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Merged
gaow merged 3 commits into from
Jan 20, 2026
Merged

compatible with pecotmr changes #1281

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c6cf971
compatible with pecotmr changes in twas context specification and fix…
rl3328 Jan 13, 2026
c2ce6ee
improves runtime and memory usage during method selection update
Chunmingl Jan 15, 2026
11a1e51
Merge pull request #1 from Chunmingl/dev
rl3328 Jan 16, 2026
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64 changes: 37 additions & 27 deletions code/pecotmr_integration/twas_ctwas.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -577,28 +577,32 @@
"\n",
"\n",
" # function to update method selection\n",
" update_twas_method <- function(twas_df){\n",
" update_twas_method <- function(twas_df, rsq_cutoff =${rsq_cutoff}, rsq_pval_cutoff = ${rsq_pval_cutoff}){\n",
" if (nrow(twas_df) == 0) { \n",
" return(twas_df)\n",
" } \n",
" twas_df$method_selected_original <- twas_df$is_selected_method\n",
" twas_df_colnames <- colnames(twas_df)\n",
" twas_df$gene_context <- paste0(twas_df$molecular_id, \"_\", twas_df$context)\n",
" rs_update <- do.call(rbind, lapply(unique(twas_df$gene_context), function(gene_context){\n",
" do.call(rbind, lapply(unique(twas_df$gwas_study), function(study){\n",
" df <- twas_df[twas_df$gene_context==gene_context & twas_df$gwas_study==study,,drop=FALSE]\n",
" df_colnames <- colnames(df)\n",
" all_imputable <- df[df$rsq_cv>=${rsq_cutoff} & df$pval_cv<=${rsq_pval_cutoff} & !is.na(df$twas_z),,drop=FALSE]\n",
" if (nrow(all_imputable)<=1 || all(is.na(all_imputable$twas_z))) {\n",
" return(df) # gene-context pair does not having any other imputable model available.\n",
" } else {\n",
" message (\"Updating method selection for \", gene_context, \"-\", study, \".\")\n",
" selected_method_update <- all_imputable[order(-all_imputable$rsq_cv),]$method[1]\n",
" df$selected_method_update <- df$method==selected_method_update\n",
" df$is_selected_method <- df$selected_method_update\n",
" df <- df[, df_colnames]\n",
" return(df)\n",
" }\n",
" }))\n",
" }))\n",
" return(rs_update[, twas_df_colnames])\n",
" fix_sel <- twas_df$is_selected_method & (is.na(twas_df$twas_z) | is.na(twas_df$twas_pval) | is.infinite(twas_df$twas_pval) |\n",
" is.null(twas_df$twas_z) | is.null(twas_df$twas_pval))\n",
" if (!any(fix_sel)) return(twas_df) # If nothing to fix, return fast\n",
" all_group <- paste(twas_df$gene_context, twas_df$gwas_study, sep = \" - \") #gene-context-study group\n",
" fix_groups <- unique(all_group[fix_sel])\n",
"\n",
" for (fixgroup in fix_groups) {\n",
" df_idxs <- which(all_group == fixgroup) # idx of gene-context-study group that needs replacement of method selected\n",
" if (length(df_idxs) == 1) next\n",
" candidate_idxs <- df_idxs[!is.na(twas_df$twas_z[df_idxs]) & !is.na(twas_df$twas_pval[df_idxs]) & !is.infinite(twas_df$twas_z[df_idxs]) & \n",
" !is.null(twas_df$twas_z[df_idxs]) & !is.null(twas_df$twas_pval[df_idxs]) &\n",
" twas_df$rsq_cv[df_idxs] >= rsq_cutoff & twas_df$pval_cv[df_idxs] <= rsq_pval_cutoff] \n",
" if (length(candidate_idxs) <= 0 || all(is.na(candidate_idxs))) next\n",
" best_i <- candidate_idxs[which.max(twas_df$rsq_cv[candidate_idxs])]\n",
" best_method <- twas_df$method[best_i]\n",
" twas_df$is_selected_method[df_idxs] <- (twas_df$method[df_idxs] == best_method)\n",
" message (\"Updating method selection for \", fixgroup, \".\")\n",
" }\n",
" return(twas_df[, twas_df_colnames])\n",
" }\n",
"\n",
" # Load metadata and configuration - let these fail if there are issues\n",
Expand Down Expand Up @@ -638,7 +642,7 @@
" message(paste(\"Error checking weight files:\", e$message))\n",
" return(list())\n",
" })\n",
" \n",
"\n",
" if(length(weight_db_list_update) <= 0) {\n",
" message(paste0(\"No valid weight files for region ${_filtered_region_info[3]}. Creating empty output files.\"))\n",
" # Define TWAS result columns (same as in final_results)\n",
Expand Down Expand Up @@ -677,15 +681,17 @@
" for (gene_db in names(weight_db_list_update)) {\n",
" weight_dbs <- weight_db_list_update[[gene_db]]\n",
" message(paste(\"Processing gene:\", gene_db, \"with\", length(weight_dbs), \"weight files\"))\n",
" \n",
" conditions = xqtl_meta_df |> filter(region_id == gene_db) |> pull(contexts)\n",
"\n",
" # Load weights for this gene - let it fail if there are real issues\n",
" twas_weights_results[[gene_db]] = load_twas_weights(\n",
" weight_dbs, \n",
" conditions = if(is.na(conditions)) NULL else conditions,\n",
" variable_name_obj = \"variant_names\", \n",
" susie_obj = \"susie_weights_intermediate\",\n",
" twas_weights_table = \"twas_weights\"\n",
" )\n",
" \n",
"\n",
" if (length(twas_weights_results[[gene_db]]) > 1) {\n",
" twas_weights_results[[gene_db]]$data_type <- setNames(\n",
" lapply(names(twas_weights_results[[gene_db]]$weights), function(context) {\n",
Expand Down Expand Up @@ -739,9 +745,7 @@
" # TWAS analysis - allow this to fail with informative errors\n",
" twas_results_db <- vector(\"list\", length(twas_weights_results)) \n",
" for (batch in seq_along(twas_weights_results)) {\n",
" \n",
" message(paste(\"Processing batch\", batch, \"of\", length(twas_weights_results)))\n",
" \n",
" res <- tryCatch(\n",
" twas_pipeline(\n",
" twas_weights_results[[batch]], \n",
Expand Down Expand Up @@ -802,10 +806,16 @@
" final_results <- do.call(rbind, lapply(twas_results_db, function(x) {\n",
" if (!is.null(x$twas_result)) x$twas_result[, c(2,1,14:16,3:13)] else data.frame()\n",
" }))\n",
"\n",
" # update methods if twas z-score is NA \n",
" final_results <- update_twas_method(final_results) \n",
" message(paste(\"Writing\", nrow(final_results), \"final TWAS results\"))\n",
" fwrite(final_results, ${_output[0]:r}, sep = \"\\t\", compress = \"gzip\")\n",
" final_results <- update_twas_method(final_results) \n",
" if (nrow(final_results)==0) {\n",
" message(\"No valid TWAS results to write\")\n",
" fwrite(data.frame(), file = ${_output[0]:r}, sep = \"\\t\", compress = \"gzip\")\n",
" } else {\n",
" message(paste(\"Writing\", nrow(final_results), \"final TWAS results\"))\n",
" fwrite(final_results, ${_output[0]:r}, sep = \"\\t\", compress = \"gzip\")\n",
" }\n",
" } else {\n",
" message(\"No valid TWAS results to write\")\n",
" fwrite(data.frame(), file = ${_output[0]:r}, sep = \"\\t\", compress = \"gzip\")\n",
Expand Down
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