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Amine GHOZLANE
shaman
Commits
a9956d3a
Commit
a9956d3a
authored
Oct 20, 2016
by
svolant
Browse files
bug biom+tree abundance
parent
23fa289e
Changes
5
Hide whitespace changes
Inline
Side-by-side
Rfunctions/Data_Management.R
View file @
a9956d3a
...
...
@@ -47,8 +47,6 @@ read_rdp <- function(filename, threshold_annot)
## Check the format of the counts table
CheckCountsTable
<-
function
(
counts
)
{
...
...
@@ -165,13 +163,15 @@ GetCountsMerge <- function(input,dataInput,taxoSelect,target,design)
CT_noNorm
=
NULL
normFactors
=
NULL
FeatureSize
=
NULL
CT_Norm
=
NULL
## Counts and taxo tables
CT
=
dataInput
$
counts
taxo
=
dataInput
$
taxo
# save(CT,target,taxo,file="testMerge.RData")
## Select cols in the target
labels
=
target
[,
1
]
labels
=
rownames
(
target
)
ind
=
which
(
colnames
(
CT
)
%in%
labels
)
## Get the normalization variable (normalization can be done according to this variable)
...
...
@@ -200,10 +200,10 @@ GetCountsMerge <- function(input,dataInput,taxoSelect,target,design)
CT
=
OrderCounts
(
counts
=
CT
,
labels
=
labels
)
$
CountsOrder
CT_noNorm
=
CT
RowProd
=
sum
(
apply
(
CT_noNorm
,
1
,
prod
))
## Create the dds object
dds
<-
DESeqDataSetFromMatrix
(
countData
=
CT
,
colData
=
target
,
design
=
design
)
dds
<-
DESeqDataSetFromMatrix
(
countData
=
CT
,
colData
=
target
,
design
=
design
,
ignoreRank
=
TRUE
)
save
(
dds
,
file
=
"testdds.RData"
)
if
(
is.null
(
VarNorm
)){
## Counts normalisation
## Normalisation with or without 0
...
...
@@ -225,7 +225,7 @@ GetCountsMerge <- function(input,dataInput,taxoSelect,target,design)
CT_tmp
=
CT
[,
indgrp
]
CT_tmp
=
removeNulCounts
(
CT_tmp
)
target_tmp
=
data.frame
(
labels
=
rownames
(
target
)[
indgrp
])
dds_tmp
<-
DESeqDataSetFromMatrix
(
countData
=
CT_tmp
,
colData
=
target_tmp
,
design
=~
labels
)
dds_tmp
<-
DESeqDataSetFromMatrix
(
countData
=
CT_tmp
,
colData
=
target_tmp
,
design
=~
labels
,
ignoreRank
=
TRUE
)
if
(
input
$
AccountForNA
==
"NonNull"
)
{
dds_tmp
=
estimateSizeFactors
(
dds_tmp
,
locfunc
=
eval
(
as.name
(
input
$
locfunc
)),
geoMeans
=
GeoMeansCT
(
CT_tmp
));
normFactors
[
indgrp
]
=
sizeFactors
(
dds_tmp
)}
if
(
input
$
AccountForNA
==
"All"
)
{
dds_tmp
=
estimateSizeFactors
(
dds_tmp
,
locfunc
=
eval
(
as.name
(
input
$
locfunc
)));
normFactors
[
indgrp
]
=
sizeFactors
(
dds_tmp
)}
if
(
input
$
AccountForNA
==
"Weighted"
&&
input
$
AccountForNA
!=
"NonNull"
)
{
dds_tmp
=
estimateSizeFactors
(
dds_tmp
,
locfunc
=
eval
(
as.name
(
input
$
locfunc
)),
geoMeans
=
GeoMeansCT
(
CT_tmp
));
normFactors
[
indgrp
]
=
w.sizefactor
(
CT_tmp
)}
...
...
