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Fiumara_BasePrimeEd2022
Fiumara_BasePrimeEd2022_WES
Commits
6fe5b298
Commit
6fe5b298
authored
Jul 31, 2023
by
Stefano Beretta
Browse files
Update WESopt_plot_results.R
parent
01515227
Changes
1
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Inline
Side-by-side
scripts/WESopt_plot_results.R
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6fe5b298
...
@@ -43,6 +43,161 @@ snv_colors2 <- function(del = FALSE, alpha = 1) {
...
@@ -43,6 +43,161 @@ snv_colors2 <- function(del = FALSE, alpha = 1) {
return
(
var_cols
)
return
(
var_cols
)
}
}
# Circos + Legend
legend_plot
=
function
(
t
,
sample
)
{
t
<-
mutate
(
t
,
TYPE
=
case_when
(
nchar
(
REF
)
==
1
&
nchar
(
ALT
)
==
1
&
ALT
!=
"*"
~
"Substitution"
,
nchar
(
REF
)
==
1
&
nchar
(
ALT
)
==
1
&
ALT
==
"*"
~
"Deletion"
,
nchar
(
REF
)
>
nchar
(
ALT
)
&
nchar
(
REF
)
-
nchar
(
ALT
)
>=
1
~
"Deletion"
,
nchar
(
REF
)
<
nchar
(
ALT
)
&
nchar
(
ALT
)
-
nchar
(
REF
)
>=
1
~
"Insertion"
,
TRUE
~
"Other"
))
# Substitutions
t.subs
<-
t
%>%
filter
(
TYPE
==
"Substitution"
)
%>%
tbl_df
()
t.subs
$
SUB
<-
paste0
(
t.subs
$
REF
,
t.subs
$
ALT
)
t.subs
$
SUB
<-
factor
(
t.subs
$
SUB
,
levels
=
sort
(
unique
(
t.subs
$
SUB
)))
cols_names
<-
levels
(
t.subs
$
SUB
)
cols
<-
snv_colors2
(
del
=
F
)
t.subs
<-
merge
(
t.subs
,
data.frame
(
cols
,
SUB
=
names
(
cols
)),
all.x
=
TRUE
)
tt.subs
<-
t.subs
%>%
filter
(
Sample
==
sample
)
%>%
tbl_df
()
# Deletions / Insertions
t.other
<-
t
%>%
filter
(
TYPE
!=
"Substitution"
)
%>%
tbl_df
()
tt.other
<-
t.other
%>%
filter
(
Sample
==
sample
)
%>%
tbl_df
()
if
(
nrow
(
tt.other
)
>
0
)
{
tt.other
$
AF
<-
1
}
tt.other
$
col
<-
ifelse
(
tt.other
$
TYPE
==
"Deletion"
,
"Red"
,
"Blue"
)
# Circos
par
(
mar
=
rep
(
0
,
4
))
chr.names
<-
paste0
(
"chr"
,
c
(
1
:
22
,
"X"
,
"Y"
))
circos.par
(
"start.degree"
=
90
)
circos.initializeWithIdeogram
(
species
=
"hg38"
,
chromosome.index
=
chr.names
,
plotType
=
c
())
# Legends (center)
legend
(
-0.5
,
0.85
,
lty
=
1
,
lwd
=
2
,
seg.len
=
1
,
col
=
c
(
"Red"
,
"Blue"
),
legend
=
c
(
"Deletion"
,
"Insertion"
),
bty
=
'n'
,
#xjust = 0,
x.intersp
=
0.4
,
y.intersp
=
1
,
inset
=
c
(
0.05
,
0
),
title.adj
=
0.1
,
title
=
"Small Indels"
)
legend
(
-0.5
,
0.45
,
pch
=
16
,
col
=
cols
,
legend
=
names
(
cols
),
pt.cex
=
1.2
,
bty
=
'n'
,
ncol
=
3
,
#xjust = 0,
x.intersp
=
0.4
,
y.intersp
=
1
,
inset
=
c
(
0.05
,
0
),
border
=
"NA"
,
title.adj
=
0.1
,
title
=
"Substitution"
)
if
(
"snpEff_Impact"
%in%
colnames
(
tt.subs
))
{
legend
(
-0.5
,
-0.2
,
pch
=
c
(
10
,
13
),
col
=
"red"
,
legend
=
c
(
"Relevant Impact"
,
"Target Gene"
),
pt.cex
=
1.8
,
bty
=
'n'
,
ncol
=
1
,
#xjust = 0,
x.intersp
=
0.6
,
y.intersp
=
1
,
inset
=
c
(
0.2
,
0
),
border
=
"NA"
,
title.adj
=
0
,
title
=
"Highlight Variants"
)
}
circos.clear
()
}
plot_circos
<-
function
(
t
,
sample
)
{
# Substitutions
t
<-
mutate
(
t
,
TYPE
=
case_when
(
nchar
(
REF
)
==
1
&
nchar
(
ALT
)
==
1
&
ALT
!=
"*"
~
"Substitution"
,
nchar
(
REF
)
==
1
&
nchar
(
ALT
)
==
1
&
ALT
==
"*"
~
"Deletion"
,
nchar
(
REF
)
