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Merged
gaow merged 6 commits into from
May 31, 2026
Merged

Update colocboost and univariate pipeline (very few changes) #1324

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529090c
Update colocboost.ipynb
xueweic May 24, 2026
6ecfcd1
Update mnm_regression.ipynb
xueweic May 30, 2026
1e59f74
Update mnm_regression.ipynb
xueweic May 30, 2026
69849ce
Update mnm_regression.ipynb
xueweic May 30, 2026
3761ad0
Update mnm_regression.ipynb
xueweic May 30, 2026
5ae771f
Update mnm_regression.ipynb
xueweic May 31, 2026
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38 changes: 19 additions & 19 deletions code/mnm_analysis/mnm_methods/colocboost.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -291,7 +291,9 @@
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Multi-ancestry: per-study LD reference specified in gwas_meta_multi.tsv\n",
"sos run pipeline/colocboost.ipynb colocboost \\\n",
Expand All @@ -306,9 +308,7 @@
" --separate-gwas --xqtl-coloc \\\n",
" --region-name ENSG00000239945 \\\n",
" --phenotype-names trait_A\n"
],
"outputs": [],
"execution_count": null
]
},
{
"cell_type": "markdown",
Expand Down Expand Up @@ -1182,7 +1182,7 @@
},
{
"cell_type": "code",
"execution_count": 1,
"execution_count": null,
"metadata": {
"kernel": "SoS",
"tags": []
Expand Down Expand Up @@ -1350,21 +1350,21 @@
" \n",
" # - analysis parameters\n",
" region_info = list(region_coord=parse_region(\"${_meta_info[0]}\"), grange=parse_region(\"${_meta_info[1]}\"), region_name=region_name)\n",
" res <- colocboost_analysis_pipeline(region_data = fdat, \n",
" event_filters = event_filters,\n",
" # - analysis\n",
" xqtl_coloc = xqtl_coloc,\n",
" joint_gwas = joint_gwas,\n",
" separate_gwas = separate_gwas,\n",
" # - individual QC\n",
" maf_cutoff = maf_cutoff, \n",
" pip_cutoff_to_skip_ind = pip_cutoff_to_skip_ind,\n",
" # - sumstat QC\n",
" pip_cutoff_to_skip_sumstat = pip_cutoff_to_skip_sumstat,\n",
" keep_indel = keep_indel,\n",
" qc_method = qc_method,\n",
" impute = impute, \n",
" impute_opts = impute_opts)\n",
" res <- colocboost_pipeline(region_data = fdat, \n",
" event_filters = event_filters,\n",
" # - analysis\n",
" xqtl_coloc = xqtl_coloc,\n",
" joint_gwas = joint_gwas,\n",
" separate_gwas = separate_gwas,\n",
" # - individual QC\n",
" maf_cutoff = maf_cutoff, \n",
" pip_cutoff_to_skip_ind = pip_cutoff_to_skip_ind,\n",
" # - sumstat QC\n",
" pip_cutoff_to_skip_sumstat = pip_cutoff_to_skip_sumstat,\n",
" keep_indel = keep_indel,\n",
" qc_method = qc_method,\n",
" impute = impute, \n",
" impute_opts = impute_opts)\n",
"\n",
" # Reorganize outputs\n",
" computing_time <- c(computing_time, res$computing_time)\n",
Expand Down
25 changes: 16 additions & 9 deletions code/mnm_analysis/mnm_methods/mnm_regression.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -944,7 +944,7 @@
" region_name = \"${_meta_info[2]}\"\n",
" }\n",
"\n",
" region_info = list(region_coord=parse_region(\"${_meta_info[0]}\"), grange=parse_region(\"${_meta_info[1]}\"), region_name=region_name)\n",