@@ -247,9 +247,13 @@ GetCountsMerge <- function(input,dataInput,taxoSelect,target,design)
# Only interesting OTU
# merged_table = merge(CT, taxo[order(rownames(CT)),], by="row.names")
save
(
CT
,
taxo
,
file
=
"testMerge.RData"
)
merged_table
=
merge
(
CT
,
taxo
,
by
=
"row.names"
)
## Why ??
CT
=
merged_table
[,
2
:
(
dim
(
CT
)[
2
]
+1
)]
taxo
=
merged_table
[,(
dim
(
CT
)[
2
]
+2
)
:
dim
(
merged_table
)[
2
]]
## ???
rownames
(
CT
)
=
merged_table
[,
1
]
rownames
(
taxo
)
=
merged_table
[,
1
]
#ordOTU = order(rownames(taxo))
...
...
@@ -258,9 +262,9 @@ GetCountsMerge <- function(input,dataInput,taxoSelect,target,design)
# indOTU_annot = which(rownames(CT)%in%rownames(taxo))
# counts_annot = CT[indOTU_annot[ordOTU],]
## Aggregate matrix
if
(
taxoSelect
==
"OTU/Gene"
||
input
$
FileFormat
==
"fileBiom"
)
counts
=
counts_annot
if
(
taxoSelect
==
"OTU/Gene"
)
counts
=
counts_annot
else
{
if
(
input
$
TypeTable
==
"MGS"
){
if
(
input
$
TypeTable
==
"MGS"
&&
input
$
FileFormat
!=
"fileBiom"
){
taxoS
=
taxo
[,
input
$
TypeTable
]
counts
=
aggregate
(
counts_annot
,
by
=
list
(
Taxonomy
=
taxoS
),
mean
)
rownames
(
counts
)
=
counts
[,
1
]
...
...
@@ -270,7 +274,7 @@ GetCountsMerge <- function(input,dataInput,taxoSelect,target,design)
colnames
(
counts_int
)
=
colnames
(
counts
)
counts
=
counts_int
}
if
(
taxoSelect
!=
"MGS"
){
if
(
taxoSelect
!=
"MGS"
||
input
$
FileFormat
==
"fileBiom"
){
#taxoS = taxo[ordOTU,taxoSelect]
taxoS
=
taxo
[,
taxoSelect
]
counts
=
aggregate
(
counts_annot
,
by
=
list
(
Taxonomy
=
taxoS
),
sum
)
...
...
@@ -528,6 +532,7 @@ plot_filter <- function(counts,th.samp,th.abund,type="Scatter")
SelectThreshAb
<-
function
(
infile
,
lambda
=
500
,
graph
=
TRUE
){
rs
<-
rowSums
(
infile
)
lambda
=
max
(
rs
)
test_Filtre
<-
sapply
(
c
(
min
(
rs
)
:
lambda
),
FUN
=
function
(
x
)
table
(
rs
>
x
))
x
<-
c
(
min
(
rs
)
:
lambda
)
reslm
<-
lm
(
test_Filtre
[
1
,]
~
x
)
$
coefficients
...
...
Rfunctions/Stat_Model.R
View file @
a9956d3a
...
...
@@ -33,7 +33,9 @@ GetInteraction2 <- function(target)
## Get the dds object of DESeq2
Get_dds_object
<-
function
(
input
,
counts
,
target
,
design
,
normFactorsOTU
,
CT_noNorm
,
CT_Norm
)
{
dds
<-
DESeqDataSetFromMatrix
(
countData
=
counts
,
colData
=
target
,
design
=
design
)
dds
<-
DESeqDataSetFromMatrix
(
countData
=
counts
,
colData
=
target
,
design
=
design
,
ignoreRank
=
TRUE
)
sizeFactors
(
dds
)
=
normFactorsOTU
dds
<-
estimateDispersions
(
dds
,
fitType
=
input
$
fitType
)
if
(
as.numeric
(
R.Version
()
$
major
)
>=
3
&&
as.numeric
(
R.Version
()
$
minor
)
>=
1.3
){
...
...
Rfunctions/VisuPlot.R
View file @
a9956d3a
...
...
