Comparing different settings in multi-group analysis

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Last updated: 2025-04-16

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---

Introduction

Settings are:

• THINS = [“0.1”,“0.5”,“1”]
• GROUP_PRIOR_VAR_STRUCTURES = [“shared_all”, “shared_type”]
• NUMBER_OF_SIGNALS = [“1”,“5”]
• WITH_ST = [“with_ST”, “without_ST”,“with_susieST”]

library(ctwas)
library(ggplot2)
library(dplyr)
library(tidyr)
library(scales)

source("/project/xinhe/xsun/multi_group_ctwas/data/samplesize.R")

mapping_predictdb <- readRDS("/project2/xinhe/shared_data/multigroup_ctwas/weights/mapping_files/PredictDB_mapping.RDS")
mapping_munro <- readRDS("/project2/xinhe/shared_data/multigroup_ctwas/weights/mapping_files/Munro_mapping.RDS")
mapping_two <- rbind(mapping_predictdb,mapping_munro)

traits_silver <- c("T2D","LDL","BMI","RBC","IBD","SCZ","aFib")
names(traits_silver) <- c("T2D-panukb","LDL-ukb-d-30780_irnt","BMI-panukb","RBC-panukb","IBD-ebi-a-GCST004131","SCZ-ieu-b-5102","aFib-ebi-a-GCST006414")


folder_results_old <- "/project/xinhe/shengqian/ctwas_GWAS_analysis/snakemake_outputs/"
folder_results_susieST <- "/project/xinhe/xsun/multi_group_ctwas/15.susie_weights/snakemake_outputs/"

thins <- c("0.1", "0.5", "1")
var_strucs <- c("shared_all", "shared_type")
Ls <- c("5","1")
sts <- c("without_ST","with_ST","with_susieST")

# st <- "without_ST"
# var_struc  <- "shared_all"
# L  <- 5
# thin  <- 0.1

create_summary_plot_withTP <- function(df, columns_to_plot, x_var = "setting", x_order = NULL, title = NULL) {

  # Reshape data
  df_long <- df %>%
    pivot_longer(
      cols = all_of(columns_to_plot),
      names_to = "variable",
      values_to = "value"
    )
  
  # Convert to factor with specified order if x_order is provided
  if (!is.null(x_order)) {
    df_long <- df_long %>%
      mutate(across(all_of(x_var), ~factor(., levels = x_order)))
  }
  
  # Identify the max value for scaling
  max_main <- max(df_long$value[df_long$variable != "TP_rate"], na.rm = TRUE)
  max_tp_rate <- max(df_long$value[df_long$variable == "TP_rate"], na.rm = TRUE)
  
  if(max_tp_rate ==0) {
    max_tp_rate <- 1
  }
  
  # Rescale TP_rate
  df_long <- df_long %>%
    mutate(scaled_value = ifelse(variable == "TP_rate", 
                                 value * (max_main / max_tp_rate), value))
  
  # Create plot
  ggplot(df_long, aes(x = .data[[x_var]], y = scaled_value, color = variable, shape = variable)) +
    #geom_point(size = 3, position = position_jitter(width = 0.2)) +
    geom_point(size = 3) + 
    scale_y_continuous(
      name = "Count",
      sec.axis = sec_axis(~ . * (max_tp_rate / max_main), name = "TP Rate")
    ) +
    labs(x = "Settings", title = title) +
    theme_minimal() +
    theme(
      axis.text.x = element_text(angle = 45, hjust = 1, size = 10),
      legend.position = "right",
      legend.title = element_blank()
    ) +
    scale_color_brewer(palette = "Set1")
}


create_summary_plot <- function(df, columns_to_plot, x_var = "setting", x_order = NULL, title = NULL) {
  # Reshape data
  df_long <- df %>%
    pivot_longer(
      cols = all_of(columns_to_plot),
      names_to = "variable",
      values_to = "value"
    )
  
  # Convert to factor with specified order if x_order is provided
  if (!is.null(x_order)) {
    df_long <- df_long %>%
      mutate(across(all_of(x_var), ~factor(., levels = x_order)))
  }
  
  # Create plot
  ggplot(df_long, aes(x = .data[[x_var]], y = value, color = variable)) +
    #geom_point(size = 3, position = position_jitter(width = 0.2)) +
    geom_point(size = 3) + 
    labs(x = "Settings", y = "Count/Value", title = title) +
    theme_minimal() +
    theme(
      axis.text.x = element_text(angle = 45, hjust = 1, size = 10),
      legend.position = "right",
      legend.title = element_blank()
    ) +
    scale_color_brewer(palette = "Set1")
}

