('download_boxplot', "Download Plot"),
),
column(width = 5, align = "center", h2("Contingency Table",align="center", style = "font-size:14pt"),
div(style = 'overflow-x: scroll; overflow-y: scroll', tableOutput('contTable')),
column(width = 12, align = "center", h2("Frequency Table",align="center", style = "font-size:14pt"),
div(style = 'overflow-x: scroll; overflow-y: scroll', tableOutput('freqTable')),
column(width = 12, h2("Summary Table",align="center", style = "font-size:14pt"),
div(style = 'overflow-x: scroll; overflow-y: scroll', tableOutput('summaryTable'))
)
),
)
),
)
),
fluidRow(
box(width = 12, status = 'primary', title = textOutput("selectedModelName"),
column(width = 4,
column(width = 12,
h2("Modeling Variables",align="center", style = "font-size:14pt"),
uiOutput("choose_total_cells"),
selectInput("clinicalClass", "Select Clinical Variable Class",
choices = c("Numeric" = "numeric",
"Factor" = "factor"),
selected = "factor"),
uiOutput("modeling_reference")),
column(width = 12,
uiOutput("choose_uni_covariates"))
),
column(width = 8,
# column(width = 12, h2("Cumulative Distribution Function (CDF)", align="center", style = "font-size:14pt"),
# status = "primary",
# plotOutput("cdfplot"),
# downloadButton('download_cdfplot', 'Download Plot')),
column(width = 12, align = "center", h2("Beta Binomial Model Statistics",align="center", style = "font-size:14pt"),
div(style = 'overflow-x: scroll', tableOutput('model_stats'))),
column(width = 12,
# selectInput("selectedModel", "Select Desired Model",
# choices = c("Poisson",
# "Negative Binomial",
# "Zero Inflated Binomial",
# "Binomial",
# "Beta Binomial",
# "Zero Inflated Poisson"),
# selected = "Beta Binomial")
htmlOutput("modelingDescription"))
),
# column(width = 4, align = "center",
# h2("Akaike Information Criterion (AIC)",align="center", style = "font-size:14pt"),
# h2("Lower indicates a better model fit...",align="center", style = "font-size:10pt"),
# div(style = 'overflow-x: scroll', tableOutput('aic_table')))#height:120px; ; overflow-y: scroll
)
),
fluidRow(
box(width = 12, status = "primary",
downloadButton(
outputId = "univariate_report",
label = "Download Univariate Report"
),
# checkboxInput(
# "printFunctions",
# "Print Functions in Report?",
# value=F
# ),
HTML('<footer>
For access to the code used to produce plots and analyses, please visit <a href = "https://github.com/FridleyLab/iTIME">Fridley Lab GitHub</a>.
</footer>')
)
)
),
tabItem(tabName='multivariate',
h1("Multivariate Summary and Visualization", align="center"),
fluidRow(
box(width = 12, status = "primary",
column(width = 3,
uiOutput("choose_heatmap_clinical"),
selectInput("heatmap_transform", "Select Transformation Method",
choices=c("None" = "none",
"Square Root" = "square_root"),
selected="square_root"),
awesomeCheckbox("cluster_heatmap_annotation", "Group Annotation",
value = TRUE),
awesomeCheckbox("cluster_heatmap_Marker", "Cluster by Marker",
value = TRUE),
uiOutput("choose_heatmap_marker"),
tags$style("awesome-checkbox-group-custom {background-color: #2cdeeb;}"),
),
column(width = 9,
column(width = 6, h2("Heatmap", align="center", style = "font-size:14pt"),
plotOutput("heatmap", width="100%"),#height = 510
downloadButton('download_heatmap', "Download Heatmap"),
),
column(width = 6, h2("Principal Component Analysis (PCA)", align="center", style = "font-size:14pt"),
plotOutput("pca", width="100%"),
downloadButton("download_pca", "Download PCA Plot", style = "margin-bottom:25px")
)
)
),
),
),
tabItem(tabName = 'spatial',
h1("Spatial Summary", align="center"),
box(width = 12, status = "primary",
column(width = 4, h2("Spatial Plot Selections", style = "font-size:14pt"),
uiOutput("choosePlotlyMarkers")),
column(width = 8, h2("Spatial Plot", align="center",style = "font-size:14pt"),
plotlyOutput("spatial_plotly", width = "85%", height = "575"),
#downloadButton('download_spatialPlotly', 'Download Plot')
)
),
box(width = 12, status = "primary",
column(width = 4, h2("Spatial Plot Selections", style = "font-size:14pt"),
uiOutput("choose_ripley")
,selectInput("ripleysEstimator", "Select an Estimator",
choices = c("Ripley's K" = "K",
#"Besag's L" = "L",
#"Marcon's M" = "M",
"Nearest Neighbor G" = "G"),
selected = "K")
),
column(width = 8, h2("Spatial Plot", align="center", style = "font-size:14pt"),
plotOutput("ripleysPlot", height = 350),
downloadButton('download_ripley', 'Download Plot')
)
),
HTML('<footer>
In cases of large holes or uneven cell distributions, the theoretical estimate of complete spatial randomness (CSR) may be an inaccurate measure.
</footer>')
),
tabItem(tabName = 'about',
h1("About iTIME", align="center"),
fluidRow(
box(width = 9, status = "primary",
uiOutput('aboutitime'),
),
box(title = "Development Team",
width = 3, status = "primary",
p("- Brooke Fridley"),
p("- Alex Soupir"),
p("- Chris Wilson"),
p("- Jordan Creed"),
p("- Oscar Ospina"),
p("- Gregory Kimmel"),
p("- Joseph Markowitz"),
p("- Christelle Colin Leitzinger"),
p("- Nick Chakiryan"),
br(),
p("For more information about our lab and other projects please check",
"out our website at",
a("https://lab.moffitt.org/fridley/", href = "https://lab.moffitt.org/fridley/")),
br(),
p("All code for this project are publically available on",
a("GitHub.", href = "https://github.com/FridleyLab/iTIME"))
)
)
)
)
)
)