imputation launcher class

impute_jass/impute_jass/__init__.py

 import impute_jass.ld_matrix as LD
 import impute_jass.stat_models as model
 import impute_jass.windows
+from impute_jass.imputation_launcher import imputation_launcher

impute_jass/impute_jass/imputation_launcher.py

+"""
+Function set to launch imputation on a complete chromosome or
+on the genome
+"""
+import glob
+from .windows import Ld_region_centered_window_imputation
+
+class imputation_launcher:
+
+    def __init__(self, window_size=10000):
+        self.imputation_style = "online"
+        self.window_size = window_size
+
+    def chromosome_imputation(self, chrom, Zscores, ref_panel, ld_folder):
+        """
+
+        """
+
+        ref_panel_file = "/mnt/atlas/PCMA/1._DATA/ImpG_refpanel/{0}.eur.1pct.bim".format(chrom)
+        #ref_panel = pd.read_csv(ref_panel_file, sep="\t", names=['chr', "nothing", 'pos', 'Ref_all', 'alt_all'], index_col = 1)
+
+        pattern = "{0}/{1}*.ld".format(ld_folder, chrom)
+        for LD_file in glob.glob(pattern):
+            print("processing Region: {0}".format(LD_file))
+
+            Zscores = Ld_region_centered_window_imputation(LD_file, ref_panel, Zscores, self.window_size)
+        return Zscores

impute_jass/impute_jass/windows.py

@@ -54,15 +54,13 @@ def prepare_Zscore_for_imputation(ref_panel, Zscores):
 def in_region(pos_vector, start, end):
     return ((start < pos_vector) & (pos_vector < end))
 
-def Ld_region_centered_window_imputation(LD_file, ref_panel_folder, Zscores, window_size, unknowns=pd.Series([])):
+def Ld_region_centered_window_imputation(LD_file, ref_panel, Zscores, window_size, unknowns=pd.Series([])):
     """
         Each missing Snp is imputed by known snp found in a window centered on the SNP to impute
         Argument
     """
     (chrom, start_ld_block, end_ld_block) = parse_region_position(LD_file)
 
-    ref_panel_file = "/mnt/atlas/PCMA/1._DATA/ImpG_refpanel/{0}.eur.1pct.bim".format(chrom)
-    ref_panel = pd.read_csv(ref_panel_file, sep="\t", names=['chr', "nothing", 'pos', 'Ref_all', 'alt_all'], index_col = 1)
 
     LD_mat = generate_sparse_matrix(LD_file, ref_panel)
 
@@ -79,9 +77,9 @@ def Ld_region_centered_window_imputation(LD_file, ref_panel_folder, Zscores, win
 
     for snp_unknown in unknowns:
         # Boundary of the centered_window
-
-        start_pos = max((ref_panel.loc[snp_unknown,'pos'] - window_size), start_ld_block)
-        end_pos = min(ref_panel.loc[snp_unknown,'pos'] + window_size, end_ld_block)
+        #print(((ref_panel.loc[snp_unknown,'pos'] - window_size), float(start_ld_block)))
+        start_pos = max((ref_panel.loc[snp_unknown,'pos'] - window_size), float(start_ld_block))
+        end_pos = min(ref_panel.loc[snp_unknown,'pos'] + window_size, float(end_ld_block))
         #print(snp_unknown, start_pos, end_pos, start_ld_block, end_ld_block)
 
         in_LD_reg_n_window =  in_region(Zscores.pos, start_pos, end_pos)
@@ -102,4 +100,5 @@ def Ld_region_centered_window_imputation(LD_file, ref_panel_folder, Zscores, win
         i = i+1
         if i%100 == 0:
             print("{0}\%".format(np.round(i/N_snp,4)))
+    print(Zscores.head(10))
     return Zscores.sort_values(by="pos")