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custom
casertanucera_leukemia2023
Commits
5af245d0
Commit
5af245d0
authored
Aug 04, 2023
by
Matteo Barcella
Browse files
updating AF comparison script
parent
aba1e70e
Changes
1
Show whitespace changes
Inline
Side-by-side
WES/AF_comparison.R
View file @
5af245d0
...
...
@@ -9,6 +9,7 @@ inputdata <- list()
for
(
mysample
in
c
(
"12_27_1"
,
"12_27_2"
,
"10_395_3"
,
"10_395_4"
))
{
inputdata
[[
"rawcall"
]][[
mysample
]]
<-
filter_variants_v3
(
infile
=
paste0
(
mysample
,
"_dbsnp_cc_cnc_dbnsfp_refseq_light_raw_filtered.fields.txt"
),
sampleid
=
mysample
,
dp
=
50
)
inputdata
[[
"passonly"
]][[
mysample
]]
<-
filter_variants_v3
(
infile
=
paste0
(
mysample
,
"_dbsnp_cc_cnc_dbnsfp_refseq_light.fields.txt"
),
sampleid
=
mysample
,
dp
=
50
)
}
source
(
file
=
"Compare_variants_AF_v3.R"
)
...
...
@@ -69,6 +70,48 @@ plot_grid(AF_density_raw[["12-27_miRNA_L"]], AF_density_raw[["12-27_miRNA_H"]],
nrow
=
2
)
dev.off
()
## PLOTTING PASS-ONLY
tmpdf_1_pass
<-
subset.data.frame
(
x
=
Comparison_12_27
$
passonly
$
unionannot
,
select
=
c
(
"AF_GFP_H"
),
subset
=
AF_GFP_H
>
0
)
tmpdf_2_pass
<-
subset.data.frame
(
x
=
Comparison_12_27
$
passonly
$
unionannot
,
select
=
c
(
"AF_GFP_L"
),
subset
=
AF_GFP_L
>
0
)
tmpdf_3_pass
<-
subset.data.frame
(
x
=
Comparison_10_395
$
passonly
$
unionannot
,
select
=
c
(
"AF_GFP_H"
),
subset
=
AF_GFP_H
>
0
)
tmpdf_4_pass
<-
subset.data.frame
(
x
=
Comparison_10_395
$
passonly
$
unionannot
,
select
=
c
(
"AF_GFP_L"
),
subset
=
AF_GFP_L
>
0
)
AF_density_pass
<-
list
()
AF_density_pass
[[
"12-27_miRNA_L"
]]
<-
ggplot
(
data
=
tmpdf_1_pass
,
mapping
=
aes
(
AF_GFP_H
))
+
ylim
(
0
,
300
)
+
geom_histogram
(
bins
=
50
,
fill
=
alpha
(
"#003366"
,
0.8
))
+
xlab
(
"miRNA_low"
)
+
theme
(
axis.text
=
element_text
(
size
=
14
),
legend.title
=
element_blank
())
+
ggtitle
(
"12-27_miRNA_L"
)
AF_density_pass
[[
"12-27_miRNA_H"
]]
<-
ggplot
(
data
=
tmpdf_2_pass
,
mapping
=
aes
(
AF_GFP_L
))
+
ylim
(
0
,
300
)
+
geom_histogram
(
bins
=
50
,
fill
=
alpha
(
"#fc2803"
,
0.8
))
+
xlab
(
"miRNA_high"
)
+
theme
(
axis.text
=
element_text
(
size
=
14
),
legend.title
=
element_blank
())
+
ggtitle
(
"12-27_miRNA_H"
)
AF_density_pass
[[
"10-395_miRNA_L"
]]
<-
ggplot
(
data
=
tmpdf_3_pass
,
mapping
=
aes
(
AF_GFP_H
))
+
ylim
(
0
,
300
)
+
geom_histogram
(
bins
=
50
,
fill
=
alpha
(
"#003366"
,
0.8
))
+
xlab
(
"miRNA_low"
)
+
theme
(
axis.text
=
element_text
(
size
=
14
),
legend.title
=
element_blank
())
+
ggtitle
(
"10-395_miRNA_L"
)
AF_density_pass
[[
"10-395_miRNA_H"
]]
<-
ggplot
(
data
=
tmpdf_4_pass
,
mapping
=
aes
(
AF_GFP_L
))
+
ylim
(
0
,
300
)
+
geom_histogram
(
bins
=
50
,
fill
=
alpha
(
"#fc2803"
,
0.8
))
+
xlab
(
"miRNA_high"
)
+
theme
(
axis.text
=
element_text
(
size
=
14
),
legend.title
=
element_blank
())
+
ggtitle
(
"10-395_miRNA_H"
)
png
(
filename
=
"AF_density_pass_variants.png"
,
width
=
8
,
height
=
6
,
units
=
"in"
,
res
=
300
)
plot_grid
(
AF_density_pass
[[
"12-27_miRNA_L"
]],
AF_density_pass
[[
"12-27_miRNA_H"
]],
AF_density_pass
[[
"10-395_miRNA_L"
]]
,
AF_density_pass
[[
"10-395_miRNA_H"
]],
nrow
=
2
)
dev.off
()
# Histograms with PASS or clustered_events
AF_density_mildfilt
<-
list
()
Mild_vars_12_27
<-
Comparison_12_27
$
rawcall
$
unionannot
...
...
@@ -81,6 +124,7 @@ tmpdf_1_mild <- subset.data.frame(x = Mild_vars_12_27, select = c("AF_GFP_H"),
tmpdf_2_mild
<-
subset.data.frame
(
x
=
Mild_vars_12_27
,
select
=
c
(
"AF_GFP_L"
),
subset
=
AF_GFP_L
>
0
&
(
FILTER_GFP_H_simple
==
"PASS"
|
FILTER_GFP_L_simple
==
"PASS"
)
&
!
HGVS_P
==
""
)
Mild_vars_10_395
<-
Comparison_10_395
$
rawcall
$
unionannot
Mild_vars_10_395
$
FILTER_GFP_H_simple
<-
ifelse
(
test
=
Mild_vars_10_395
$
FILTER_GFP_H
==
"PASS"
,
"PASS"
,
"NOPASS"
)
Mild_vars_10_395
$
FILTER_GFP_L_simple
<-
ifelse
(
test
=
Mild_vars_10_395
$
FILTER_GFP_L
==
"PASS"
,
"PASS"
,
"NOPASS"
)
...
...
@@ -221,6 +265,8 @@ df_2 <- subset.data.frame(x = raw_vars_12_27_2, subset = variantkey %in% mykeys,
colnames
(
df_2
)
<-
c
(
"variantkey"
,
"AF_GFP_L"
,
"DP_GFP_L"
,
"Gene"
,
"Effect"
,
"FILTER"
)
# modificare
union_df
<-
merge.data.frame
(
x
=
df_1
,
y
=
df_2
,
by
=
c
(
"variantkey"
,
"Gene"
,
"Effect"
),
all
=
T
)
...
...
@@ -255,4 +301,3 @@ print(ggplot(data = union_df_exonic, mapping = aes(x = AF_GFP_H, y = AF_GFP_L, l
geom_text_repel
(
size
=
3
,
show.legend
=
FALSE
,
segment.alpha
=
0.4
)
+
theme
(
plot.title
=
element_text
(
hjust
=
0.5
),
legend.title
=
element_blank
(),
legend.position
=
"none"
))
dev.off
()
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