LDL-ukb-d-30780_irnt

trait <- "LDL-ukb-d-30780_irnt"

setting_names <- c()
prop_h2g_nonsnp_all <- c()
num_gene_pip08_all <- c()
num_silver_pip08_all <- c()
num_bystander_pip08_all <- c()
imputable_known_all <- c()
imputable_bystander_all <- c()
for (st in sts) {
  for (thin in thins) {
    for (var_struc in var_strucs) {
      for (L in Ls) {
        
        if(st == "with_susieST"){
          folder_results <- folder_results_susieST
        }else{
          folder_results <- folder_results_old
        }
        
        setting_names <- c(setting_names, paste0(st,"_thin",thin,"_",var_struc,"_L",L))
        
        # non-snp %h2g
        param <- readRDS(paste0(folder_results,"/",trait,"/",trait,".",st,".thin",thin,".",var_struc,".param.RDS"))
        
        ctwas_parameters <- summarize_param(param, samplesize[trait])
        prop_h2g <- ctwas_parameters$prop_heritability
        prop_h2g_nonsnp <- 1 - ctwas_parameters$prop_heritability["SNP"]
        prop_h2g_nonsnp_all <- c(prop_h2g_nonsnp_all,prop_h2g_nonsnp)
        
        # num_gene_pip08
        combined_pip_by_group <- readRDS(paste0(folder_results,"/",trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L, ".combined_pip_bygroup_final.RDS"))
        combined_pip_sig <- combined_pip_by_group[combined_pip_by_group$combined_pip > 0.8,]
        
        num_gene_pip08_all <- c(num_gene_pip08_all, nrow(combined_pip_sig))
        
        # silver_standard genes
        known <- readRDS(paste0("/project/xinhe/xsun/multi_group_ctwas/data/silverstandard/known_annotations_",traits_silver[trait],".RDS"))
        bystander <- readRDS(paste0("/project/xinhe/xsun/multi_group_ctwas/data/silverstandard/bystanders_",traits_silver[trait],".RDS"))

        num_silver_pip08_all <- c(num_silver_pip08_all,sum(combined_pip_sig$gene_name %in% known))
        num_bystander_pip08_all <- c(num_bystander_pip08_all,sum(combined_pip_sig$gene_name %in% bystander))
        
        # imputable genes
        z_gene <-  readRDS(paste0(folder_results,"/",trait,"/",trait,".",st,".z_gene.RDS"))
        z_gene <- z_gene %>%
                  mutate(molecular_id = sub("\\|.*", "", id)) %>%  # Extract ENSG ID from id
                  left_join(mapping_two %>% dplyr::select(molecular_id, gene_name), by = "molecular_id")
        
        imputable_known_all <- c(imputable_known_all,sum(unique(z_gene$gene_name) %in% known))
        imputable_bystander_all <- c(imputable_bystander_all,sum(unique(z_gene$gene_name) %in% bystander))
        
      }
    }
  }
}


df <- data.frame(setting = setting_names,prop_h2g_nonsnp = prop_h2g_nonsnp_all ,num_gene_pip08 = num_gene_pip08_all,
                 num_silver_total = rep(length(known),length(setting_names)), num_imputable_silver = imputable_known_all, num_silver_pip08 = num_silver_pip08_all,
                 num_bystander_total = rep(length(bystander),length(setting_names)), num_imputable_bystander = imputable_bystander_all, num_bystander_pip08 = num_bystander_pip08_all,
                 TP_rate = num_silver_pip08_all/(num_silver_pip08_all+num_bystander_pip08_all))

## plot Non-SNP %h2g
create_summary_plot(df,x_order = setting_names, 
                    columns_to_plot = c("prop_h2g_nonsnp"), title = "%h2g -- NON-SNP")

Past versions of unnamed-chunk-2-1.png

Version	Author	Date
b815d3b	XSun	2025-04-09
f119060	XSun	2025-04-05

# 
# ## silver standard gene
# create_summary_plot(df,x_order = setting_names, 
#                     columns_to_plot = c("num_gene_pip08","num_imputable_silver","num_silver_pip08"),
#                     title = "Silver standard genes")
# 
# ## bystander genes
# create_summary_plot(df,x_order = setting_names, 
#                     columns_to_plot = c("num_gene_pip08","num_bystander_pip08"),
#                     title = "Bystander genes")
# 
# ## tp
# create_summary_plot(df,x_order = setting_names, 
#                     columns_to_plot = c("num_silver_pip08"),
#                     title = "True positive rate")

create_summary_plot_withTP(df,x_order = setting_names, 
                    columns_to_plot =  c("num_gene_pip08","num_silver_pip08","TP_rate","num_imputable_silver"))