" region_info = list(region_coord=parse_region(\"${_meta_info[0]}\"), analysis_region = \"${_meta_info[1]}\", grange=parse_region(\"${_meta_info[1]}\"), region_name=region_name)\n",
"\n",
" finemapping_result = list()\n",
" preset_variants_result = list()\n",
Expand Down Expand Up @@ -979,7 +979,8 @@
" X_scalar=fdat$residual_X_scalar[[r]], \n",
" Y_scalar=if (fdat$residual_Y_scalar[[r]] == 1) 1 else fdat$residual_Y_scalar[[r]][,i,drop=FALSE],\n",
" X_variance=fdat$X_variance[[r]],\n",
" other_quantities = list(dropped_samples = dropped_samples),\n",
" region = region_info$analysis_region,\n",
" other_quantities = list(dropped_samples = dropped_samples, condition_id = names(fdat$residual_Y)[r]),\n",
" # filters\n",
" imiss_cutoff = ${imiss},\n",
" maf_cutoff = NULL,\n",
Expand Down Expand Up @@ -1014,7 +1015,8 @@
" X_scalar=fdat$residual_X_scalar[[r]], \n",
" Y_scalar=if (fdat$residual_Y_scalar[[r]] == 1) 1 else fdat$residual_Y_scalar[[r]][,i,drop=FALSE],\n",
" X_variance=fdat$X_variance[[r]],\n",
" other_quantities = list(dropped_samples = dropped_samples),\n",
" region = region_info$analysis_region,\n",
" other_quantities = list(dropped_samples = dropped_samples, condition_id = names(fdat$residual_Y)[r]),\n",
" # filters\n",
" imiss_cutoff = ${imiss},\n",
" maf_cutoff = ${min_twas_maf},\n",
Expand Down Expand Up @@ -1232,7 +1234,7 @@
"\n",
" context_regions <- list(${\",\".join([(\"c('\"+x+\"')\") if isinstance(x, str) else (\"c\"+ str(x)) for x in _meta_info[3]])})\n",
" names(context_regions) <- colnames(fdat$residual_Y)\n",
" region_info = list(region_coord=parse_region(\"${_meta_info[0]}\"), grange=parse_region(\"${_meta_info[1]}\"), region_name=region_name)\n",
" region_info = list(region_coord=parse_region(\"${_meta_info[0]}\"), analysis_region = \"${_meta_info[1]}\", grange=parse_region(\"${_meta_info[1]}\"), region_name=region_name)\n",
"\n",
" dd_prior <- if (${mixture_prior:r} == '.' || ${mixture_prior:r} == '') NULL else readRDS(${mixture_prior:r})\n",
" dd_prior_cv <- if (${mixture_prior_cv:r} == '.' || ${mixture_prior_cv:r} == '') NULL else readRDS(${mixture_prior_cv:r})\n",
Expand All @@ -1244,6 +1246,7 @@
" Y = fdat$residual_Y,\n",
" maf = fdat$maf,\n",
" X_variance = fdat$X_variance,\n",
" region = region_info$analysis_region,\n",
" other_quantities = list(dropped_samples = fdat$dropped_samples),\n",
" # filters\n",
" imiss_cutoff = ${imiss}, \n",
Expand Down Expand Up @@ -1414,14 +1417,14 @@
" gene_id <- names(combined_list[[\"extracted_regional_window_combined_susie_result\"]][[condition_name]])[i]\n",
" \n",
" # Extract top_loci variants\n",
" variants1 <- unique(susie_result_1[[\"top_loci\"]][[\"variant_id\"]])\n",
" variants1 <- unique(susie_result_1[[\"top_loci\"]][[\"variant\"]])\n",
" if (length(variants1) > 0) {\n",
" different_in_all_genes <- TRUE\n",
" \n",
" for (j in 1:length(combined_list[[\"extracted_regional_window_combined_susie_result\"]][[condition_name]])) {\n",
" if (i != j) {\n",
" susie_result_2 <- combined_list[[\"extracted_regional_window_combined_susie_result\"]][[condition_name]][[j]]\n",
" variants2 <- unique(susie_result_2[[\"top_loci\"]][[\"variant_id\"]])\n",
