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Fiumara_BasePrimeEd2022
Fiumara_BasePrimeEd2022_WES
Commits
14a5691d
Commit
14a5691d
authored
Jul 31, 2023
by
Stefano Beretta
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parent
d1906bfa
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scripts/WESopt_plot_results.R
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14a5691d
library
(
dplyr
)
library
(
ggplot2
)
library
(
RColorBrewer
)
library
(
CMplot
)
library
(
gtable
)
library
(
circlize
)
library
(
grid
)
library
(
gridExtra
)
library
(
stringr
)
library
(
e1071
)
library
(
openxlsx
)
library
(
VennDiagram
)
library
(
scales
)
library
(
ggVennDiagram
)
library
(
reshape2
)
#########################
### Utility Functions ###
#########################
# A helper function to define a region on the layout
define_region
<-
function
(
row
,
col
){
viewport
(
layout.pos.row
=
row
,
layout.pos.col
=
col
)
}
# Function to define colors for SNVs
snv_colors2
<-
function
(
del
=
FALSE
,
alpha
=
1
)
{
nuc
<-
c
(
"A"
,
"C"
,
"G"
,
"T"
)
# Point deletions
dels
<-
alpha
(
brewer.pal
(
5
,
"Greys"
)[
2
:
5
],
1
)
names
(
dels
)
<-
paste0
(
nuc
,
"*"
)
# Transitions
ts
<-
alpha
(
brewer.pal
(
5
,
"Blues"
)[
2
:
5
],
1
)
names
(
ts
)
<-
c
(
"CT"
,
"GA"
,
"AG"
,
"TC"
)
# Tansversions
tv1
<-
alpha
(
brewer.pal
(
5
,
"YlGn"
)[
2
:
5
],
1
)
names
(
tv1
)
<-
c
(
"AC"
,
"TG"
,
"AT"
,
"TA"
)
tv2
<-
alpha
(
brewer.pal
(
5
,
"OrRd"
)[
2
:
5
],
1
)
names
(
tv2
)
<-
c
(
"CA"
,
"GT"
,
"CG"
,
"GC"
)
var_cols
<-
c
(
ts
,
tv1
,
tv2
)
if
(
del
)
{
var_cols
<-
c
(
var_cols
,
dels
)
}
return
(
var_cols
)
}
# Variant Plot function
plot_variants
<-
function
(
full.t
,
out_dir
,
plot_prefix
,
fill_by
)
{
dir.create
(
path
=
out_dir
,
showWarnings
=
F
)
tt
<-
full.t
%>%
filter
(
grepl
(
"chr"
,
CHROM
))
%>%
filter
(
!
CHROM
%in%
c
(
"chrY"
,
"chrM"
))
%>%
group_by
(
Sample
,
!!!
syms
(
fill_by
))
%>%
summarise
(
Count
=
n
())
write.xlsx
(
x
=
list
(
"NumVariants"
=
tt
),
file
=
paste
(
out_dir
,
paste0
(
plot_prefix
,
"_VariantCounts.xlsx"
),
sep
=
"/"
))
p
<-
ggplot
(
tt
,
aes
(
x
=
Sample
,
y
=
Count
,
fill
=
get
(
fill_by
)))
+
theme_bw
(
base_size
=
12
)
+
theme
(
axis.text.x
=
element_text
(
angle
=
90
,
hjust
=
1
,
vjust
=
0.5
),
legend.position
=
"none"
)
+
geom_bar
(
stat
=
"identity"
)
+
scale_y_continuous
(
labels
=
scales
::
comma
,
n.breaks
=
8
)
+
xlab
(
""
)
+
facet_grid
(
.
~
get
(
fill_by
),
scales
=
"free_x"
,
space
=
"free"
)
ggsave
(
filename
=
paste
(
out_dir
,
paste0
(
plot_prefix
,
"_VariantCounts.pdf"
),
sep
=
"/"
),
plot
=
p
,
width
=
6
,
height
=
6
)
tt
<-
full.t
%>%
filter
(
grepl
(
"chr"
,
CHROM
))
%>%
filter
(
!
