Skip to content
GitLab
Projects
Groups
Snippets
/
Help
Help
Support
Community forum
Keyboard shortcuts
?
Submit feedback
Contribute to GitLab
Sign in
Toggle navigation
Menu
🚀
This server has been upgraded to GitLab release
15.7
.
🚀
Open sidebar
pertz-lab
shiny-timecourse-inspector
Commits
c78bb2e3
Commit
c78bb2e3
authored
Sep 24, 2019
by
dmattek
Browse files
Added tooltips for normalisation section
parent
82458782
Changes
2
Hide whitespace changes
Inline
Side-by-side
modules/auxfunc.R
View file @
c78bb2e3
...
...
@@ -165,9 +165,13 @@ help.text.short = c(
'Select columns to group data according to treatment, condition, etc.'
,
'Select math operation to perform on a single or two columns,'
,
'Select range of time for further processing.'
,
'
Normalise time series
to
a
selected
regio
n.'
,
'
Divide measurments by the mean/median or calculate z-score with respect
to selected
time spa
n.'
,
'Download time series after modification in this section.'
,
'Long format: a row is a single data point. Wide format: a row contains entire time series with columns as time points.'
'Long format: a row is a single data point. Wide format: a row is a time series with columns as time points.'
,
'Fold-change or z-score with respect to selected time span.'
,
'Normalise with respect to this time span.'
,
'Calculate fold-change and z-score using the median and Median Absolute Deviation, instead of the mean and sd.'
,
'Normalise to mean/median of selected time calculated globally, per group, or for individual time series.'
)
# Functions for data processing ----
...
...
server.R
View file @
c78bb2e3
...
...
@@ -327,19 +327,28 @@ shinyServer(function(input, output, session) {
})
# UI-side-panel-normalization ----
# select normalisation method
# - fold-change calculates fold change with respect to the mean
# - z-score calculates z-score of the selected regione of the time series
output
$
uiChBnorm
=
renderUI
({
if
(
DEB
)
cat
(
file
=
stdout
(),
'server:uiChBnorm\n'
)
if
(
input
$
chBnorm
)
{
tagList
(
radioButtons
(
'rBnormMeth'
,
label
=
'Select method'
,
choices
=
list
(
'fold-change'
=
'mean'
,
'z-score'
=
'z.score'
)
choices
=
list
(
'fold-change'
=
'mean'
,
'z-score'
=
'z.score'
),
width
=
"40%"
),
bsTooltip
(
'rBnormMeth'
,
help.text.short
[
11
],
placement
=
"right"
,
trigger
=
"hover"
,
options
=
NULL
)
)
}
})
# select the region of the time series for normalisation
output
$
uiSlNorm
=
renderUI
({
if
(
DEB
)
cat
(
file
=
stdout
(),
'server:uiSlNorm\n'
)
...
...
@@ -353,36 +362,49 @@ shinyServer(function(input, output, session) {
locRTmin
=
min
(
locTpts
)
locRTmax
=
max
(
locTpts
)
tagList
(
sliderInput
(
'slNormRtMinMax'
,
label
=
'Time
range for norm.
'
,
label
=
'Time
span
'
,
min
=
locRTmin
,
max
=
locRTmax
,
value
=
c
(
locRTmin
,
0.1
*
locRTmax
),
step
=
1
),
bsTooltip
(
'slNormRtMinMax'
,
help.text.short
[
12
],
placement
=
"right"
,
trigger
=
"hover"
,
options
=
NULL
)
)
}
})
# use robust stats (median instead of mean, mad instead of sd)
output
$
uiChBnormRobust
=
renderUI
({
if
(
DEB
)
cat
(
file
=
stdout
(),
'server:uiChBnormRobust\n'
)
if
(
input
$
chBnorm
)
{
tagList
(
checkboxInput
(
'chBnormRobust'
,
label
=
'Robust stats'
,
FALSE
)
FALSE
,
width
=
"40%"
),
bsTooltip
(
'chBnormRobust'
,
help.text.short
[
13
],
placement
=
"right"
,
trigger
=
"hover"
,
options
=
NULL
)
)
}
})
# choose whether normalisation should be calculated for the entire dataset, group, or trajectory
output
$
uiChBnormGroup
=
renderUI
({
if
(
DEB
)
cat
(
file
=
stdout
(),
'server:uiChBnormGroup\n'
)
if
(
input
$
chBnorm
)
{
tagList
(
radioButtons
(
'chBnormGroup'
,
label
=
'Normalisation grouping'
,
choices
=
list
(
'Entire dataset'
=
'none'
,
'Per facet'
=
'group'
,
'Per trajectory'
=
'id'
))
choices
=
list
(
'Entire dataset'
=
'none'
,
'Per group'
=
'group'
,
'Per trajectory'
=
'id'
),
width
=
"40%"
),
bsTooltip
(
'chBnormGroup'
,
help.text.short
[
14
],
placement
=
"right"
,
trigger
=
"hover"
,
options
=
NULL
)
)
}
})
...
...
Write
Preview
Supports
Markdown
0%
Try again
or
attach a new file
.
Cancel
You are about to add
0
people
to the discussion. Proceed with caution.
Finish editing this message first!
Cancel
Please
register
or
sign in
to comment