Merge branch 'master' into 'dev'

# Conflicts:
#   jass/models/worktable.py
#   jass/static/index.html

doc/Makefile

@@ -17,4 +17,4 @@ help:
 # Catch-all target: route all unknown targets to Sphinx using the new
 # "make mode" option.  $(O) is meant as a shortcut for $(SPHINXOPTS).
 %: Makefile
-	@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
\ No newline at end of file
+	@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)

jass/models/inittable.py

@@ -7,7 +7,7 @@ Created on Tue Mar 28 09:57:33 2017
 import os
 import glob
 import logging
-from pandas import HDFStore, DataFrame, read_csv, concat, options
+from pandas import HDFStore, DataFrame, read_csv, concat, options, read_hdf
 
 # create (or open) an hdf5 file and opens in append mode
 import numpy as np
@@ -129,25 +129,24 @@ def format_chr_gwas(gwas_file_chri, chrom, study_name, regions_bychr):
         (z_gwas.loc[ind, "MiddlePosition"]) = (left + right) / 2
     return(z_gwas)
 
-def compute_covariance_zscore(init_table_path):
+def compute_covariance_zscore(init_file_path):
     print("## Compute covariance ##")
-    sum_stat_jost_tab = pd.read_hdf(init_file_path, 'SumStatTab', where='Region >= {0} and Region < {1}'.format(0, 3))
+    sum_stat_jost_tab = read_hdf(init_file_path, 'SumStatTab', where='Region >= {0} and Region < {1}'.format(0, 3))
     trait = [i for i in sum_stat_jost_tab.columns if i[:2]=="z_"]
 
-    NSNP_matrix = pd.DataFrame(index=trait, columns=trait)
-    cov_matrix = pd.DataFrame(index=trait, columns=trait)
+    NSNP_matrix = DataFrame(index=trait, columns=trait)
+    cov_matrix = DataFrame(index=trait, columns=trait)
 
     cov_matrix.fillna(0, inplace=True)
     NSNP_matrix.fillna(0, inplace=True)
 
     bi = range(0,1751,50)
-    start = timeit.timeit()
     n_len = len(bi)-1
 
     for i in range(n_len):
         binf = bi[i]
         bsup = bi[(i+1)]
-        sum_stat_jost_tab = pd.read_hdf(init_file_path, 'SumStatTab', where='Region >= {0} and Region < {1}'.format(binf, bsup))
+        sum_stat_jost_tab = read_hdf(init_file_path, 'SumStatTab', where='Region >= {0} and Region < {1}'.format(binf, bsup))
 
         print("Regions {0} to {1}\r".format(binf, bsup))
         j = 0
@@ -162,10 +161,9 @@ def compute_covariance_zscore(init_table_path):
                 cov_matrix.loc[tr2,tr1] += cc.iloc[:,0].dot(cc.iloc[:,1])
                 NSNP_matrix.loc[tr2,tr1] += cc.shape[0]
             j=j+1
-    end = timeit.timeit()
-    print(end-start)
+
     #(cov_matrix/NSNP_matrix).to_csv("Covariance_on_Zscores.csv", sep="\t")
-    hdf_init = pd.HDFStore(init_table_path)
+    hdf_init = HDFStore(init_file_path)
     hdf_init.put("COV", (cov_matrix/NSNP_matrix), format="table", data_columns=True)
     hdf_init.close()
 
@@ -224,7 +222,7 @@ def create_inittable_file(
     which_cols.extend(list(pheno_select))
     hdf_init.put("PhenoList", pheno_list, format="table", data_columns=True)
     hdf_init.put("Regions", regions, format="table", data_columns=True)
-    sum_stat_tab_min_itemsizes = {"snp_ids": 50}
+    sum_stat_tab_min_itemsizes = {"snp_ids": 80, "Ref_allele":70,"Alt_allele":70}
 
     regions_bychr = regions.groupby("chr")
 
@@ -302,6 +300,7 @@ def create_inittable_file(
             check_if_SNP_unique(z_gwas_chrom)
 
             sum_stat_tab = z_gwas_chrom[which_cols]
+
             hdf_init.append(
                 "SumStatTab",
                 sum_stat_tab,
@@ -312,4 +311,4 @@ def create_inittable_file(
 
     if compute_covariance:
         print("Compute Covariance from Zscores")
-        compute_covariance_zscore(hdf_init = init_table_path)
+        compute_covariance_zscore(init_table_path)