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sc-TissueMapper_Pr
Commits
d2aadde2
Commit
d2aadde2
authored
6 years ago
by
Gervaise Henry
Browse files
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Remove some depreciated code
parent
53367009
Branches
Branches containing commit
1 merge request
!2
Merge develop into master
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2
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2 changed files
r.scripts/sc-TissueMapper.R
+1
-27
1 addition, 27 deletions
r.scripts/sc-TissueMapper.R
r.scripts/sc-TissueMapper_RUN.Pd.R
+0
-33
0 additions, 33 deletions
r.scripts/sc-TissueMapper_RUN.Pd.R
with
1 addition
and
60 deletions
r.scripts/sc-TissueMapper.R
+
1
−
27
View file @
d2aadde2
...
...
@@ -492,14 +492,6 @@ scQuSAGE <- function(sc10x,gs,res.use=0.1,ds=25000,nm="Lin",folder="lin"){
labels
<-
paste0
(
"Cluster_"
,
as.vector
(
factor
(
sc10x
@
ident
)))
#if ((ncol(sc10x@data)>ds & ds!=0)){
# rnd <- sample(1:ncol(sc10x@data),ds)
# data <- sc10x@data[,rnd]
# labels <- labels[rnd]
#} else {
# data <- sc10x@data
#}
cell.sample
<-
NULL
for
(
i
in
1
:
number.clusters
){
cell
<-
names
(
sc10x
@
ident
[
sc10x
@
ident
==
i
])
...
...
@@ -651,16 +643,7 @@ scQuSAGEsm <- function(sc10x,gs,ds=25000,nm="Lin",folder="lin"){
clusters
<-
unique
(
sc10x
@
ident
)
labels
<-
as.vector
(
factor
(
sc10x
@
ident
))
#if ((ncol(sc10x@data)>ds & ds!=0)){
# rnd <- sample(1:ncol(sc10x@data),ds)
# data <- sc10x@data[,rnd]
# labels <- labels[rnd]
#} else {
# data <- sc10x@data
#}
#data <- as.data.frame(as.matrix(data))
cell.sample
<-
NULL
for
(
i
in
clusters
){
cell
<-
names
(
sc10x
@
ident
[
sc10x
@
ident
==
i
])
...
...
@@ -773,15 +756,6 @@ scQuSAGElg <- function(sc10x,gs,ds=25000,nm="Lin",folder="lin"){
labels
<-
as.vector
(
factor
(
sc10x
@
ident
))
#if ((ncol(sc10x@data)>ds & ds!=0)){
# rnd <- sample(1:ncol(sc10x@data),ds)
# data <- sc10x@data[,rnd]
# labels <- labels[rnd]
#} else {
# data <- sc10x@data
#}
#data <- as.data.frame(as.matrix(data))
cell.sample
<-
NULL
for
(
i
in
clusters
){
cell
<-
names
(
sc10x
@
ident
[
sc10x
@
ident
==
i
])
...
...
This diff is collapsed.
Click to expand it.
r.scripts/sc-TissueMapper_RUN.Pd.R
+
0
−
33
View file @
d2aadde2
...
...
@@ -3,7 +3,6 @@ library(methods)
library
(
optparse
)
library
(
Seurat
)
library
(
readr
)
#library(readxl)
library
(
fBasics
)
library
(
pastecs
)
library
(
qusage
)
...
...
@@ -104,18 +103,11 @@ option_list=list(
make_option
(
"--cca"
,
action
=
"store"
,
default
=
50
,
type
=
'integer'
,
help
=
"Number of CCAs to cacluate"
),
make_option
(
"--acca"
,
action
=
"store"
,
default
=
30
,
type
=
'integer'
,
help
=
"Number of CCAs to align"
),
make_option
(
"--pc"
,
action
=
"store"
,
default
=
50
,
type
=
'integer'
,
help
=
"Number of PCs to cacluate"
),
#make_option("--hpc",action="store",default=0.9,type='numeric',help="Max variance cutoff for PCs to use, pre-stress"),
make_option
(
"--res.prestress"
,
action
=
"store"
,
default
=
1
,
type
=
'numeric'
,
help
=
"Resolution to cluster, pre-stress"
),
make_option
(
"--st"
,
action
=
"store"
,
default
=
TRUE
,
type
=
'logical'
,
help
=
"Remove stressed cells?"