Past versions of unnamed-chunk-2-2.png

Version	Author	Date
b815d3b	XSun	2025-04-09
f119060	XSun	2025-04-05

if(max(as.numeric(df$num_bystander_pip08)) != 0){
  create_summary_plot_withTP(df,x_order = setting_names, 
                    columns_to_plot =  c("num_bystander_pip08","TP_rate"))
}

Past versions of unnamed-chunk-2-3.png

Version	Author	Date
b815d3b	XSun	2025-04-09
f119060	XSun	2025-04-05

DT::datatable(df,caption = htmltools::tags$caption( style = 'caption-side: left; text-align: left; color:black;  font-size:150% ;',trait),options = list(pageLength = 10) )

db <- "GO_Biological_Process_2023"

num_go_adj005 <- c()
setting_names <- c()
for (st in sts) {
  for (thin in thins) {
    for (var_struc in var_strucs) {
      for (L in Ls) {

        if(st == "with_susieST"){
          folder_results <- folder_results_susieST
        }else{
          folder_results <- folder_results_old
        }
        
        setting_names <- c(setting_names, paste0(st,"_thin",thin,"_",var_struc,"_L",L))
        
        file_enrich <- paste0(folder_results,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L, ".enrichr_",db,".RDS")
        if(file.exists(file_enrich)) {
          
          enrich_results <- readRDS(file_enrich)
          num_go_adj005 <- c(num_go_adj005,nrow(enrich_results))
        }else{
          num_go_adj005 <- c(num_go_adj005,0)
        }
        
        
        
      }
    }
  }
}


df <- data.frame(setting = setting_names, num_go_adj005 = num_go_adj005)
create_summary_plot(df,x_order = setting_names, 
                    columns_to_plot = c("num_go_adj005"), title = "Number of enriched GO terms, adj_p < 0.05")

Past versions of unnamed-chunk-3-1.png

Version	Author	Date
b815d3b	XSun	2025-04-09
f119060	XSun	2025-04-05

IBD-ebi-a-GCST004131

trait <- "IBD-ebi-a-GCST004131"

setting_names <- c()
prop_h2g_nonsnp_all <- c()
num_gene_pip08_all <- c()
num_silver_pip08_all <- c()
num_bystander_pip08_all <- c()
imputable_known_all <- c()
imputable_bystander_all <- c()
for (st in sts) {
  for (thin in thins) {
    for (var_struc in var_strucs) {
      for (L in Ls) {

        if(st == "with_susieST"){
          folder_results <- folder_results_susieST
        }else{
          folder_results <- folder_results_old
        }
        
        setting_names <- c(setting_names, paste0(st,"_thin",thin,"_",var_struc,"_L",L))
        
        # non-snp %h2g
        param <- readRDS(paste0(folder_results,"/",trait,"/",trait,".",st,".thin",thin,".",var_struc,".param.RDS"))
        
        ctwas_parameters <- summarize_param(param, samplesize[trait])
        prop_h2g <- ctwas_parameters$prop_heritability
        prop_h2g_nonsnp <- 1 - ctwas_parameters$prop_heritability["SNP"]
        prop_h2g_nonsnp_all <- c(prop_h2g_nonsnp_all,prop_h2g_nonsnp)
        
        # num_gene_pip08
        combined_pip_by_group <- readRDS(paste0(folder_results,"/",trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L, ".combined_pip_bygroup_final.RDS"))
        combined_pip_sig <- combined_pip_by_group[combined_pip_by_group$combined_pip > 0.8,]
        
        num_gene_pip08_all <- c(num_gene_pip08_all, nrow(combined_pip_sig))
        
        # silver_standard genes
        known <- readRDS(paste0("/project/xinhe/xsun/multi_group_ctwas/data/silverstandard/known_annotations_",traits_silver[trait],".RDS"))
        bystander <- readRDS(paste0("/project/xinhe/xsun/multi_group_ctwas/data/silverstandard/bystanders_",traits_silver[trait],".RDS"))

        num_silver_pip08_all <- c(num_silver_pip08_all,sum(combined_pip_sig$gene_name %in% known))
        num_bystander_pip08_all <- c(num_bystander_pip08_all,sum(combined_pip_sig$gene_name %in% bystander))
        
        # imputable genes
        z_gene <-  readRDS(paste0(folder_results,"/",trait,"/",trait,".",st,".z_gene.RDS"))
        z_gene <- z_gene %>%
                  mutate(molecular_id = sub("\\|.*", "", id)) %>%  # Extract ENSG ID from id
                  left_join(mapping_two %>% dplyr::select(molecular_id, gene_name), by = "molecular_id")
        
        imputable_known_all <- c(imputable_known_all,sum(unique(z_gene$gene_name) %in% known))
        imputable_bystander_all <- c(imputable_bystander_all,sum(unique(z_gene$gene_name) %in% bystander))
        