@@ -529,7 +529,7 @@ GetDataToPlot <- function(input,resDiff,VarInt,ind_taxo,aggregate=TRUE,rarefy=FA
## Create the variable to plot
targetInt
=
as.data.frame
(
target
[,
VarInt
])
rownames
(
targetInt
)
=
target
[,
1
]
rownames
(
targetInt
)
=
rownames
(
target
)
## Combining the Varint
if
(
length
(
VarInt
)
>
1
){
targetInt
$
AllVar
=
apply
(
targetInt
,
1
,
paste
,
collapse
=
"-"
);
targetInt
$
AllVar
=
factor
(
targetInt
$
AllVar
,
levels
=
expand.grid2.list
(
list.val
))}
if
(
length
(
VarInt
)
<=
1
){
targetInt
$
AllVar
=
target
[,
VarInt
];
targetInt
$
AllVar
=
factor
(
targetInt
$
AllVar
,
levels
=
val
)}
...
...
@@ -586,4 +586,126 @@ GetDataToPlot <- function(input,resDiff,VarInt,ind_taxo,aggregate=TRUE,rarefy=FA
}
## Create the data table for the tree representation
CreateTableTree
<-
function
(
input
,
resDiff
,
CT_Norm_OTU
,
taxo_table
,
VarInt
,
ind_taxo
=
rownames
(
CT_Norm_OTU
))
{
dds
=
resDiff
$
dds
val
=
c
()
list.val
=
list
()
counts
=
CT_Norm_OTU
target
=
resDiff
$
target
counts_tmp_combined
=
NULL
prop_tmp_combined
=
NULL
targetInt
=
NULL
namesCounts
=
NULL
levelsMod
=
NULL
## Select a subset within the taxonomy level (default is the 12 most abundant)
nbKept
=
length
(
ind_taxo
)
Taxonomy
=
rownames
(
counts
)
if
(
length
(
VarInt
)
>
0
&&
nbKept
>
0
)
{
## Get the modalities to keep
for
(
i
in
1
:
length
(
VarInt
))
{
## Replace "-" by "."
target
[,
VarInt
[
i
]]
=
gsub
(
"-"
,
"."
,
target
[,
VarInt
[
i
]])
Tinput
=
paste
(
"input$"
,
"ModVisu"
,
VarInt
[
i
],
sep
=
""
)
expr
=
parse
(
text
=
Tinput
)
## All the modalities for all the var of interest
val
=
c
(
val
,
eval
(
expr
))
list.val
[[
i
]]
=
eval
(
expr
)
}
if
(
!
is.null
(
val
)
&&
!
is.null
(
list.val
))
{
## Create the variable to plot
targetInt
=
as.data.frame
(
target
[,
VarInt
])
rownames
(
targetInt
)
=
rownames
(
target
)
## Combining the Varint
if
(
length
(
VarInt
)
>
1
){
targetInt
$
AllVar
=
apply
(
targetInt
,
1
,
paste
,
collapse
=
"-"
);
targetInt
$
AllVar
=
factor
(
targetInt
$
AllVar
,
levels
=
expand.grid2.list
(
list.val
))}
if
(
length
(
VarInt
)
<=
1
){
targetInt
$
AllVar
=
target
[,
VarInt
];
targetInt
$
AllVar
=
factor
(
targetInt
$
AllVar
,
levels
=
val
)}
colnames
(
targetInt
)
=
c
(
VarInt
,
"AllVar"
)
## Keep only the selected modalities
ind_kept
=
which
(
!
is.na
(
targetInt
$
AllVar
))
targetInt
=
targetInt
[
ind_kept
,]
levelsMod
=
levels
(
targetInt
$
AllVar
)
## Create the counts matrix only for the selected subset
counts_tmp
=
counts
[
Taxonomy
%in%
ind_taxo
,]
counts_tmp
=
counts_tmp
[,
colnames
(
counts_tmp
)
%in%
rownames
(
targetInt
)]
## Be careful transposition !
if
(
nrow
(
counts_tmp
)
>
0
&&
nrow
(
targetInt
)
>
0
)
{
counts_tmp_combined
=
aggregate
(
t
(
counts_tmp
),
by
=
list
(
targetInt
$
AllVar
),
mean
)
rownames
(
counts_tmp_combined
)
=
counts_tmp_combined
$
Group.1
namesCounts
=
counts_tmp_combined
$
Group.1
counts_tmp_combined
=
as.matrix
(
counts_tmp_combined
[,
-1
])
}
## Ordering the counts
if
(
!