),
make_option
(
"--stg"
,
action
=
"store"
,
default
=
"go"
,
type
=
'character'
,
help
=
"Geneset to use for stress ID"
),
make_option
(
"--cut.stress"
,
action
=
"store"
,
default
=
0.9
,
type
=
'numeric'
,
help
=
"Cutoff for stress score"
),
#make_option("--hpc.poststress",action="store",default=0.85,type='numeric',help="Max variance cutoff for PCs to use, post-stress"),
make_option
(
"--res.poststress"
,
action
=
"store"
,
default
=
0.2
,
type
=
'numeric'
,
help
=
"Resolution to cluster, post-stress"
),
#make_option("--ds",action="store",default=250,type='integer',help="Number of cells to downsample"),
#make_option("--hpc.epi",action="store",default=0.85,type='numeric',help="Max variance cutoff for PCs to use, Epi"),
#make_option("--res.epi",action="store",default=0.2,type='numeric',help="Resolution to cluster, Epi"),
#make_option("--hpc.st",action="store",default=0.85,type='numeric',help="Max variance cutoff for PCs to use, St"),
#make_option("--res.st",action="store",default=0.15,type='numeric',help="Resolution to cluster, St"),
make_option
(
"--cut.ne"
,
action
=
"store"
,
default
=
0.999
,
type
=
'numeric'
,
help
=
"Cutoff for NE score"
)
)
opt
=
parse_args
(
OptionParser
(
option_list
=
option_list
))
...
...
@@ -164,14 +156,7 @@ rm(sc10x.D17)
rm
(
sc10x.D27
)
rm
(
sc10x.D35
)
#results <- scPC(sc10x,lx=opt$lx,hx=opt$hx,ly=opt$ly,cc=opt$cc,pc=opt$pc,hpc=opt$hpc,file="pre.stress",cca=TRUE)
#sc10x <- results[[1]]
#genes.hvg.prestress <- results[[2]]
#pc.use.prestress <- results[[3]]
#rm(results)
sc10x
<-
scCluster
(
sc10x
,
pc.use
=
opt
$
acca
,
res.use
=
opt
$
res.prestress
,
folder
=
"pre.stress"
,
red
=
"cca.aligned"
)
#sc10x <- scCluster(sc10x,pc.use=pc.use.prestress,res.use=opt$res.prestress,folder="pre.stress",red="pca")
if
(
opt
$
st
==
TRUE
){
results
<-
scStress
(
sc10x
,
stg
=
opt
$
stg
,
res.use
=
opt
$
res.prestress
,
cut
=
opt
$
cut.stress
)
...
...
@@ -180,17 +165,7 @@ if (opt$st==TRUE){
sc10x.Stress
<-
results
[[
3
]]
rm
(
results
)
#results <- scPC(sc10x,lx=opt$lx,hx=opt$hx,ly=opt$ly,cc=opt$cc,pc=opt$pc,hpc=opt$hpc,file="post.stress",cca=FALSE)
#sc10x <- results[[1]]
#genes.hvg.poststress <- results[[2]]
#pc.use.poststress <- results[[3]]
#rm(results)
#sc10x <- scCluster(sc10x,pc.use=pc.use.poststress,res.use=opt$res.poststress,folder="post.stress",red="pca")
sc10x
<-
scCluster
(
sc10x
,
pc.use
=
opt
$
acca
,
res.use
=
opt
$
res.poststress
,
folder
=
"post.stress"
,
red
=
"cca.aligned"
)
#sc10x <- scCluster(sc10x,pc.use=opt$acca,res.use=0.15,folder="post.stress",red="cca.aligned")
#sc10x <- scCluster(sc10x,pc.use=opt$acca,res.use=0.25,folder="post.stress",red="cca.aligned")
#sc10x <- scCluster(sc10x,pc.use=opt$acca,res.use=0.5,folder="post.stress",red="cca.aligned")
}
gene.set1
<-
read_delim
(
"./genesets/DEG_Epi_5FC.txt"
,
"\t"
,
escape_double
=
FALSE
,
trim_ws
=
TRUE
,
col_names
=
FALSE
)
...
