From 0ca598c386b06bc5cecd5df26b25d16025711d6b Mon Sep 17 00:00:00 2001
From: hjulienne <hanna.julienne@gmail.com>
Date: Mon, 16 Sep 2019 16:11:56 +0100
Subject: [PATCH] change main
---
jass_preprocessing/__main__.py | 9 ++++++---
jass_preprocessing/map_gwas.py | 5 ++++-
2 files changed, 10 insertions(+), 4 deletions(-)
diff --git a/jass_preprocessing/__main__.py b/jass_preprocessing/__main__.py
index bee0a4f..ed42e4b 100644
--- a/jass_preprocessing/__main__.py
+++ b/jass_preprocessing/__main__.py
@@ -28,18 +28,21 @@ def launch_preprocessing(args):
Preprocessing GWAS dataset
"""
gwas_map = pd.read_csv(args.gwas_info, sep="\t", index_col=0)
+ print(gwas_map.head())
- for gwas_filename in gwas_map[['filename']]:
+ for gwas_filename in gwas_map.index:
+ print(gwas_filename)
+ print(gwas_map.columns)
tag = "{0}_{1}".format(gwas_map.loc[gwas_filename, 'consortia'],
gwas_map.loc[gwas_filename, 'outcome'])
print('processing GWAS: {}'.format(tag))
start = time.time()
- GWAS_link = jp.map_gwas.walkfs(args.gwas_folder, gwas_filename)[2]
+ GWAS_link = jp.map_gwas.walkfs(args.input_folder, gwas_filename)[2]
+
mapgw = jp.map_gwas.map_columns_position(GWAS_link, args.gwas_info)
gw_df = jp.map_gwas.read_gwas(GWAS_link, mapgw)
-
ref = pd.read_csv(args.ref_path, header=None, sep= "\t",
names =['chr', "pos", "snp_id", "ref", "alt", "MAF"],
index_col="snp_id")
diff --git a/jass_preprocessing/map_gwas.py b/jass_preprocessing/map_gwas.py
index 2b0816f..f3e8313 100644
--- a/jass_preprocessing/map_gwas.py
+++ b/jass_preprocessing/map_gwas.py
@@ -112,7 +112,7 @@ def map_columns_position(gwas_internal_link, GWAS_labels):
mapgw = pd.Series(label_position, index=reference_label)
mapgw = mapgw.loc[~mapgw.isna()].astype(int)
mapgw.sort_values(inplace=True)
- print(mapgw)
+
f.close()
return mapgw
@@ -128,6 +128,8 @@ def read_gwas( gwas_internal_link, column_map):
Return:
a pandas dataframe with missing value all equal to np.nan
"""
+ print("Reading file:")
+ print(gwas_internal_link)
fullGWAS = pd.read_csv(gwas_internal_link, delim_whitespace=True,
usecols = column_map.values, #column_dict['label_position'].keys(),
@@ -140,6 +142,7 @@ def read_gwas( gwas_internal_link, column_map):
'NA', 'NULL', 'NaN',
'nan', 'na', '.'])
+
fullGWAS = fullGWAS[~fullGWAS.index.duplicated(keep='first')]
#fullGWAS = convert_missing_values(fullGWAS)
--
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