CHROM
%in%
c
(
"chrY"
,
"chrM"
))
%>%
group_by
(
Sample
,
!!!
syms
(
fill_by
),
REF
,
ALT
)
%>%
summarise
(
Count
=
n
())
tt
<-
mutate
(
tt
,
TYPE
=
case_when
(
nchar
(
REF
)
==
1
&
nchar
(
ALT
)
==
1
&
ALT
!=
"*"
~
"SNV"
,
nchar
(
REF
)
==
1
&
nchar
(
ALT
)
==
1
&
ALT
==
"*"
~
"DEL"
,
nchar
(
REF
)
>
nchar
(
ALT
)
&
nchar
(
REF
)
-
nchar
(
ALT
)
>=
1
~
"DEL"
,
nchar
(
REF
)
<
nchar
(
ALT
)
&
nchar
(
ALT
)
-
nchar
(
REF
)
>=
1
~
"INS"
,
TRUE
~
"Other"
))
write.xlsx
(
x
=
list
(
"VariantClass"
=
tt
),
file
=
paste
(
out_dir
,
paste0
(
plot_prefix
,
"_VariantClassification.xlsx"
),
sep
=
"/"
))
tt_type
<-
tt
%>%
group_by
(
Sample
,
!!!
syms
(
fill_by
),
TYPE
)
%>%
summarise
(
SumCount
=
sum
(
Count
))
%>%
arrange
(
desc
(
SumCount
))
%>%
group_by
(
Sample
,
!!!
syms
(
fill_by
))
%>%
mutate
(
CountPerc
=
SumCount
/
sum
(
SumCount
))
write.xlsx
(
x
=
list
(
"VariantType"
=
tt_type
),
file
=
paste
(
out_dir
,
paste0
(
plot_prefix
,
"_VariantType.xlsx"
),
sep
=
"/"
))
p
<-
ggplot
(
tt_type
,
aes
(
x
=
Sample
,
y
=
SumCount
,
fill
=
TYPE
))
+
theme_bw
(
base_size
=
12
)
+
theme
(
axis.text.x
=
element_text
(
angle
=
30
,
hjust
=
1
),
legend.position
=
"top"
)
+
guides
(
fill
=
guide_legend
(
ncol
=
6
))
+
xlab
(
""
)
+
ylab
(
"Count"
)
+
scale_fill_brewer
(
palette
=
"Set1"
,
name
=
""
)
+
geom_bar
(
stat
=
"identity"
,
position
=
"stack"
)
+
scale_y_continuous
(
labels
=
scales
::
comma
,
n.breaks
=
8
)
+
facet_grid
(
.
~
get
(
fill_by
),
scales
=
"free_x"
,
space
=
"free"
)
ggsave
(
filename
=
paste
(
out_dir
,
paste0
(
plot_prefix
,
"_VariantTypes.pdf"
),
sep
=
"/"
),
plot
=
p
,
width
=
6
,
height
=
6
)
p
<-
ggplot
(
tt_type
,
aes
(
x
=
Sample
,
y
=
CountPerc
,
fill
=
TYPE
))
+
theme_bw
(
base_size
=
12
)
+
theme
(
axis.text.x
=
element_text
(
angle
=
30
,
hjust
=
1
),
legend.position
=
"top"
)
+
guides
(
fill
=
guide_legend
(
ncol
=
6
))
+
xlab
(
""
)
+
ylab
(
"Count"
)
+
scale_fill_brewer
(
palette
=
"Set1"
,
name
=
""
)
+
geom_bar
(
stat
=
"identity"
,
position
=
"stack"
)
+
scale_y_continuous
(
labels
=
scales
::
percent_format
(
accuracy
=
2
),
n.breaks
=
10
)
+
facet_grid
(
.