is.null
(
counts_tmp_combined
))
{
MeanCounts
=
apply
(
counts_tmp_combined
,
2
,
mean
)
ord
=
order
(
MeanCounts
,
decreasing
=
TRUE
)
counts_tmp_combined
=
as.matrix
(
counts_tmp_combined
[,
ord
])
}
}
}
return
(
list
(
counts
=
counts_tmp_combined
,
targetInt
=
targetInt
,
namesCounts
=
namesCounts
,
levelsMod
=
levelsMod
))
}
###########################
## Tree
###########################
## The count matrix must be given at the leaf level.
Plot_Visu_Tree
<-
function
(
input
,
resDiff
,
CT_Norm_OTU
,
taxo_table
)
{
res
=
NULL
## Get Input for BarPlot
VarInt
=
input
$
VisuVarInt
ind_taxo
=
input
$
selectTaxoPlot
## Removed column with only 1 modality
ind
=
which
(
apply
(
taxo_table
,
2
,
FUN
=
function
(
x
)
length
(
unique
(
x
[
!
is.na
(
x
)])))
==
1
)
if
(
length
(
ind
)
>
0
)
taxo_table
=
taxo_table
[,
-
ind
]
# tmp_combined = GetDataToPlot(input,resDiff,VarInt,ind_taxo,CT_Norm_OTU=CT_Norm_OTU)
if
(
nrow
(
CT_Norm_OTU
)
>
0
&&
!
is.null
(
CT_Norm_OTU
)
&&
nrow
(
taxo_table
)
>
0
&&
!
is.null
(
taxo_table
))
{
tmp
=
CreateTableTree
(
input
,
resDiff
,
CT_Norm_OTU
,
taxo_table
,
VarInt
)
if
(
nrow
(
tmp
$
counts
)
>
0
&&
!
is.null
(
tmp
$
counts
))
{
merge_dat
=
merge
(
taxo_table
,
round
(
t
(
tmp
$
counts
)),
by
=
"row.names"
)
colnames
(
merge_dat
)[
1
]
=
"OTU"
levels
<-
c
(
"OTU"
,
colnames
(
taxo_table
))
conditions
<-
rownames
(
tmp
$
counts
)
nodeFind
=
input
$
TaxoTree
if
(
input
$
TaxoTree
==
"..."
)
nodeFind
=
NULL
res
=
treeWeightD3
(
merge_dat
,
conditions
,
levels
,
nodeFind
=
nodeFind
,
height
=
input
$
heightVisu
+10
)
}
}
return
(
res
)
}
server.R
View file @
a9956d3a
source
(
'LoadPackages.R'
)
library
(
plotly
)
library
(
treeWeightD3
)
shinyServer
(
function
(
input
,
output
,
session
)
{
hide
(
id
=
"loading-content"
,
anim
=
TRUE
,
animType
=
"fade"
,
time
=
1.5
)
...
...
@@ -471,18 +471,26 @@ shinyServer(function(input, output,session) {
data
=
read.csv
(
inFile
$
datapath
,
sep
=
input
$
septarget
,
header
=
TRUE
)
data
=
as.data.frame
(
data
)
names
=
colnames
(
data
)
## Change the rownames
rownames
(
data
)
<-
as.character
(
data
[,
1
])
## Keep only the row which are in the count table
ind
=
which
(
rownames
(
data
)
%in%
colnames
(
counts
))
data
=
as.data.frame
(
data
[
ind
,])
colnames
(
data
)
=
names
## Replace "-" by "."
ind_num
=
which
(
sapply
(
data
,
is.numeric
))
ind_num
=
which
(
sapply
(
as.
data
.frame
(
data
[,
-1
])
,
is.numeric
))
+
1
if
(
length
(
ind_num
)
>
0
){
data_tmp
=
cbind
(
as.data.frame
(
apply
(
data
[,
-
ind_num
],
2
,
gsub
,
pattern
=
"-"
,
replacement
=
"."