      }
    }
  }
}


df <- data.frame(setting = setting_names,prop_h2g_nonsnp = prop_h2g_nonsnp_all ,num_gene_pip08 = num_gene_pip08_all,
                 num_silver_total = rep(length(known),length(setting_names)), num_imputable_silver = imputable_known_all, num_silver_pip08 = num_silver_pip08_all,
                 num_bystander_total = rep(length(bystander),length(setting_names)), num_imputable_bystander = imputable_bystander_all, num_bystander_pip08 = num_bystander_pip08_all,
                 TP_rate = num_silver_pip08_all/(num_silver_pip08_all+num_bystander_pip08_all))

## plot Non-SNP %h2g
create_summary_plot(df,x_order = setting_names, 
                    columns_to_plot = c("prop_h2g_nonsnp"), title = "%h2g -- NON-SNP")

Past versions of unnamed-chunk-4-1.png

Version	Author	Date
b815d3b	XSun	2025-04-09
f119060	XSun	2025-04-05

# 
# ## silver standard gene
# create_summary_plot(df,x_order = setting_names, 
#                     columns_to_plot = c("num_gene_pip08","num_imputable_silver","num_silver_pip08"),
#                     title = "Silver standard genes")
# 
# ## bystander genes
# create_summary_plot(df,x_order = setting_names, 
#                     columns_to_plot = c("num_gene_pip08","num_bystander_pip08"),
#                     title = "Bystander genes")
# 
# ## tp
# create_summary_plot(df,x_order = setting_names, 
#                     columns_to_plot = c("num_silver_pip08"),
#                     title = "True positive rate")

create_summary_plot_withTP(df,x_order = setting_names, 
                    columns_to_plot =  c("num_gene_pip08","num_silver_pip08","TP_rate","num_imputable_silver"))

Past versions of unnamed-chunk-4-2.png

Version	Author	Date
b815d3b	XSun	2025-04-09
f119060	XSun	2025-04-05

if(max(as.numeric(df$num_bystander_pip08)) != 0){
  create_summary_plot_withTP(df,x_order = setting_names, 
                    columns_to_plot =  c("num_bystander_pip08","TP_rate"))
}

DT::datatable(df,caption = htmltools::tags$caption( style = 'caption-side: left; text-align: left; color:black;  font-size:150% ;',trait),options = list(pageLength = 10) )

db <- "GO_Biological_Process_2023"

num_go_adj005 <- c()
setting_names <- c()
for (st in sts) {
  for (thin in thins) {
    for (var_struc in var_strucs) {
      for (L in Ls) {

        if(st == "with_susieST"){
          folder_results <- folder_results_susieST
        }else{
          folder_results <- folder_results_old
        }
        
        setting_names <- c(setting_names, paste0(st,"_thin",thin,"_",var_struc,"_L",L))
        
        file_enrich <- paste0(folder_results,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L, ".enrichr_",db,".RDS")
        if(file.exists(file_enrich)) {
          
          enrich_results <- readRDS(file_enrich)
          num_go_adj005 <- c(num_go_adj005,nrow(enrich_results))
        }else{
          num_go_adj005 <- c(num_go_adj005,0)
        }
        
        
        
      }
    }
  }
}


df <- data.frame(setting = setting_names, num_go_adj005 = num_go_adj005)
create_summary_plot(df,x_order = setting_names, 
                    columns_to_plot = c("num_go_adj005"), title = "Number of enriched GO terms, adj_p < 0.05")

Past versions of unnamed-chunk-5-1.png

Version	Author	Date
b815d3b	XSun	2025-04-09
f119060	XSun	2025-04-05

T2D-panukb

trait <- "T2D-panukb"

setting_names <- c()
prop_h2g_nonsnp_all <- c()
num_gene_pip08_all <- c()
num_silver_pip08_all <- c()
num_bystander_pip08_all <- c()
imputable_known_all <- c()
imputable_bystander_all <- c()
for (st in sts) {
  for (thin in thins) {
    for (var_struc in var_strucs) {
      for (L in Ls) {
        
        if(st == "with_susieST"){
          folder_results <- folder_results_susieST
        }else{
          folder_results <- folder_results_old
        }

        setting_names <- c(setting_names, paste0(st,"_thin",thin,"_",var_struc,"_L",L))

