diff --git a/doc/source/generating_joint_analysis.rst b/doc/source/generating_joint_analysis.rst
index 3c44f1f9861f158620a15172cd48c2a22fe95efa..dfa4f247d7df16f60091baf7276f4bd526c2178f 100644
--- a/doc/source/generating_joint_analysis.rst
+++ b/doc/source/generating_joint_analysis.rst
@@ -6,16 +6,38 @@ you can generate analysis for any combination
 and several joint tests with the command jass create-project-data
 (see command line usage for the detail of arguments).
 
-Whatever the test used, the command will generate three output:
+Genome-wide analysis
+--------------------
+
+Whatever the test used, the command will generate three main output:
 
 * A HDFStore containing several tables (Each table can be read from the HDFStore with the pandas.read_hdf function):
-  - 'SumStatTab' : The results of the joint analysis by SNPs
-  - 'PhenoList' : the meta data of analysed GWAS
-  - 'COV' : The H0 covariance used to perform joint analysis
-  - 'Regions' : Results of the joint analysis summarised by LD regions
+	- 'SumStatTab' : The results of the joint analysis by SNPs
+	- 'PhenoList' : the meta data of analysed GWAS
+	- 'COV' : The H0 covariance used to perform joint analysis
+	- 'Regions' : Results of the joint analysis summarised by LD regions
 * A .png Manhattan plot
 * A .png Quadrant plot which is a scatter plot of the minimum p-value by region of the joint test with respect to the minimum p-value by region of the univariate tests.
 
+You can also get: 
+	- The multi-phenotype analysis results file in CSV format,
+	- A png image of the quantile-quantile plot (qq-plot) that shows the validity of the results by comparing the distribution of SNP results to the theoretical distribution.
+
+Analysis by region
+------------------
+
+To perform an analysis by region (local analysis) you must give the chromosome number and the start and end of the region to be studied.
+
+Whatever the test used, the command will generate three output:
+
+* A HDFStore containing several tables (Each table can be read from the HDFStore with the pandas.read_hdf function):
+	- 'SumStatTab' : The results of the joint analysis by SNPs for the interval [start-end] chosen by the user
+	- 'PhenoList' : the meta data of analysed GWAS
+	- 'COV' : The H0 covariance used to perform joint analysis
+	- 'Regions' : Results of the joint analysis summarised by LD regions (only for the interval [start-end] chosen by the user)
+	- 'gene_exon' : Genes label, start and end position, direction, biotype. Exons label, start and end position, associated gene. (the genes and exons data are available only for the interval [start-end] chosen by the user)
+* A .png zoom plot (Manhattan plot restricted to the interval [start-end] chosen by the user) 
+* The multi-phenotype local analysis results file in CSV format
 
 The Omnibus tests
 -----------------