~
get
(
fill_by
),
scales
=
"free_x"
,
space
=
"free"
)
ggsave
(
filename
=
paste
(
out_dir
,
paste0
(
plot_prefix
,
"_VariantTypesPerc.pdf"
),
sep
=
"/"
),
plot
=
p
,
width
=
6
,
height
=
6
)
tt
<-
full.t
%>%
filter
(
nchar
(
REF
)
==
1
&
nchar
(
ALT
)
==
1
&
grepl
(
"chr"
,
CHROM
))
%>%
filter
(
!
CHROM
%in%
c
(
"chrY"
,
"chrM"
))
%>%
group_by
(
Sample
,
!!!
syms
(
fill_by
),
REF
,
ALT
)
%>%
summarise
(
Count
=
n
())
%>%
group_by
(
Sample
,
!!!
syms
(
fill_by
))
%>%
mutate
(
CountPerc
=
Count
/
sum
(
Count
))
tt
$
Variant
<-
paste0
(
tt
$
REF
,
tt
$
ALT
)
tt
$
Variant
<-
factor
(
tt
$
Variant
,
levels
=
sort
(
unique
(
tt
$
Variant
)))
write.xlsx
(
x
=
list
(
"SNV"
=
tt
),
file
=
paste
(
out_dir
,
paste0
(
plot_prefix
,
"_SNVcounts.xlsx"
),
sep
=
"/"
))
tt
$
Variant
<-
factor
(
tt
$
Variant
,
levels
=
rev
(
names
(
snv_colors2
())))
p2
<-
ggplot
(
tt
,
aes
(
x
=
Sample
,
y
=
Count
,
fill
=
Variant
))
+
theme_bw
(
base_size
=
12
)
+
theme
(
axis.text.x
=
element_text
(
angle
=
30
,
hjust
=
1
))
+
geom_bar
(
stat
=
"identity"
)
+
scale_fill_manual
(
values
=
snv_colors2
(
del
=
F
))
+
xlab
(
""
)
+
scale_y_continuous
(
labels
=
scales
::
comma
,
n.breaks
=
8
)
+
facet_grid
(
.
~
get
(
fill_by
),
scales
=
"free_x"
,
space
=
"free"
)
ggsave
(
filename
=
paste
(
out_dir
,
paste0
(
plot_prefix
,
"_SNVcounts.pdf"
),
sep
=
"/"
),
plot
=
p2
,
width
=
7
,
height
=
7
)
p2p
<-
ggplot
(
tt
,
aes
(
x
=
Sample
,
y
=
CountPerc
,
fill
=
Variant
))
+
theme_bw
(
base_size
=
12
)
+
theme
(
axis.text.x
=
element_text
(
angle
=
30
,
hjust
=
1
))
+
geom_bar
(
stat
=
"identity"
)
+
scale_fill_manual
(
values
=
snv_colors2
(
del
=
F
))
+
scale_y_continuous
(
labels
=
scales
::
percent_format
(
accuracy
=
2
),
n.breaks
=
10
)
+
xlab
(
""
)
+
facet_grid
(
.