        # non-snp %h2g
        param <- readRDS(paste0(folder_results,"/",trait,"/",trait,".",st,".thin",thin,".",var_struc,".param.RDS"))

        ctwas_parameters <- summarize_param(param, samplesize[trait])
        prop_h2g <- ctwas_parameters$prop_heritability
        prop_h2g_nonsnp <- 1 - ctwas_parameters$prop_heritability["SNP"]
        prop_h2g_nonsnp_all <- c(prop_h2g_nonsnp_all,prop_h2g_nonsnp)

        # num_gene_pip08
        combined_pip_by_group <- readRDS(paste0(folder_results,"/",trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L, ".combined_pip_bygroup_final.RDS"))
        combined_pip_sig <- combined_pip_by_group[combined_pip_by_group$combined_pip > 0.8,]

        num_gene_pip08_all <- c(num_gene_pip08_all, nrow(combined_pip_sig))

        # silver_standard genes
        known <- readRDS(paste0("/project/xinhe/xsun/multi_group_ctwas/data/silverstandard/known_annotations_",traits_silver[trait],".RDS"))
        bystander <- readRDS(paste0("/project/xinhe/xsun/multi_group_ctwas/data/silverstandard/bystanders_",traits_silver[trait],".RDS"))

        num_silver_pip08_all <- c(num_silver_pip08_all,sum(combined_pip_sig$gene_name %in% known))
        num_bystander_pip08_all <- c(num_bystander_pip08_all,sum(combined_pip_sig$gene_name %in% bystander))

        # imputable genes
        z_gene <-  readRDS(paste0(folder_results,"/",trait,"/",trait,".",st,".z_gene.RDS"))
        z_gene <- z_gene %>%
                  mutate(molecular_id = sub("\\|.*", "", id)) %>%  # Extract ENSG ID from id
                  left_join(mapping_two %>% dplyr::select(molecular_id, gene_name), by = "molecular_id")

        imputable_known_all <- c(imputable_known_all,sum(unique(z_gene$gene_name) %in% known))
        imputable_bystander_all <- c(imputable_bystander_all,sum(unique(z_gene$gene_name) %in% bystander))

      }
    }
  }
}


df <- data.frame(setting = setting_names,prop_h2g_nonsnp = prop_h2g_nonsnp_all ,num_gene_pip08 = num_gene_pip08_all,
                 num_silver_total = rep(length(known),length(setting_names)), num_imputable_silver = imputable_known_all, num_silver_pip08 = num_silver_pip08_all,
                 num_bystander_total = rep(length(bystander),length(setting_names)), num_imputable_bystander = imputable_bystander_all, num_bystander_pip08 = num_bystander_pip08_all,
                 TP_rate = num_silver_pip08_all/(num_silver_pip08_all+num_bystander_pip08_all))

## plot Non-SNP %h2g
create_summary_plot(df,x_order = setting_names,
                    columns_to_plot = c("prop_h2g_nonsnp"), title = "%h2g -- NON-SNP")

Past versions of unnamed-chunk-6-1.png

Version	Author	Date
b815d3b	XSun	2025-04-09
f119060	XSun	2025-04-05

#
# ## silver standard gene
# create_summary_plot(df,x_order = setting_names,
#                     columns_to_plot = c("num_gene_pip08","num_imputable_silver","num_silver_pip08"),
#                     title = "Silver standard genes")
#
# ## bystander genes
# create_summary_plot(df,x_order = setting_names,
#                     columns_to_plot = c("num_gene_pip08","num_bystander_pip08"),
#                     title = "Bystander genes")
#
# ## tp
# create_summary_plot(df,x_order = setting_names,
#                     columns_to_plot = c("num_silver_pip08"),
#                     title = "True positive rate")

create_summary_plot_withTP(df,x_order = setting_names,
                    columns_to_plot =  c("num_gene_pip08","num_silver_pip08","TP_rate","num_imputable_silver"))

Past versions of unnamed-chunk-6-2.png

Version	Author	Date
b815d3b	XSun	2025-04-09
f119060	XSun	2025-04-05

if(max(as.numeric(df$num_bystander_pip08)) != 0){
  create_summary_plot_withTP(df,x_order = setting_names, 
                    columns_to_plot =  c("num_bystander_pip08","TP_rate"))
}