" variants2 <- unique(susie_result_2[[\"top_loci\"]][[\"variant\"]])\n",
" \n",
" # Compare variants\n",
" if (length(variants2) > 0) {\n",
Expand Down Expand Up @@ -1515,7 +1518,7 @@
" region_name = \"${_meta_info[2]}\"\n",
" }\n",
"\n",
" region_info = list(region_coord=parse_region(\"${_meta_info[0]}\"), grange=parse_region(\"${_meta_info[1]}\"), region_name=region_name)\n",
" region_info = list(region_coord=parse_region(\"${_meta_info[0]}\"), analysis_region = \"${_meta_info[1]}\", grange=parse_region(\"${_meta_info[1]}\"), region_name=region_name)\n",
" \n",
" dd_prior <- NULL\n",
" if (${\"TRUE\" if data_driven_prior else \"FALSE\"}) {\n",
Expand All @@ -1532,6 +1535,7 @@
" Y=fdat$residual_Y[,filtered_event_names],\n",
" maf=fdat$maf,\n",
" X_variance = fdat$X_variance,\n",
" region = region_info$analysis_region,\n",
" other_quantities = list(dropped_samples = fdat$dropped_samples),\n",
" # filters\n",
" imiss_cutoff = ${imiss}, \n",
Expand Down Expand Up @@ -1664,6 +1668,7 @@
" }\n",
" \n",
" fitted = setNames(replicate(length(fdat$residual_Y), list(), simplify = FALSE), names(fdat$residual_Y))\n",
" region_info = list(region_coord=parse_region(\"${_meta_info[0]}\"), analysis_region = \"${_meta_info[1]}\", grange=parse_region(\"${_meta_info[1]}\"), region_name=\"${_meta_info[2]}\")\n",
" for (r in 1:length(fitted)) {\n",
" st = proc.time()\n",
" fitted[[r]] = list()\n",
Expand All @@ -1684,6 +1689,7 @@
" data_x = fdat$residual_X[[r]], data_y = top_pc_data[,i],\n",
" X_scalar = fdat$residual_X_scalar[[r]], y_scalar = 1, maf = fdat$maf[[r]],\n",
" coverage = ${coverage[0]}, secondary_coverage = c(${\",\".join([str(x) for x in coverage[1:]])}), signal_cutoff = ${pip_cutoff},\n",
" region = region_info$analysis_region,\n",
" other_quantities = list(dropped_samples = list(X=fdat$dropped_sample$dropped_samples_X[[r]], \n",
" y=fdat$dropped_sample$dropped_samples_Y[[r]], \n",
" covar=fdat$dropped_sample$dropped_samples_covar[[r]]))),\n",
Expand Down Expand Up @@ -1722,11 +1728,12 @@
" data_x = fdat$residual_X[[r]], data_y = NULL,\n",
" X_scalar = fdat$residual_X_scalar[[r]], y_scalar = 1, maf = fdat$maf[[r]],\n",
" coverage = ${coverage[0]}, secondary_coverage = c(${\",\".join([str(x) for x in coverage[1:]])}), signal_cutoff = ${pip_cutoff},\n",
" region = region_info$analysis_region,\n",
" other_quantities = list(dropped_samples = list(X=fdat$dropped_sample$dropped_samples_X[[r]], y=fdat$dropped_sample$dropped_samples_Y[[r]], \n",
" covar=fdat$dropped_sample$dropped_samples_covar[[r]]))),\n",
" primary_method = \"fsusie\")\n",
" fitted[[r]]$total_time_elapsed = proc.time() - st\n",
" fitted[[r]]$region_info = list(region_coord=parse_region(\"${_meta_info[0]}\"), grange=parse_region(\"${_meta_info[1]}\"), region_name=\"${_meta_info[2]}\")\n",
" fitted[[r]]$region_info = region_info\n",
" # original data no longer relevant, set to NA to release memory\n",
" fdat$residual_X[[r]] <- NA\n",
" fdat$residual_Y[[r]] <- NA\n",
Expand Down Expand Up @@ -1827,4 +1834,4 @@
},
"nbformat": 4,
"nbformat_minor": 4
}
}