~
get
(
fill_by
),
scales
=
"free_x"
,
space
=
"free"
)
ggsave
(
filename
=
paste
(
out_dir
,
paste0
(
plot_prefix
,
"_SNVcountsPerc.pdf"
),
sep
=
"/"
),
plot
=
p2p
,
width
=
7
,
height
=
7
)
}
###############
### General ###
###############
wdir
<-
"WESopt"
out_dir
<-
paste
(
wdir
,
"results"
,
sep
=
"/"
)
dir.create
(
out_dir
,
showWarnings
=
F
)
# Samples
samples
<-
c
(
"S1_B1"
,
"S2_B2"
,
"S3_B3"
,
"S4_D0"
,
"S5_D1"
,
"S6_D3"
,
"S7_E0"
,
"S8_E1"
,
"S9_E2"
,
"S10_vitroB"
,
"S11_vitroD"
,
"S12_vitroE"
)
################
### Variants ###
################
full.t
<-
data.frame
()
for
(
ss
in
samples
)
{
print
(
ss
)
t
<-
read.table
(
gzfile
(
paste
(
wdir
,
"data"
,
ss
,
paste0
(
ss
,
"-DP500_PASS_sGQ80_sDP10.ANNOT.vcf.gz"
),
sep
=
"/"
)),
comment.char
=
"#"
,
sep
=
"\t"
)
colnames
(
t
)
<-
c
(
"CHROM"
,
"POS"
,
"ID"
,
"REF"
,
"ALT"
,
"QUAL"
,
"FILTER"
,
"ANNOT"
,
"FORMAT"
,
"SAMPLE"
)
t
$
Sample
<-
ss
t
$
Vars
<-
paste
(
t
$
CHROM
,
t
$
POS
,
t
$
REF
,
t
$
ALT
,
sep
=
"-"
)
t
$
Group
<-
ifelse
(
startsWith
(
str_split_fixed
(
ss
,
"_"
,
2
)[,
2
],
"vitro"
),
gsub
(
"vitro"
,
""
,
str_split_fixed
(
ss
,
"_"
,
2
)[,
2
]),
str_sub
(
str_split_fixed
(
ss
,
"_"
,
2
)[,
2
],
1
,
1
))
t
$
Type
<-
ifelse
(
startsWith
(
str_split_fixed
(
ss
,
"_"
,
2
)[,
2
],
"vitro"
),
"Vitro"
,
"Sample"
)
t
$
DP
<-
as.numeric
(
str_split_fixed
(
t
$
SAMPLE
,
":"
,
5
)[,
3
])
t
$
AD
<-
as.numeric
(
str_split_fixed
(
str_split_fixed
(
t
$
SAMPLE
,
":"
,
5
)[,
2
],
","
,
2
)[,
1
])
t
$
VAF
<-
(
t
$
DP
-
t
$
AD
)
/
t
$
DP
full.t
<-
rbind
(
full.t
,
t
)
}
# Filter CHR only
chr
<-
c
(
paste0
(
"chr"
,
seq
(
1
,
22
)),
"chrX"
)
full.t
<-
subset
(
full.t
,
CHROM
%in%
chr
)
full.t
$
CHROM
<-
factor
(
full.t
$
CHROM
,
levels
=
chr
)
full.t
$
Sample
<-
factor
(
full.t
$
Sample
,
levels
=
unique
(
full.t
$
Sample
))
# Remove Multi
full.t.nomulti
<-
full.t
[
grep
(
","
,
full.t
$
ALT
,
value
=
F
,
invert
=
T
),
]
write.table
(
x
=
full.t.nomulti
,
file
=
paste
(
out_dir
,
"Full_NoMulti_res.tsv"
,
sep
=
"/"
),
sep
=
"\t"
,
quote
=
F
,
row.names
=
F
,
col.names
=
T
)
plot_variants
(
full.t
=
full.t.nomulti
,
out_dir
=
out_dir
,
plot_prefix
=
"Full_NoMulti"
,
fill_by
=
"Group"
)
# Check Vitro overlap (for germline)
full.venn
<-
list
()
for
(
vs
in
subset
(
unique
(
full.t.nomulti
[
,
c
(
"Sample"
,
"Type"
)]),
Type
==
"Vitro"
)
$
Sample
)
{
print
(
vs
)
full.venn
[[
vs
]]
<-
full.t.nomulti
[
full.t.nomulti
$
Sample
==
vs
,
"Vars"
]
}
venn
<-
Venn
(
full.venn
)
data
<-
process_data
(
venn
)
vreg
<-
venn_region
(
data
)
vreg
$
NumInters
<-
as.character
(
str_count
(
venn_region
(
data
)
$
name
,
"[..]"