Past versions of unnamed-chunk-6-3.png

Version	Author	Date
f119060	XSun	2025-04-05

DT::datatable(df,caption = htmltools::tags$caption( style = 'caption-side: left; text-align: left; color:black;  font-size:150% ;',trait),options = list(pageLength = 10) )

db <- "GO_Biological_Process_2023"

num_go_adj005 <- c()
setting_names <- c()
for (st in sts) {
  for (thin in thins) {
    for (var_struc in var_strucs) {
      for (L in Ls) {
        
        if(st == "with_susieST"){
          folder_results <- folder_results_susieST
        }else{
          folder_results <- folder_results_old
        }

        setting_names <- c(setting_names, paste0(st,"_thin",thin,"_",var_struc,"_L",L))
        
        file_enrich <- paste0(folder_results,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L, ".enrichr_",db,".RDS")
        if(file.exists(file_enrich)) {
          
          enrich_results <- readRDS(file_enrich)
          num_go_adj005 <- c(num_go_adj005,nrow(enrich_results))
        }else{
          num_go_adj005 <- c(num_go_adj005,0)
        }
        
        
        
      }
    }
  }
}


df <- data.frame(setting = setting_names, num_go_adj005 = num_go_adj005)
create_summary_plot(df,x_order = setting_names, 
                    columns_to_plot = c("num_go_adj005"), title = "Number of enriched GO terms, adj_p < 0.05")

Past versions of unnamed-chunk-7-1.png

Version	Author	Date
b815d3b	XSun	2025-04-09
f119060	XSun	2025-04-05

BMI-panukb

trait <- "BMI-panukb"

setting_names <- c()
prop_h2g_nonsnp_all <- c()
num_gene_pip08_all <- c()
num_silver_pip08_all <- c()
num_bystander_pip08_all <- c()
imputable_known_all <- c()
imputable_bystander_all <- c()
for (st in sts) {
  for (thin in thins) {
    for (var_struc in var_strucs) {
      for (L in Ls) {

        if(st == "with_susieST"){
          folder_results <- folder_results_susieST
        }else{
          folder_results <- folder_results_old
        }
        
        setting_names <- c(setting_names, paste0(st,"_thin",thin,"_",var_struc,"_L",L))

        # non-snp %h2g
        param <- readRDS(paste0(folder_results,"/",trait,"/",trait,".",st,".thin",thin,".",var_struc,".param.RDS"))

        ctwas_parameters <- summarize_param(param, samplesize[trait])
        prop_h2g <- ctwas_parameters$prop_heritability
        prop_h2g_nonsnp <- 1 - ctwas_parameters$prop_heritability["SNP"]
        prop_h2g_nonsnp_all <- c(prop_h2g_nonsnp_all,prop_h2g_nonsnp)

        # num_gene_pip08
        combined_pip_by_group <- readRDS(paste0(folder_results,"/",trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L, ".combined_pip_bygroup_final.RDS"))
        combined_pip_sig <- combined_pip_by_group[combined_pip_by_group$combined_pip > 0.8,]

        num_gene_pip08_all <- c(num_gene_pip08_all, nrow(combined_pip_sig))

        # silver_standard genes
        known <- readRDS(paste0("/project/xinhe/xsun/multi_group_ctwas/data/silverstandard/known_annotations_",traits_silver[trait],".RDS"))
        bystander <- readRDS(paste0("/project/xinhe/xsun/multi_group_ctwas/data/silverstandard/bystanders_",traits_silver[trait],".RDS"))

        num_silver_pip08_all <- c(num_silver_pip08_all,sum(combined_pip_sig$gene_name %in% known))
        num_bystander_pip08_all <- c(num_bystander_pip08_all,sum(combined_pip_sig$gene_name %in% bystander))

        # imputable genes
        z_gene <-  readRDS(paste0(folder_results,"/",trait,"/",trait,".",st,".z_gene.RDS"))
        z_gene <- z_gene %>%
                  mutate(molecular_id = sub("\\|.*", "", id)) %>%  # Extract ENSG ID from id
                  left_join(mapping_two %>% dplyr::select(molecular_id, gene_name), by = "molecular_id")

        imputable_known_all <- c(imputable_known_all,sum(unique(z_gene$gene_name) %in% known))
        imputable_bystander_all <- c(imputable_bystander_all,sum(unique(z_gene$gene_name) %in% bystander))

      }
    }
  }
}


df <- data.frame(setting = setting_names,prop_h2g_nonsnp = prop_h2g_nonsnp_all ,num_gene_pip08 = num_gene_pip08_all,
                 num_silver_total = rep(length(known),length(setting_names)), num_imputable_silver = imputable_known_all, num_silver_pip08 = num_silver_pip08_all,
                 num_bystander_total = rep(length(bystander),length(setting_names)), num_imputable_bystander = imputable_bystander_all, num_bystander_pip08 = num_bystander_pip08_all,
                 TP_rate = num_silver_pip08_all/(num_silver_pip08_all+num_bystander_pip08_all))

