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Paul Igor Costea
metaSNV
Commits
2e7332a1
Commit
2e7332a1
authored
Apr 25, 2017
by
Paul Costea
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Plain Diff
FST calculation added
parent
8f69707d
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-21
metaSNV_post.py
metaSNV_post.py
+13
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metaSNV_post.py
View file @
2e7332a1
...
...
@@ -338,47 +338,39 @@ def compute_diversity(ind, sample1, sample2):
# Apply the compute_diversity to all positions for a specific pairwise comparison
def
genetic_distance
(
sample1
,
sample2
):
temp_res
=
[
compute_diversity
(
ind
,
sample1
,
sample2
)
for
ind
in
list
(
sample1
.
index
.
levels
[
0
]
)]
temp_res
=
[
compute_diversity
(
ind
,
sample1
,
sample2
)
for
ind
in
set
(
list
(
sample1
.
index
)
)]
return
np
.
nansum
(
temp_res
)
def
computeAllDiv
(
args
):
print
"Computing diversities"
# Coverage
cov_perc
=
pd
.
read_table
(
args
.
percentage_file
,
skiprows
=
[
1
],
index_col
=
False
)
cov_perc
=
cov_perc
.
set_index
(
cov_perc
.
loc
[:,
'Unnamed: 0'
])
cov_perc
=
cov_perc
.
drop
(
'Unnamed: 0'
,
1
)
# Genome
bedfile_tab
=
pd
.
read_table
(
args
.
projdir
+
'/bed_header'
,
index_col
=
0
,
header
=
None
)
bed_index
=
[
i
.
split
(
'.'
)[
0
]
for
i
in
list
(
bedfile_tab
.
index
)]
bedfile_tab
=
bedfile_tab
.
set_index
(
pd
.
Index
(
bed_index
))
# Loop over species :
allFreq
=
glob
.
glob
(
args
.
projdir
+
'/filtered/pop/*.freq'
)
for
f
in
allFreq
:
# Get species name :
species
=
int
(
f
.
split
(
'/'
)[
-
1
].
split
(
'.'
)[
0
])
# Get species genome length
genome_length
=
bedfile_tab
.
loc
[
str
(
species
),
2
].
sum
()
# Read the freq table as data.frame
data
=
pd
.
read_table
(
f
,
index_col
=
0
,
na_values
=
[
'-1'
])
pre_index
=
[
i
.
split
(
':'
)
for
i
in
list
(
data
.
index
)]
# Setting index for each position
index1
=
[
item
[
0
]
+
':'
+
item
[
1
]
+
':'
+
item
[
2
]
for
item
in
pre_index
]
# Setting index for Non-synonymous vs Synonymous
index2
=
[
item
[
4
]
for
item
in
pre_index
]
indexes
=
[
index1
,
index2
]
index
=
pd
.
MultiIndex
.
from_arrays
(
indexes
,
names
=
[
'position'
,
'significance'
])
data
=
data
.
set_index
(
index
)
pos_index
=
[
item
[
0
]
+
':'
+
item
[
1
]
+
':'
+
item
[
2
]
for
item
in
pre_index
]
data
=
data
.
set_index
(
pd
.
Index
(
pos_index
))
# Correcting the coverage by the genome length observed in each pairwise comparison
correction_cov
=
[[
min
(
cov_perc
.
loc
[
species
,
i
],
cov_perc
.
loc
[
species
,
j
])
*
genome_length
/
100
for
i
in
data
.
columns
]
for
j
in
data
.
columns
]
dist
=
[[
genetic_distance
(
data
.
iloc
[:,
[
i
]],
data
.
iloc
[:,
[
j
]])
/
correction_cov
[
i
][
j
]
for
i
in
range
(
j
+
1
)]
for
j
in
range
(
len
(
data
.
columns
))]
dist
=
pd
.
DataFrame
(
dist
,
index
=
data
.
columns
,
columns
=
data
.
columns
)
correction_cov
=
[[(
min
(
cov_perc
.
loc
[
species
,
i
],
cov_perc
.
loc
[
species
,
j
])
*
genome_length
)
/
100
for
i
in
data
.
columns
]
for
j
in
data
.
columns
]
dist
=
[[
genetic_distance
(
data
.
iloc
[:,
[
i
]],
data
.
iloc
[:,
[
j
]])
/
correction_cov
[
j
][
i
]
for
i
in
range
(
j
+
1
)]
for
j
in
range
(
len
(
data
.
columns
))]
FST
=
[[(
1
-
(
dist
[
i
][
i
]
+
dist
[
j
][
j
])
/
(
2
*
dist
[
j
][
i
]))
for
i
in
range
(
j
+
1
)]
for
j
in
range
(
len
(
dist
))]
dist
=
pd
.
DataFrame
(
dist
,
index
=
data
.
columns
,
columns
=
data
.
columns
)
FST
=
pd
.
DataFrame
(
FST
,
index
=
data
.
columns
,
columns
=
data
.
columns
)
dist
.
to_csv
(
args
.
projdir
+
'/distances/'
+
'%s.diversity'
%
species
,
sep
=
'
\t
'
)
FST
.
to_csv
(
args
.
projdir
+
'/distances/'
+
'%s.FST'
%
species
,
sep
=
'
\t
'
)
if
__name__
==
"__main__"
:
# print("globals: {}".format(globals()))
...
...
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