))
cc
<-
brewer.pal
(
name
=
"Set2"
,
n
=
8
)
cc_cat
<-
cc
[
1
:
length
(
unique
(
vreg
$
NumInters
))]
names
(
cc_cat
)
<-
unique
(
vreg
$
NumInters
)
s.plot
<-
ggplot
()
+
# change mapping of color filling
geom_sf
(
aes
(
fill
=
NumInters
),
data
=
vreg
,
show.legend
=
FALSE
)
+
scale_fill_manual
(
values
=
cc_cat
)
+
# adjust edge size and color
geom_sf
(
color
=
"grey"
,
size
=
1
,
data
=
venn_setedge
(
data
),
show.legend
=
FALSE
)
+
# show set label in bold
geom_sf_text
(
aes
(
label
=
name
),
fontface
=
"bold"
,
data
=
venn_setlabel
(
data
),
size
=
8
,
nudge_y
=
c
(
-400
,
-50
,
-400
),
nudge_x
=
c
(
150
,
0
,
-150
))
+
# add a alternative region name
geom_sf_label
(
aes
(
label
=
paste0
(
count
,
"\n"
,
"("
,
round
(
count
/
sum
(
count
)
*
100
,
1
),
"%)"
)),
data
=
vreg
,
alpha
=
0.5
,
size
=
5
)
+
theme_void
()
ggsave
(
filename
=
paste
(
out_dir
,
"Vitro_vars_venn.pdf"
,
sep
=
"/"
),
plot
=
s.plot
,
width
=
5
,
height
=
5
)
# Control
vitro_ctrl
<-
subset
(
full.t.nomulti
,
Sample
==
"S12_vitroE"
)
vitro_ctrl_vars
<-
vitro_ctrl
$
Vars
# Remove germline
full.t.nomulti.noGerm
<-
subset
(
full.t.nomulti
,
!
(
Vars
%in%
vitro_ctrl_vars
))
plot_variants
(
full.t
=
full.t.nomulti.noGerm
,
out_dir
=
out_dir
,
plot_prefix
=
"Full_NoMulti_noGerm"
,
fill_by
=
"Group"
)
# Parse snpEff Annotation
full.t.nomulti.noGerm
$
snpEff_tmp
<-
lapply
(
full.t.nomulti.noGerm
$
ANNOT
,
function
(
x
){
tmp
<-
strsplit
(
x
,
";"
)[[
1
]]
ann_pos
<-
length
(
tmp
)
if
(
!
startsWith
(
tmp
[
length
(
tmp
)],
"ANN"
))
{
for
(
i
in
seq
(
1
,
length
(
tmp
)))
{
if
(
startsWith
(
tmp
[
i
],
"ANN"
))
{
ann_pos
<-
i
}
}
}
tmp
<-
tmp
[
ann_pos
]
})
full.t.nomulti.noGerm
$
snpEff_Effect
<-
sapply
(
full.t.nomulti.noGerm
$
snpEff_tmp
,
function
(
tmp
){
strsplit
(
tmp
,
"|"
,
fixed
=
T
)[[
1
]][
2
]
},
USE.NAMES
=
F
)
full.t.nomulti.noGerm
$
snpEff_Impact
<-
sapply
(
full.t.nomulti.noGerm
$
snpEff_tmp
,
function
(
tmp
){
strsplit
(
tmp
,
"|"
,
fixed
=
T
)[[
1
]][
3
]
},
USE.NAMES
=
F
)
full.t.nomulti.noGerm
$
snpEff_Gene
<-
sapply
(
full.t.nomulti.noGerm
$
snpEff_tmp
,
function
(
tmp