## plot Non-SNP %h2g
create_summary_plot(df,x_order = setting_names,
                    columns_to_plot = c("prop_h2g_nonsnp"), title = "%h2g -- NON-SNP")

Past versions of unnamed-chunk-8-1.png

Version	Author	Date
b815d3b	XSun	2025-04-09
f119060	XSun	2025-04-05

#
# ## silver standard gene
# create_summary_plot(df,x_order = setting_names,
#                     columns_to_plot = c("num_gene_pip08","num_imputable_silver","num_silver_pip08"),
#                     title = "Silver standard genes")
#
# ## bystander genes
# create_summary_plot(df,x_order = setting_names,
#                     columns_to_plot = c("num_gene_pip08","num_bystander_pip08"),
#                     title = "Bystander genes")
#
# ## tp
# create_summary_plot(df,x_order = setting_names,
#                     columns_to_plot = c("num_silver_pip08"),
#                     title = "True positive rate")

create_summary_plot_withTP(df,x_order = setting_names,
                    columns_to_plot =  c("num_gene_pip08","num_silver_pip08","TP_rate","num_imputable_silver"))

Past versions of unnamed-chunk-8-2.png

Version	Author	Date
b815d3b	XSun	2025-04-09
f119060	XSun	2025-04-05

if(max(as.numeric(df$num_bystander_pip08)) != 0){
  create_summary_plot_withTP(df,x_order = setting_names, 
                    columns_to_plot =  c("num_bystander_pip08","TP_rate"))
}

Past versions of unnamed-chunk-8-3.png

Version	Author	Date
b815d3b	XSun	2025-04-09
f119060	XSun	2025-04-05

DT::datatable(df,caption = htmltools::tags$caption( style = 'caption-side: left; text-align: left; color:black;  font-size:150% ;',trait),options = list(pageLength = 10) )

db <- "GO_Biological_Process_2023"

num_go_adj005 <- c()
setting_names <- c()
for (st in sts) {
  for (thin in thins) {
    for (var_struc in var_strucs) {
      for (L in Ls) {

        if(st == "with_susieST"){
          folder_results <- folder_results_susieST
        }else{
          folder_results <- folder_results_old
        }
        
        setting_names <- c(setting_names, paste0(st,"_thin",thin,"_",var_struc,"_L",L))
        
        file_enrich <- paste0(folder_results,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L, ".enrichr_",db,".RDS")
        if(file.exists(file_enrich)) {
          
          enrich_results <- readRDS(file_enrich)
          num_go_adj005 <- c(num_go_adj005,nrow(enrich_results))
        }else{
          num_go_adj005 <- c(num_go_adj005,0)
        }
        
        
        
      }
    }
  }
}


df <- data.frame(setting = setting_names, num_go_adj005 = num_go_adj005)
create_summary_plot(df,x_order = setting_names, 
                    columns_to_plot = c("num_go_adj005"), title = "Number of enriched GO terms, adj_p < 0.05")

Past versions of unnamed-chunk-9-1.png

Version	Author	Date
f119060	XSun	2025-04-05

aFib-ebi-a-GCST006414

trait <- "aFib-ebi-a-GCST006414"

setting_names <- c()
prop_h2g_nonsnp_all <- c()
num_gene_pip08_all <- c()
num_silver_pip08_all <- c()
num_bystander_pip08_all <- c()
imputable_known_all <- c()
imputable_bystander_all <- c()

sts_noother <- "with_susieST"

for (st in sts_noother) {
  for (thin in thins) {
    for (var_struc in var_strucs) {
      for (L in Ls) {
        
        if(st == "with_susieST"){
          folder_results <- folder_results_susieST
        }else{
          folder_results <- folder_results_old
        }
        
        setting_names <- c(setting_names, paste0(st,"_thin",thin,"_",var_struc,"_L",L))
        
        # non-snp %h2g
        param <- readRDS(paste0(folder_results,"/",trait,"/",trait,".",st,".thin",thin,".",var_struc,".param.RDS"))
        
        ctwas_parameters <- summarize_param(param, samplesize[trait])
        prop_h2g <- ctwas_parameters$prop_heritability
        prop_h2g_nonsnp <- 1 - ctwas_parameters$prop_heritability["SNP"]
        prop_h2g_nonsnp_all <- c(prop_h2g_nonsnp_all,prop_h2g_nonsnp)
        
        # num_gene_pip08
        combined_pip_by_group <- readRDS(paste0(folder_results,"/",trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L, ".combined_pip_bytype_final.RDS"))
        combined_pip_sig <- combined_pip_by_group[combined_pip_by_group$combined_pip > 0.8,]
        
        num_gene_pip08_all <- c(num_gene_pip08_all, nrow(combined_pip_sig))
        
