Small correction in documentation

doc/source/index.rst

@@ -94,6 +94,7 @@ The raiss package outputs imputed GWAS files in the tabular format:
 |   snp_ids   | position | Ref_allele | Alt_allele | z_score |  Var  | ld_score |
 +=============+==========+============+============+=========+=======+==========+
 |  rs3802985  |  198510  |      T     |      C     |  0.334  | -1.0  |   -1.0   |
++-------------+----------+------------+------------+---------+-------+----------+
 | rs111876722 |  201922  |      C     |      T     |  0.297  |	0.16 |  5.412   |
 +-------------+----------+------------+------------+---------+-------+----------+
 

raiss/imputation_R2.py

@@ -76,7 +76,7 @@ def z_amplitude_effect(zscore_folder, masked_folder, output_folder, ref_folder,
         z_treshold (list) : float list to select Z score to mask above Z score
         eigen_ratio (float): rcond parameter (must be between 0 and 1)
         window_size, buffer_size, l2_regularization, R2_threshold : imputation parameter (see raiss command line documentation)
-        N_to_mask (int): Number of SNPs masked in the initial dataset to compute the correlation between true value and imputed value
+        ratio_to_mask (int): the fraction of SNPs above the z_threshold to mask in the initial dataset to compute the correlation between true value and imputed value
     """
     z_file = "{0}/z_{1}_{2}.txt".format(zscore_folder, gwas, chrom)
     zscore = pd.read_csv(z_file, index_col=0, sep="\t")