>
nchar
(
ALT
)
&
nchar
(
REF
)
-
nchar
(
ALT
)
>=
1
~
"Deletion"
,
nchar
(
REF
)
<
nchar
(
ALT
)
&
nchar
(
ALT
)
-
nchar
(
REF
)
>=
1
~
"Insertion"
,
TRUE
~
"Other"
))
t.subs
<-
t
%>%
filter
(
TYPE
==
"Substitution"
)
%>%
tbl_df
()
t.subs
$
SUB
<-
paste0
(
t.subs
$
REF
,
t.subs
$
ALT
)
t.subs
$
SUB
<-
factor
(
t.subs
$
SUB
,
levels
=
sort
(
unique
(
t.subs
$
SUB
)))
cols_names
<-
levels
(
t.subs
$
SUB
)
cols
<-
snv_colors2
(
del
=
F
,
alpha
=
0.8
)
t.subs
<-
merge
(
t.subs
,
data.frame
(
cols
,
SUB
=
names
(
cols
)),
all.x
=
TRUE
)
tt.subs
<-
t.subs
%>%
filter
(
Sample
==
sample
)
%>%
tbl_df
()
# Deletions / Insertions
t.other
<-
t
%>%
filter
(
TYPE
!=
"Substitution"
)
%>%
tbl_df
()
tt.other
<-
t.other
%>%
filter
(
Sample
==
sample
)
%>%
tbl_df
()
if
(
nrow
(
tt.other
)
>
0
)
{
tt.other
$
VAF
<-
1
}
tt.other
$
col
<-
ifelse
(
tt.other
$
TYPE
==
"Deletion"
,
"Red"
,
"Blue"
)
if
(
"IMPACT"
%in%
colnames
(
tt.other
))
{
hio
<-
subset
(
tt.other
,
IMPACT
%in%
c
(
"HIGH"
,
"MODERATE"
))
if
(
nrow
(
hio
)
>
0
)
{
print
(
hio
)
}
}
# Circos
par
(
mar
=
rep
(
0
,
4
))
chr.names
<-
paste0
(
"chr"
,
c
(
1
:
22
,
"X"
,
"Y"
))
circos.par
(
"start.degree"
=
90
)
circos.initializeWithIdeogram
(
species
=
"hg38"
,
chromosome.index
=
chr.names
,
plotType
=
c
(
"ideogram"
,
"labels"
))
lines
<-
seq
(
0
,
1
,
0.2
)
line_factors
<-
expand.grid
(
x
=
get.all.sector.index
(),
y
=
lines
)
circos.trackPlotRegion
(
factors
=
line_factors
$
x
,
y
=
line_factors
$
y
,
track.height
=
0.4
,
panel.fun
=
function
(
x
,
y
)
{
xl
<-
get.cell.meta.data
(
"xlim"
)
for
(
i
in
lines
)
{
circos.lines
(
xl
,
c
(
i
,
i
),
col
=
"grey"
)
}
})
for
(
i
in
lines
)
{
circos.text
(
0
,
i
,
i
,
col
=
"black"
,
sector.index
=
"chrY"
,
track.index
=
3
,
cex
=
0.5
,
adj
=
c
(
0.01
,
0.01
))
}
circos.trackPoints
(
tt.subs
$
CHROM
,
tt.subs
$
POS
,
tt.subs
$
VAF
,
pch
=
16
,
cex
=
1.5
,
col
=
as.character
(
tt.subs
$
cols
))
if
(
"snpEff_Impact"
%in%
colnames
(
tt.subs
))
{
hi
<-
subset
(
tt.subs
,
snpEff_Impact
%in%
c
(
"HIGH"
,
"MODERATE"
))
if
(
nrow
(
hi
)
>
0
)
{
circos.trackPoints
(
hi
$
CHROM
,
hi
$
POS
,
hi
$
VAF
,
pch
=
10
,
cex
=
1.8
,
col
=
"red"
,
track.index
=
3
)
}
b2m_df
<-
data.frame
(
"CHROM"
=
c
(
"chr15"
),
"POS"
=
c
(
44715702
),
"VAF"
=
c
(
0.7
))
circos.trackPoints
(
b2m_df
$
CHROM
,
b2m_df
$
POS
,
b2m_df
$
VAF
,
pch
=
13
,
cex
=
2.5
,
col
=
"red"
,
track.index
=
3
)
}
circos.trackPlotRegion
(
factors
=
line_factors
$
x
,
ylim
=
c
(
0
,
1
),
track.height
=
0.1
)
if
(
nrow
(
tt.other
)
>
0
)
{
circos.trackLines
(
tt.other
$
CHROM
,
tt.other
$
POS
,
tt.other
$
VAF
,
track.index
=
4
,
col
=
as.character
(
tt.other
$
col
),
lwd
=
2
,
type
=
'h'
)
}
text
(
0
,
0
,
sample
,
cex
=
1.5
)
circos.clear
()
}
# Variant Plot function
# Variant Plot function
plot_variants
<-
function
(
full.t
,
out_dir
,
plot_prefix
,
fill_by
)
{
plot_variants
<-
function
(
full.t
,
out_dir
,
plot_prefix
,
fill_by
)
{
dir.create
(
path
=
out_dir
,
showWarnings
=
F
)
dir.create
(
path
=
out_dir
,
showWarnings
=
F
)
...
...
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