...
@@ -303,12 +278,6 @@ gc()
results.cor.Epi.lgea
<-
scQuSAGEsm
(
sc10x.Epi
,
gs
=
gene.set
,
ds
=
min.epi
,
nm
=
"Epi.dws.sub"
,
folder
=
"lgea"
)
rm
(
gene.set
)
#sc10x.St <- scCluster(sc10x.St,pc.use=opt$acca,res.use=opt$res.st,folder="st",red="cca.aligned")
#sc10x.St <- scCluster(sc10x.St,pc.use=opt$acca,res.use=0.2,folder="st",red="cca.aligned")
#sc10x.St <- scCluster(sc10x.St,pc.use=opt$acca,res.use=0.25,folder="st",red="cca.aligned")
#sc10x.St <- scCluster(sc10x.St,pc.use=opt$acca,res.use=0.5,folder="st",red="cca.aligned")
#sc10x.St <- scCluster(sc10x.St,pc.use=opt$acca,res.use=0.1,folder="st",red="cca.aligned")
sc10x.St
<-
RunTSNE
(
object
=
sc10x.St
,
reduction.use
=
"cca.aligned"
,
dims.use
=
1
:
opt
$
acca
,
do.fast
=
TRUE
)
postscript
(
paste0
(
"./analysis/tSNE/st/tSNE_Sample.eps"
))
plot
<-
TSNEPlot
(
object
=
sc10x.St
,
group.by
=
"samples"
,
pt.size
=
2.5
,
do.return
=
TRUE
,
vector.friendly
=
FALSE
)
...
...
@@ -363,7 +332,6 @@ sc10x <- scMerge(sc10x,sc10x,sc10x.Epi.NE,i.1="Merge_Epi.dws_St.go",i.2="NE",nm=
sc10x.Epi
<-
scMerge
(
sc10x.Epi
,
sc10x.Epi
,
sc10x.Epi.NE
,
i.1
=
"Epi.dws.sub"
,
i.2
=
"NE"
,
nm
=
"Epi.dws.sub_NE"
)
gene.orthog
<-
read.delim
(
"./genesets/Ensemble.mus-hum.txt"
)
#gene.set1 <- read_excel("./genesets/SupTab3_Consensus_Sigs.xlsx",skip=5)
gene.set1
<-
read_csv
(
"./genesets/SupTab3_Consensus_Sigs.csv"
,
skip
=
6
)
gene.set2
<-
as.data.frame
(
gene.set1
$
Basal
[
!
is.na
(
gene.set1
$
Basal
)])
colnames
(
gene.set2
)
<-
"genes"
...
...
@@ -402,7 +370,6 @@ gene.set2 <- as.list(gene.set2)
names
(
gene.set2
)
<-
"Ionocyte"
gene.set
<-
c
(
gene.set
,
gene.set2
)
rm
(
gene.set2
)
#gene.set1 <- read_excel("./genesets/SupTab6_Krt13_Hillock.xlsx",skip=5)
gene.set1
<-
read_csv
(
"./genesets/SupTab6_Krt13_Hillock.csv"
,
skip
=
6
)
gene.set1
<-
gene.set1
[
gene.set1
$
FDR
<=
0.05
&
gene.set1
$
'log2 fold-change (MAST)'
>=
1.5
,
1
]
colnames
(
gene.set1
)
<-
"genes"
...
...
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