)),
data
[,
ind_num
])
data_tmp
=
cbind
(
as.data.frame
(
apply
(
as.data.frame
(
data
[,
-
ind_num
]
)
,
2
,
gsub
,
pattern
=
"-"
,
replacement
=
"."
)),
data
[,
ind_num
])
colnames
(
data_tmp
)
=
c
(
colnames
(
data
)[
-
ind_num
],
colnames
(
data
)[
ind_num
])
data
=
data_tmp
}
if
(
length
(
ind_num
)
==
0
){
data
=
as.data.frame
(
apply
(
data
,
2
,
gsub
,
pattern
=
"-"
,
replacement
=
"."
))}
rownames
(
data
)
<-
as.character
(
data
[,
1
])
ind
=
which
(
rownames
(
data
)
%in%
colnames
(
counts
))
target
=
data
[
ind
,]
target
=
data
# target = as.data.frame(apply(target,2,gsub,pattern = "-",replacement = "."))
...
...
@@ -1071,6 +1079,7 @@ shinyServer(function(input, output,session) {
counts
=
dMC
$
counts
CT_noNorm
=
dMC
$
CT_noNorm
CT_Norm
=
dMC
$
CT_Norm
## If no file, size factors are estimated
normFactors
=
SizeFactors_fromFile
()
$
normFactors
...
...
@@ -1508,6 +1517,16 @@ shinyServer(function(input, output,session) {
##
#####################################################
output
$
PlotVisuTree
<-
renderTreeWeightD3
({
resDiff
=
ResDiffAnal
()
taxo_table
=
dataInput
()
$
data
$
taxo
CT_Norm_OTU
=
dataMergeCounts
()
$
CT_Norm
res
=
NULL
if
(
!
is.null
(
resDiff
$
dds
)
&&
length
(
input
$
VisuVarInt
)
>=
1
)
res
=
Plot_Visu_Tree
(
input
,
resDiff
,
CT_Norm_OTU
,
taxo_table
)
return
(
res
)
})
output
$
PlotVisuBar
<-
renderChart
({
resDiff
=
ResDiffAnal
()
...
...
@@ -1699,8 +1718,10 @@ shinyServer(function(input, output,session) {
if
(
input
$
PlotVisuSelect
==
"Barplot"
)
res
=
showOutput
(
"PlotVisuBar"
)
if
(
input
$
PlotVisuSelect
==
"Heatmap"
)
res
=
d3heatmapOutput
(
"heatmap"
,
height
=
input
$
heightVisu
+10
)
if
(
input
$
PlotVisuSelect
==
"Boxplot"
)
res
=
plotOutput
(
"Boxplot"
,
height
=
input
$
heightVisu
+10
)
if
(
input
$
PlotVisuSelect
==
"Tree"
)
res
=
treeWeightD3Output
(
'PlotVisuTree'
,
height
=
input
$
heightVisu
+10
,
width
=
"100%"
)
if
(
input
$
PlotVisuSelect
==
"Scatterplot"
&&
!
input
$
AddRegScatter
)
res
=
scatterD3Output
(
"ScatterplotD3"
,
height
=
input
$
heightVisu
+10
)
if
(
input
$
PlotVisuSelect
==
"Scatterplot"
&&
input
$
AddRegScatter
)
res
=
plotOutput
(
"Scatterplotgg"
,
height
=
input
$
heightVisu
+10
)
if
(
input
$
PlotVisuSelect
==
"Diversity"
)
res
=
plotOutput
(
"DiversityPlot"
,
height
=
input
$
heightVisu
+10
)
if
(
input
$
PlotVisuSelect
==
"Rarefaction"
)
res
=
plotOutput
(
"RarefactionPlot"
,
dblclick
=
"RarefactionPlot_dblclick"
,
brush
=
brushOpts
(
id
=
"RarefactionPlot_brush"
,
resetOnNew
=
TRUE
),
height
=
input
$
heightVisu
+10
)
return
(
res
)
...
...
