diff --git a/doc/source/index.rst b/doc/source/index.rst
index cae2a933ad3eb48b1c6feb59726ffcd381001f59..85f30e71d7ac6c4c18ff7378c1e28a7640b5e45d 100644
--- a/doc/source/index.rst
+++ b/doc/source/index.rst
@@ -97,11 +97,11 @@ Input
 Note that the combination of Consortium and outcome must be unique because it will be used as an index in the cleaning process.
 
 Here is an example of descriptor field, the field irrelevant (for example odd ratio for continuous trait) for the study must be filled with na.
-
+Some fields are optional like the imputation_quality. If not used they can be filled with na. 
 .. csv-table:: GWAS information table!
 
-   :header: "filename","consortia","outcome","fullName","type","Nsample","Ncase","Ncontrol","Nsnp","snpid","a1","a2","freq","pval","n","z","OR","se","code","imp","ncas","ncont"
-   "GIANT_HEIGHT_Wood_et_al.txt","GIANT","HEIGHT","Height","Anthropometry",253288,	na,	na, 2550858,	"MarkerName",	"Allele1", "Allele2", "Freq.Allele1.HapMapCEU","p","N","b",na,"SE",na,na,na,na
+   :header: "filename","consortia","outcome","fullName","type","Nsample","Ncase","Ncontrol","Nsnp","snpid","a1","a2","freq","pval","n","z","OR","se","code","imp","ncas","ncont","imputation_quality"
+   "GIANT_HEIGHT_Wood_et_al.txt","GIANT","HEIGHT","Height","Anthropometry",253288,	na,	na, 2550858,	"MarkerName",	"Allele1", "Allele2", "Freq.Allele1.HapMapCEU","p","N","b",na,"SE",na,na,na,na, "imputationInfo"
 
 
 Command line usage example:
diff --git a/jass_preprocessing/map_gwas.py b/jass_preprocessing/map_gwas.py
index 9d4c94de779df05a1b838c02db05df670c3e1204..0fb853450ec16deb81e4e51e377f6b532e084cf0 100644
--- a/jass_preprocessing/map_gwas.py
+++ b/jass_preprocessing/map_gwas.py
@@ -169,7 +169,7 @@ def read_gwas( gwas_internal_link, column_map, imputation_treshold=None):
 
     print(fullGWAS.head())
     if imputation_treshold:
-        fullGWAS = fullGWAS.loc[fullName.imputation_quality > imputation_treshold]
+        fullGWAS = fullGWAS.loc[fullGWAS.imputation_quality > imputation_treshold]
     fullGWAS = fullGWAS[~fullGWAS.index.duplicated(keep='first')]
     #fullGWAS = convert_missing_values(fullGWAS)