From 0872c0967d6a73dfbfebd182feaed4f2da660948 Mon Sep 17 00:00:00 2001 From: rl3328 Date: Wed, 12 Nov 2025 15:49:48 +0000 Subject: [PATCH 1/2] add --finemap-extra-opts in univariate_analysis_pipeline --- code/mnm_analysis/mnm_methods/mnm_regression.ipynb | 2 ++ 1 file changed, 2 insertions(+) diff --git a/code/mnm_analysis/mnm_methods/mnm_regression.ipynb b/code/mnm_analysis/mnm_methods/mnm_regression.ipynb index f0947d3b3..3dabad6f2 100644 --- a/code/mnm_analysis/mnm_methods/mnm_regression.ipynb +++ b/code/mnm_analysis/mnm_methods/mnm_regression.ipynb @@ -993,6 +993,7 @@ " # fine-mapping results summary\n", " signal_cutoff = ${pip_cutoff},\n", " coverage = c(${\",\".join([str(x) for x in coverage])}),\n", + " finemapping_extra_opts = ${f\"list({finemapping_extra_opts})\" if finemapping_extra_opts else \"list(refine = TRUE)\"},\n", " # TWAS weights and CV for TWAS weights\n", " twas_weights = FALSE, \n", " max_cv_variants=${max_cv_variants},\n", @@ -1029,6 +1030,7 @@ " # fine-mapping results summary\n", " signal_cutoff = ${pip_cutoff},\n", " coverage = c(${\",\".join([str(x) for x in coverage])}),\n", + " finemapping_extra_opts = ${f\"list({finemapping_extra_opts})\" if finemapping_extra_opts else \"list(refine = TRUE)\"},\n", " # TWAS weights and CV for TWAS weights\n", " twas_weights = TRUE, \n", " max_cv_variants=${max_cv_variants},\n", From d9a92b69018f545c7422eaeef39f2be6334b854c Mon Sep 17 00:00:00 2001 From: rl3328 Date: Wed, 12 Nov 2025 18:35:18 +0000 Subject: [PATCH 2/2] update the finemapping-extra-opts --- code/mnm_analysis/mnm_methods/mnm_regression.ipynb | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/code/mnm_analysis/mnm_methods/mnm_regression.ipynb b/code/mnm_analysis/mnm_methods/mnm_regression.ipynb index 3dabad6f2..f57c1f5be 100644 --- a/code/mnm_analysis/mnm_methods/mnm_regression.ipynb +++ b/code/mnm_analysis/mnm_methods/mnm_regression.ipynb @@ -555,6 +555,8 @@ "# to determine if follow up analysis will be continued or to simply return NULL\n", "# If this is negative we use a default way to determine this cutoff which is conservative but still useful\n", "parameter: skip_analysis_pip_cutoff = []\n", + "# Modify Finemapping parameters\n", + "parameter: finemapping_extra_opts = \"\"\n", "# Skip fine-mapping\n", "parameter: skip_fine_mapping = False\n", "# Skip TWAS weights computation\n", @@ -993,7 +995,7 @@ " # fine-mapping results summary\n", " signal_cutoff = ${pip_cutoff},\n", " coverage = c(${\",\".join([str(x) for x in coverage])}),\n", - " finemapping_extra_opts = ${f\"list({finemapping_extra_opts})\" if finemapping_extra_opts else \"list(refine = TRUE)\"},\n", + " finemapping_extra_opts = ${finemapping_extra_opts if finemapping_extra_opts else \"list(refine = TRUE)\"},\n", " # TWAS weights and CV for TWAS weights\n", " twas_weights = FALSE, \n", " max_cv_variants=${max_cv_variants},\n", @@ -1030,7 +1032,7 @@ " # fine-mapping results summary\n", " signal_cutoff = ${pip_cutoff},\n", " coverage = c(${\",\".join([str(x) for x in coverage])}),\n", - " finemapping_extra_opts = ${f\"list({finemapping_extra_opts})\" if finemapping_extra_opts else \"list(refine = TRUE)\"},\n", + " finemapping_extra_opts = ${finemapping_extra_opts if finemapping_extra_opts else \"list(refine = TRUE)\"},\n", " # TWAS weights and CV for TWAS weights\n", " twas_weights = TRUE, \n", " max_cv_variants=${max_cv_variants},\n",