@@ -1941,6 +1962,28 @@ shinyServer(function(input, output,session) {
})
output
$
VarIntVisuTree
<-
renderUI
({
target
=
dataInputTarget
()
$
target
data
=
dataInput
()
$
data
taxo
=
input
$
TaxoSelect
resDiff
=
ResDiffAnal
()
res
=
NULL
if
(
!
is.null
(
data
$
counts
)
&&
!
is.null
(
data
$
taxo
)
&&
nrow
(
data
$
counts
)
>
0
&&
nrow
(
data
$
taxo
)
>
0
&&
!
is.null
(
taxo
)
&&
taxo
!=
"..."
&&
!
is.null
(
target
))
{
counts
=
dataMergeCounts
()
$
counts
Available_x
=
sort
(
rownames
(
counts
))
res
=
selectizeInput
(
"TaxoTree"
,
h6
(
strong
(
paste
(
"Select a specific"
,
taxo
,
sep
=
" "
))),
c
(
"..."
,
Available_x
),
multiple
=
FALSE
)
}
return
(
res
)
})
#####################################################
##
## KRONA
...
...
@@ -1972,8 +2015,23 @@ shinyServer(function(input, output,session) {
## Disable the actionbutton if the number of feature is lower than 2
observe
({
input
$
TaxoSelect
testRank
=
FALSE
counts
=
dataMergeCounts
()
$
counts
InterVar
=
input
$
InterestVar
if
(
length
(
InterVar
)
>
0
)
{
design
=
GetDesign
(
input
)
target
=
dataInputTarget
()
$
target
modelMatrix
<-
model.matrix
(
design
,
data
=
as.data.frame
(
target
))
rk
=
qr
(
modelMatrix
)
$
rank
testRank
=
(
ncol
(
modelMatrix
)
==
rk
)
}
if
(
input
$
AddFilter
&&
!
is.null
(
input
$
SliderThSamp
)
&&
!
is.null
(
input
$
SliderThAb
))
{
ind.filter
=
Filtered_feature
(
counts
,
input
$
SliderThSamp
,
input
$
SliderThAb
)
$
ind
...
...
@@ -1984,13 +2042,14 @@ shinyServer(function(input, output,session) {
if
(
nrow
(
counts
)
>=
2
){
shinyjs
::
enable
(
"RunDESeq"
)
}
if
(
nrow
(
counts
)
<
2
)
{
if
(
nrow
(
counts
)
<
2
||
!
testRank
)
{
shinyjs
::
disable
(
"RunDESeq"
)
}
}
if
(
is.null
(
counts
))
{
if
(
is.null
(
counts
)
||
!
testRank
)
{
shinyjs
::
disable
(
"RunDESeq"
)
}
})
...
...
ui.R
View file @
a9956d3a
options
(
shiny.sanitize.errors
=
FALSE
)
source
(
"css/owncss.R"
)
source
(
"Rfunctions/Data_Management.R"
)
library
(
treeWeightD3
)
if
(
!
require
(
scatterD3
))
{
devtools
::
install_github
(
'aghozlane/scatterD3'
)
library
(
scatterD3
)
}
if
(
!
require
(
shinydashboard
)){
installed.packages
(
"shinydashboard"
)
library
(
shinydashboard
)
...
...
@@ -577,7 +582,7 @@ body <- dashboardBody(
column
(
width
=
3
,
box
(
title
=
"Select your plot"
,
width
=
NULL
,
status
=
"primary"
,
solidHeader
=
TRUE
,
collapsible
=
FALSE
,
collapsed
=
FALSE
,
selectizeInput
(
"PlotVisuSelect"
,
""
,
c
(
"Barplot"
=
"Barplot"
,
"Heatmap"
=
"Heatmap"
,
"Boxplot"
=
"Boxplot"
,
"Scatterplot"
=
"Scatterplot"
,
"Diversity"
=
"Diversity"
,
"Rarefaction"
=
"Rarefaction"
),
selected
=
"Barplot"
)
selectizeInput
(
"PlotVisuSelect"
,
""
,
c
(
"Barplot"
=
"Barplot"
,
"Heatmap"
=
"Heatmap"
,
"Boxplot"
=
"Boxplot"
,
"
Tree"
=
"Tree"
,
"
Scatterplot"
=
"Scatterplot"
,
"Diversity"
=
"Diversity"
,
"Rarefaction"
=
"Rarefaction"
),
selected
=
"Barplot"
)
),
...
