From a648a89c1b79c5cc03253beca577bba95818fdb3 Mon Sep 17 00:00:00 2001 From: Daniel Danis Date: Thu, 28 Sep 2023 16:16:46 -0400 Subject: [PATCH] Fix tutorial tables. --- docs/tutorial.rst | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/docs/tutorial.rst b/docs/tutorial.rst index 8d40b993..9f42dcc1 100644 --- 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