){
strsplit
(
tmp
,
"|"
,
fixed
=
T
)[[
1
]][
4
]
},
USE.NAMES
=
F
)
full.t.nomulti.noGerm
$
snpEff_GeneName
<-
sapply
(
full.t.nomulti.noGerm
$
snpEff_tmp
,
function
(
tmp
){
strsplit
(
tmp
,
"|"
,
fixed
=
T
)[[
1
]][
5
]
},
USE.NAMES
=
F
)
full.t.nomulti.noGerm
$
snpEff_BioType
<-
sapply
(
full.t.nomulti.noGerm
$
snpEff_tmp
,
function
(
tmp
){
strsplit
(
tmp
,
"|"
,
fixed
=
T
)[[
1
]][
8
]
},
USE.NAMES
=
F
)
full.t.nomulti.noGerm
$
snpEff_tmp
<-
NULL
# Save results
write.table
(
x
=
full.t.nomulti.noGerm
,
file
=
paste
(
out_dir
,
"Full_NoMulti_noGerm_res.tsv"
,
sep
=
"/"
),
sep
=
"\t"
,
quote
=
F
,
row.names
=
F
,
col.names
=
T
)
## Samples only ##
samples.t.nomulti.noGerm
<-
subset
(
full.t.nomulti.noGerm
,
Type
==
"Sample"
)
plot_variants
(
full.t
=
samples.t.nomulti.noGerm
,
out_dir
=
out_dir
,
plot_prefix
=
"Samples_NoMulti_noGerm"
,
fill_by
=
"Group"
)
write.table
(
x
=
samples.t.nomulti.noGerm
,
file
=
paste
(
out_dir
,
"Samples_NoMulti_noGerm_res.tsv"
,
sep
=
"/"
),
sep
=
"\t"
,
quote
=
F
,
row.names
=
F
,
col.names
=
T
)
############################
### Cancer-related Genes ###
############################
offt_gene
<-
c
(
"ABCB1"
,
"ABCC2"
,
"ABL1"
,
"ABL2"
,
"AKT1"
,
"AKT2"
,
"AKT3"
,
"ALK"
,
"ANGPTL7"
,
"APC"
,
"ASXL1"
,
"ATM"
,
"ATRX"
,
"BCYRN1"
,
"BRAF"
,
"BRCA1"
,
"BRCA2"
,
"CBL"
,
"CDA"
,
"CDH1"
,
"CDKN2A"
,
"CDKN2B"
,
"CEBPA"
,
"CHD7"
,
"CHIC2"
,
"CREBBP"
,
"CRLF2"
,
"CSF1R"
,
"CTNNB1"
,
"CYP19A1"
,
"CYP2A13"
,
"CYP2A6"
,
"CYP2A7"
,
"CYP2B6"
,
"CYP2B7P"
,
"CYP2C19"
,
"CYP2C9"
,
"CYP2D6"
,
"CYP2D7"
,
"DACH1"
,
"DDR1"
,
"DDR2"
,
"DDX3X"
,
"DDX54"
,
"DNMT3A"
,
"DPYD"
,
"DPYD-AS1"
,
"EGFR"
,
"EGFR-AS1"
,
"ERBB2"
,
"ERBB3"
,
"ERBB4"
,
"ERG"
,
"ESR1"
,
"EVI2A"
,
"EVI2B"
,
"EZH2"
,
"FBXW7"
,
"FGFR1"
,
"FGFR2"
,
"FGFR3"
,
"FGFR4"
,
"FLT1"
,
"FLT3"
,
"FLT4"
,
"FSTL5"
,
"GNA11"
,
"GNAQ"
,
"GNAS"
,
"GNAS-AS1"
,
"GSTP1"
,
"GTF2IP1"
,
"H3F3A"
,
"HNF1A"
,
"HRAS"
,
"IDH1"
,
"IDH2"
,
"IKZF1"
,
"IL1RAPL1"
,
"IL2RA"
,
"IL2RB"
,
"IL2RG"
,
"INPP4B"
,
"JAK1"
,
"JAK2"
,
"JAK3"
,
"KDM6A"
,
"KDR"
,
"KIT"
,
"KMT2A"
,
"KRAS"
,
"LAMA2"
,
"LCK"
,
"LOC100287072"
,