...
@@ -592,6 +597,8 @@ body <- dashboardBody(
h5
(
strong
(
"Select the modalities"
)),
uiOutput
(
"ModVisu"
)
),
conditionalPanel
(
condition
=
"input.PlotVisuSelect=='Tree' "
,
uiOutput
(
"VarIntVisuTree"
)),
conditionalPanel
(
condition
=
"input.PlotVisuSelect=='Scatterplot' "
,
uiOutput
(
"VarIntVisuScatter"
),
radioButtons
(
"TransDataScatter"
,
"Data transformation"
,
c
(
"Log2 +1"
=
"log2"
,
"None"
=
"none"
),
inline
=
TRUE
),
...
...
@@ -599,14 +606,14 @@ body <- dashboardBody(
radioButtons
(
"CorMeth"
,
"Correlation method"
,
c
(
"Pearson"
=
"pearson"
,
"Spearman"
=
"spearman"
),
inline
=
TRUE
),
checkboxInput
(
"AddRegScatter"
,
"Add regression line"
,
FALSE
)
),
conditionalPanel
(
condition
=
"input.PlotVisuSelect!='Rarefaction' && input.PlotVisuSelect!='Diversity' && input.PlotVisuSelect!='Scatterplot'"
,
conditionalPanel
(
condition
=
"input.PlotVisuSelect!='Rarefaction' && input.PlotVisuSelect!='Diversity' && input.PlotVisuSelect!='Scatterplot'
&& input.PlotVisuSelect!='Tree'
"
,
radioButtons
(
"SelectSpecifTaxo"
,
"Select the features"
,
c
(
"Most abundant"
=
"Most"
,
"All"
=
"All"
,
"Differential features"
=
"Diff"
,
"Non differential features"
=
"NoDiff"
))
),
conditionalPanel
(
condition
=
"input.PlotVisuSelect!='Rarefaction' && input.PlotVisuSelect!='Diversity' && input.PlotVisuSelect!='Scatterplot' && (input.SelectSpecifTaxo=='Diff' || input.SelectSpecifTaxo=='NoDiff') "
,
conditionalPanel
(
condition
=
"input.PlotVisuSelect!='Rarefaction' && input.PlotVisuSelect!='Diversity' && input.PlotVisuSelect!='Scatterplot' &&
input.PlotVisuSelect!='Tree' &&
(input.SelectSpecifTaxo=='Diff' || input.SelectSpecifTaxo=='NoDiff') "
,
selectizeInput
(
"ContrastList_table_Visu"
,
""
,
choices
=
""
,
multiple
=
TRUE
),
radioButtons
(
"UnionInterContrasts"
,
"Union or intersection ?"
,
c
(
"Union"
=
"Union"
,
"Intersection"
=
"Inter"
),
inline
=
TRUE
)
),
conditionalPanel
(
condition
=
"input.PlotVisuSelect!='Rarefaction' && input.PlotVisuSelect!='Diversity' && input.PlotVisuSelect!='Scatterplot'"
,
conditionalPanel
(
condition
=
"input.PlotVisuSelect!='Rarefaction' && input.PlotVisuSelect!='Diversity' && input.PlotVisuSelect!='Scatterplot'
&& input.PlotVisuSelect!='Tree'
"
,
uiOutput
(
"TaxoToPlotVisu"
)
),
...
...
@@ -700,7 +707,7 @@ body <- dashboardBody(
##################
## ALL
##################
conditionalPanel
(
condition
=
"input.PlotVisuSelect!='Rarefaction' && input.PlotVisuSelect!='Scatterplot'"
,
conditionalPanel
(
condition
=
"input.PlotVisuSelect!='Rarefaction' && input.PlotVisuSelect!='Scatterplot'
&& input.PlotVisuSelect!='Tree'
"
,
radioButtons
(
inputId
=
"SensPlotVisu"
,
label
=
h6
(
strong
(
"Orientation"
)),
choices
=
c
(
"Vertical"
=
"Vertical"
,
"Horizontal"
=
"Horizontal"
),
selected
=
"Vertical"
,
inline
=
TRUE
)
)
),
...
...
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