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Statistical-Genetics
JASS_suite_pipeline
Commits
d1a8d71b
Commit
d1a8d71b
authored
2 years ago
by
Hanna JULIENNE
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add script to compile chromosome panel into a GW panel
parent
24a5de55
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Raiss report integration
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modules/GW_reference_panels.nf
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d1a8d71b
/*
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
JASS suite pipeline
authors : Hanna Julienne, Hervé Ménager & Lucie Troubat
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
*/
/* Parameter to set if optional pipeline steps are performed */
params
.
compute_project
=
false
/* path of input data */
params
.
ref_panel
=
'/pasteur/zeus/projets/p02/GGS_WKD/DATA_1000G/Panels/EAS/'
params
.
region
=
'/pasteur/zeus/projets/p02/GGS_WKD/DATA_1000G/Panels/Regions_LD/EAS/All_Regions_ALL_ensemble_1000G_hg38_EAS.bed'
params
.
output_folder
=
"${launchDir}"
params
.
ancestry
=
"EAS"
params
.
prefix
=
"ALL_ensemble_1000G_hg38_EAS_chr"
params
.
prefix_Impute_GWAS
=
"ALL_ensemble_1000G_hg38_EAS_"
params
.
suffix
=
""
chr_channel
=
Channel
.
from
(
1
..
22
)
ref_chr_channel
=
Channel
.
fromPath
(
params
.
ref_panel
+
"/ALL_ensemble_1000G_hg38_EAS_chr*.bim"
)
ref_chr_channel2
=
Channel
.
fromPath
(
params
.
ref_panel
+
"/ALL_ensemble_1000G_hg38_EAS_chr*.bim"
)
ref_chr_channel3
=
Channel
.
fromPath
(
params
.
ref_panel
+
"/ALL_ensemble_1000G_hg38_EAS_chr*.*"
)
process
Compute_MAF
{
input:
file
ref_panel
from
ref_chr_channel3
.
collect
()
val
chr
from
chr_channel
output:
file
"*.frq"
into
MAF_channel
"""
echo "Compute_MAF"
bfile="${params.prefix}${chr}${params.suffix}"
echo \$bfile
plink --bfile \${bfile} --freq --out ./chr${chr}
"""
}
process
create_WG_reference_panel
{
publishDir
"${launchDir}/Ref_Panel"
,
pattern:
"*.csv"
,
mode:
'copy'
input:
file
maf_files
from
MAF_channel
.
collect
()
file
chr_files
from
ref_chr_channel
.
collect
()
output:
file
"1000G_${params.ancestry}_0_01.csv"
into
ref_panel_wg_channel
"""
#!/usr/bin/env python3
import subprocess as sub
import pandas as pd
import os
cwd = os.getcwd()
print(cwd)
pref="${params.prefix}"
suf="${params.suffix}"
refchr_list = []
for chrom in range(1,23):
fi = "{0}{1}{2}.bim".format(pref,chrom,suf)
print(fi)
print(type(fi))
position = pd.read_csv(fi, sep='\t', names=['chr', "rsid", "?", "pos", "ref_al", "alt_al"])
position.set_index("rsid", inplace=True)
ref_chr = pd.read_csv("./chr{0}.frq".format(chrom), sep="\\s+")
ref_chr['pos'] = position.loc[ref_chr.SNP, "pos"].values
refchr_list.append(ref_chr[["CHR", "pos", "SNP", "A1", "A2", "MAF"]])
ref= pd.concat(refchr_list)
ref.loc[~(ref.A1+ref.A2).isin(["AT", 'TA','CG','GC'])][["CHR","SNP", "MAF", "pos", "A1", "A2"]].to_csv("1000G_${params.ancestry}_0_01.csv", index=False, header=False, sep="\t")
"""
}
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