Fix tutorial tables.

monarch-initiative · Sep 28, 2023 · a648a89 · a648a89
1 parent 8f5b83d
commit a648a89
Showing 1 changed file with 8 additions and 8 deletions.
diff --git a/docs/tutorial.rst b/docs/tutorial.rst
@@ -64,10 +64,10 @@ For instance, we can partition the patients into two groups based on presence/ab
   >>> frameshift = cohort_analysis.compare_by_variant_type(VariantEffect.FRAMESHIFT_VARIANT)
   >>> frameshift # doctest: +NORMALIZE_WHITESPACE
                               With frameshift_variant         Without frameshift_variant
-                                                Count Percent                       Count Percent  p-value
-  HP:0001166 (Arachnodactyly)                       4  30.77%                          10  76.92%  0.04718
-  HP:0001250 (Seizure)                             11  84.62%                           9  69.23%  0.64472
-  HP:0001257 (Spasticity)                           8  61.54%                           9  69.23%  1.00000
+                                                Count Percent                      Count Percent  p-value Corrected p-values
+  HP:0001166 (Arachnodactyly)                       4  30.77%                         10  76.92%  0.04718            0.14154
+  HP:0001250 (Seizure)                             11  84.62%                          9  69.23%  0.64472            1.00000
+  HP:0001257 (Spasticity)                           8  61.54%                          9  69.23%  1.00000            1.00000
 
 
 Or perform similar partitioning based on presence/absence of a *missense* variant:
@@ -77,10 +77,10 @@ Or perform similar partitioning based on presence/absence of a *missense* varian
   >>> missense = cohort_analysis.compare_by_variant_type(VariantEffect.MISSENSE_VARIANT)
   >>> missense # doctest: +NORMALIZE_WHITESPACE
                               With missense_variant         Without missense_variant
-                                              Count Percent                    Count Percent   p-value
-  HP:0001166 (Arachnodactyly)                    13  81.25%                        1  10.00%  0.000781
-  HP:0001257 (Spasticity)                        11  68.75%                        6  60.00%  0.692449
-  HP:0001250 (Seizure)                           12  75.00%                        8  80.00%  1.000000
+                                              Count Percent                    Count Percent   p-value Corrected p-values
+  HP:0001166 (Arachnodactyly)                    13  81.25%                        1  10.00%  0.000781           0.002342
+  HP:0001257 (Spasticity)                        11  68.75%                        6  60.00%  0.692449           1.000000
+  HP:0001250 (Seizure)                           12  75.00%                        8  80.00%  1.000000           1.000000
 
 
 The tables present the HPO terms that annotate the cohort members and report their counts and p values