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Amine GHOZLANE
shaman
Commits
2b5bd3f5
Commit
2b5bd3f5
authored
Feb 08, 2017
by
Amine GHOZLANE
Browse files
Debug relative abundance and add KL and JSD distance
parent
aefbaef8
Changes
4
Hide whitespace changes
Inline
Side-by-side
LoadPackages.R
View file @
2b5bd3f5
...
...
@@ -149,6 +149,10 @@ if (!require(phytools)) {
library
(
phytools
)
}
if
(
!
require
(
philentropy
)){
devtools
::
install_github
(
"HajkD/philentropy"
,
build_vignettes
=
TRUE
,
dependencies
=
TRUE
)
library
(
philentropy
)
}
# if(!require(plotly)){
...
...
Rfunctions/DiagPlot.R
View file @
2b5bd3f5
...
...
@@ -411,9 +411,19 @@ PCoAPlot_meta <-function (input, dds, group_init, CT,tree,col = c("SpringGreen",
counts.norm
=
counts.norm
[,
ind_kept
]
# print(head(counts.norm))
## Get the distance
if
(
input
$
DistClust
!=
"sere"
&&
input
$
DistClust
!=
"Unifrac"
)
dist.counts.norm
=
vegdist
(
t
(
counts.norm
),
method
=
input
$
DistClust
)
if
(
input
$
DistClust
==
"sere"
)
dist.counts.norm
=
as.dist
(
SEREcoef
(
counts.norm
))
if
(
input
$
DistClust
==
"Unifrac"
)
else
if
(
input
$
DistClust
==
"jsd"
){
#dist_jsd = JSD(sweep(counts.norm,2,colSums(counts.norm)))
dist_jsd
=
JSD
(
t
(
sweep
(
counts.norm
,
2
,
colSums
(
counts.norm
),
`/`
)))
dist_jsd
[
is.na
(
dist_jsd
)]
=
0
dist.counts.norm
=
as.dist
(
dist_jsd
)
}
else
if
(
input
$
DistClust
==
"kl"
){
dist_kl
=
KL
(
t
(
sweep
(
counts.norm
,
2
,
colSums
(
counts.norm
),
`/`
)))
dist_kl
[
is.na
(
dist_kl
)]
=
0
dist.counts.norm
=
as.dist
(
dist_kl
)
}
else
if
(
input
$
DistClust
==
"Unifrac"
)
{
tmp
=
UniFracDist
(
CT
,
tree
)
if
(
is.null
(
tree
)
||
is.null
(
tmp
))
dist.counts.norm
=
NULL
...
...
@@ -427,7 +437,10 @@ PCoAPlot_meta <-function (input, dds, group_init, CT,tree,col = c("SpringGreen",
}
}
else
{
dist.counts.norm
=
vegdist
(
t
(
counts.norm
),
method
=
input
$
DistClust
)
}
if
(
!
is.null
(
dist.counts.norm
))
{
## Do PCoA
...
...
@@ -672,9 +685,18 @@ Get_pcoa_table <-function (input, dds, group_init,CT,tree)
counts.norm
=
counts.norm
[,
ind_kept
]
## Get the distance
if
(
input
$
DistClust
!=
"sere"
&&
input
$
DistClust
!=
"Unifrac"
)
dist.counts.norm
=
vegdist
(
t
(
counts.norm
),
method
=
input
$
DistClust
)
if
(
input
$
DistClust
==
"sere"
)
dist.counts.norm
=
as.dist
(
SEREcoef
(
counts.norm
))
if
(
input
$
DistClust
==
"Unifrac"
)
{
else
if
(
input
$
DistClust
==
"jsd"
){
dist_jsd
=
JSD
(
t
(
sweep
(
counts.norm
,
2
,
colSums
(
counts.norm
),
`/`
)))
dist_jsd
[
is.na
(
dist_jsd
)]
=
0.0
dist.counts.norm
=
as.dist
(
dist_jsd
)
}
else
if
(
input
$
DistClust
==
"kl"
){
dist_kl
=
KL
(
t
(
sweep
(
counts.norm
,
2
,
colSums
(
counts.norm
),
`/`
)))
dist_kl
[
is.na
(
dist_kl
)]
=
0.0
dist.counts.norm
=
as.dist
(
dist_kl
)
}
else
if
(
input
$
DistClust
==
"Unifrac"
)
{
tmp
=
UniFracDist
(
CT
,
tree
)
if
(
is.null
(
tree
)
||
is.null
(
tmp
))
dist.counts.norm
=
NULL
if
(
!
is.null
(
tree
))
{
dist.counts.norm
=
switch
(
input
$
DistClustUnifrac
,
...
...