"LOC101928052"
,
"LPAR6"
,
"LTK"
,
"MAP2K1"
,
"MAP2K2"
,
"MAP2K4"
,
"MAP3K1"
,
"MAPK1"
,
"MED13"
,
"MEIKIN"
,
"MET"
,
"MGC32805"
,
"MGST2"
,
"MIR548AZ"
,
"MLH1"
,
"MPL"
,
"MST1R"
,
"MTOR"
,
"MTOR-AS1"
,
"MYC"
,
"MYD88"
,
"NELL2"
,
"NF1"
,
"NOTCH1"
,
"NPM1"
,
"NRAS"
,
"OMG"
,
"PDGFRA"
,
"PDGFRB"
,
"PHF6"
,
"PIK3CA"
,
"PIK3R1"
,
"PSMB1"
,
"PSMB2"
,
"PSMB5"
,
"PSMD1"
,
"PSMD2"
,
"PTCH1"
,
"PTEN"
,
"PTENP1"
,
"PTPN11"
,
"PVT1"
,
"RAF1"
,
"RARA"
,
"RARA-AS1"
,
"RARB"
,
"RARG"
,
"RB1"
,
"RET"
,
"ROS1"
,
"RPS6KB1"
,
"RUNDC3B"
,
"RUNX1"
,
"RXRA"
,
"RXRB"
,
"RXRG"
,
"SDCCAG8"
,
"SHH"
,
"SHOC2"
,
"SLC22A1"
,
"SLC22A2"
,
"SLC31A1"
,
"SLC34A2"
,
"SLC45A3"
,
"SLCO1B1"
,
"SMAD4"
,
"SMARCA4"
,
"SMARCB1"
,
"SMO"
,
"SNCAIP"
,
"SOS1"
,
"SPRED1"
,
"SRC"
,
"STK11"
,
"SUFU"
,
"TAS2R38"
,
"TET2"
,
"TMEM75"
,
"TMPRSS2"
,
"TP53"
,
"TPX2"
,
"TRRAP"
,
"TYK2"
,
"UGT1A9"
,
"UTY"
,
"VHL"
,
"WT1"
,
"YES1"
)
offt_vars
<-
subset
(
full.t.nomulti.noGerm
,
snpEff_GeneName
%in%
offt_gene
)
pdf
(
paste
(
out_dir
,
"Samples_Circos_Cancer_Genes.pdf"
,
sep
=
"/"
),
width
=
12
,
height
=
9
)
par
(
mfrow
=
c
(
3
,
4
))
for
(
gg
in
unique
(
offt_vars
$
Group
))
{
offt_vars_gg
<-
subset
(
offt_vars
,
Group
==
gg
)
print
(
gg
)
for
(
ss
in
unique
(
offt_vars_gg
$
Sample
))
{
plot_circos
(
t
=
offt_vars
,
sample
=
ss
)
}
}
legend_plot
(
t
=
offt_vars
,
sample
=
ss
)
dev.off
()
write.xlsx
(
x
=
list
(
"CancerGenes"
=
offt_vars
),
file
=
paste
(
out_dir
,
"Samples_Circos_Cancer_Genes.xlsx"
,
sep
=
"/"
))
offt_vars
<-
subset
(
samples.t.nomulti.noGerm
,
snpEff_GeneName
%in%
offt_gene
)
pdf
(
paste
(
out_dir
,
"Groups_Circos_Cancer_Genes.pdf"
,
sep
=
"/"
),
width
=
12
,
height
=
9
)
par
(
mfrow
=
c
(
2
,
2
))
for
(
gg
in
unique
(
offt_vars
$
Group
))
{
offt_vars_gg
<-
subset
(
offt_vars
,
Group
==
gg
)
offt_vars_gg
$
Sample
<-
gg
plot_circos
(
t
=
offt_vars_gg
,
sample
=
gg
)
}
legend_plot
(
t
=
offt_vars
,
sample
=
gg
)
dev.off
()
write.xlsx
(
x
=
list
(
"CancerGenes"
=
offt_vars
),
file
=
paste
(
out_dir
,
"Groups_Circos_Cancer_Genes.xlsx"
,
sep
=
"/"
))
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