@@ -684,6 +706,9 @@ Get_pcoa_table <-function (input, dds, group_init,CT,tree)
)
}
}
else
{
dist.counts.norm
=
vegdist
(
t
(
counts.norm
),
method
=
input
$
DistClust
)
}
if
(
!
is.null
(
dist.counts.norm
)){
## To get always the same result
...
...
Rfunctions/VisuPlot.R
View file @
2b5bd3f5
...
...
@@ -571,6 +571,7 @@ GetDataToPlot <- function(input,resDiff,VarInt,ind_taxo,aggregate=TRUE,rarefy=FA
counts_tmp
=
counts_tmp
[,
colnames
(
counts_tmp
)
%in%
rownames
(
targetInt
)]
## Proportions over all the taxonomies
## Proportion verified
prop_all
=
t
(
counts
)
/
rowSums
(
t
(
counts
))
prop_all
=
as.data.frame
(
prop_all
[,
Taxonomy
%in%
ind_taxo
])
prop_all
=
as.matrix
(
prop_all
[
rownames
(
prop_all
)
%in%
rownames
(
targetInt
),])
...
...
@@ -586,6 +587,7 @@ GetDataToPlot <- function(input,resDiff,VarInt,ind_taxo,aggregate=TRUE,rarefy=FA
}
if
(
!
aggregate
&&
nrow
(
counts_tmp
)
>
0
&&
nrow
(
targetInt
)
>
0
)
{
## Proportion verified
counts_tmp_combined
=
t
(
counts_tmp
)
prop_tmp_combined
=
counts_tmp_combined
/
colSums
(
counts_tmp
)
rownames
(
counts_tmp_combined
)
=
targetInt
$
AllVar
...
...
server.R
View file @
2b5bd3f5
...
...
@@ -756,7 +756,7 @@ shinyServer(function(input, output,session) {
## Export in .csv
output
$
ExportRelative
<-
downloadHandler
(
filename
=
function
()
{
'RelativeAb.csv'
},
content
=
function
(
file
){
write.csv
(
dataMergeCounts
()
$
counts
/
colSums
(
dataMergeCounts
()
$
counts
),
file
)}
content
=
function
(
file
){
write.csv
(
sweep
(
dataMergeCounts
()
$
counts
,
2
,
colSums
(
dataMergeCounts
()
$
counts
),
`/`
),
file
)}
)
## Export size factors
...
...
@@ -1551,16 +1551,16 @@ shinyServer(function(input, output,session) {
ErrorTree
=
dataInputTree
()
$
Error
TaxoSelect
=
input
$
TaxoSelect
res
=
selectInput
(
"DistClust"
,
"Distance"
,
c
(
"
euclidean"
,
"SERE"
=
"sere"
,
"canberra"
,
"bray"
,
"kulczynski"
,
"jaccard"
,
"gower"
,
"altGower
"
,
"morisita"
,
"horn"
,
"mountford"
,
"raup"
,
"binomial"
,
"chao"
,
"cao"
,
"mahalanobis
"
),
selected
=
"
canber
ra"
)
res
=
selectInput
(
"DistClust"
,
"Distance"
,
c
(
"
altGower"
,
"binomial"
,
"bray"
,
"canberra"
,
"cao"
,
"chao"
,
"euclidean"
,
"gower"
,
"horn"
,
"jaccard"
,
"jsd"
,
"kl"
,
"kulczynski"
,
"mahalanobis
"
,
"morisita"
,
"mountford"
,
"raup"
,
"SERE"
=
"sere
"
),
selected
=
"
b
ra
y
"
)
## Add the unifrac distance
if
(
!
is.null
(
tree
)
&&
!
is.null
(
input
$
fileTree
)
&&
is.null
(
ErrorTree
)
&&
TaxoSelect
==
"OTU/Gene"
)
{
res
=
selectInput
(
"DistClust"
,
"Distance"
,
c
(
"
euclidean"
,
"SERE"
=
"sere"
,
"canberra"
,
"bray"
,
"kulczynski"
,
"jaccard"
,
"
gower"
,
"altGower
"
,
"morisita"
,
"horn"
,
"mountford"
,
"raup"
,
"binomial"
,
"
chao"
,
"cao"
,
"mahalanobis
"
,
"Unifrac"
),
selected
=
"
canber
ra"
)
res
=
selectInput
(
"DistClust"
,
"Distance"
,
c
(
"
altGower"
,
"binomial"
,
"bray"
,
"canberra"
,
"cao"
,
"chao"
,
"euclidean"
,
"gower"
,
"horn"
,
"
jaccard"
,
"jsd"
,
"kl"
,
"kulczynski"
,
"mahalanobis
"
,
"morisita"
,
"mountford"
,
"raup"
,
"
SERE"
=
"sere
"
,
"Unifrac"
),
selected
=
"
b
ra
y
"
)
}
return
(
res
)
...
...
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