        # silver_standard genes
        known <- readRDS(paste0("/project/xinhe/xsun/multi_group_ctwas/data/silverstandard/known_annotations_",traits_silver[trait],".RDS"))
        bystander <- readRDS(paste0("/project/xinhe/xsun/multi_group_ctwas/data/silverstandard/bystanders_",traits_silver[trait],".RDS"))

        num_silver_pip08_all <- c(num_silver_pip08_all,sum(combined_pip_sig$gene_name %in% known))
        num_bystander_pip08_all <- c(num_bystander_pip08_all,sum(combined_pip_sig$gene_name %in% bystander))
        
        # imputable genes
        z_gene <-  readRDS(paste0(folder_results,"/",trait,"/",trait,".",st,".z_gene.RDS"))
        z_gene <- z_gene %>%
                  mutate(molecular_id = sub("\\|.*", "", id)) %>%  # Extract ENSG ID from id
                  left_join(mapping_two %>% dplyr::select(molecular_id, gene_name), by = "molecular_id")
        
        imputable_known_all <- c(imputable_known_all,sum(unique(z_gene$gene_name) %in% known))
        imputable_bystander_all <- c(imputable_bystander_all,sum(unique(z_gene$gene_name) %in% bystander))
        
      }
    }
  }
}


df <- data.frame(setting = setting_names,prop_h2g_nonsnp = prop_h2g_nonsnp_all ,num_gene_pip08 = num_gene_pip08_all,
                 num_silver_total = rep(length(known),length(setting_names)), num_imputable_silver = imputable_known_all, num_silver_pip08 = num_silver_pip08_all,
                 num_bystander_total = rep(length(bystander),length(setting_names)), num_imputable_bystander = imputable_bystander_all, num_bystander_pip08 = num_bystander_pip08_all,
                 TP_rate = num_silver_pip08_all/(num_silver_pip08_all+num_bystander_pip08_all))

## plot Non-SNP %h2g
create_summary_plot(df,x_order = setting_names, 
                    columns_to_plot = c("prop_h2g_nonsnp"), title = "%h2g -- NON-SNP")

Past versions of unnamed-chunk-10-1.png

Version	Author	Date
b815d3b	XSun	2025-04-09

# 
# ## silver standard gene
# create_summary_plot(df,x_order = setting_names, 
#                     columns_to_plot = c("num_gene_pip08","num_imputable_silver","num_silver_pip08"),
#                     title = "Silver standard genes")
# 
# ## bystander genes
# create_summary_plot(df,x_order = setting_names, 
#                     columns_to_plot = c("num_gene_pip08","num_bystander_pip08"),
#                     title = "Bystander genes")
# 
# ## tp
# create_summary_plot(df,x_order = setting_names, 
#                     columns_to_plot = c("num_silver_pip08"),
#                     title = "True positive rate")

create_summary_plot_withTP(df,x_order = setting_names, 
                    columns_to_plot =  c("num_gene_pip08","num_silver_pip08","TP_rate","num_imputable_silver"))

Past versions of unnamed-chunk-10-2.png

Version	Author	Date
b815d3b	XSun	2025-04-09

if(max(as.numeric(df$num_bystander_pip08)) != 0){
  create_summary_plot_withTP(df,x_order = setting_names, 
                    columns_to_plot =  c("num_bystander_pip08","TP_rate"))
}

Past versions of unnamed-chunk-10-3.png

Version	Author	Date
b815d3b	XSun	2025-04-09

DT::datatable(df,caption = htmltools::tags$caption( style = 'caption-side: left; text-align: left; color:black;  font-size:150% ;',trait),options = list(pageLength = 10) )

db <- "GO_Biological_Process_2023"

num_go_adj005 <- c()
setting_names <- c()
for (st in sts_noother) {
  for (thin in thins) {
    for (var_struc in var_strucs) {
      for (L in Ls) {

        if(st == "with_susieST"){
          folder_results <- folder_results_susieST
        }else{
          folder_results <- folder_results_old
        }
        
        setting_names <- c(setting_names, paste0(st,"_thin",thin,"_",var_struc,"_L",L))
        
        file_enrich <- paste0(folder_results,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L, ".enrichr_",db,".RDS")
        if(file.exists(file_enrich)) {
          
          enrich_results <- readRDS(file_enrich)
          num_go_adj005 <- c(num_go_adj005,nrow(enrich_results))
        }else{
          num_go_adj005 <- c(num_go_adj005,0)
        }
        
        
        
      }
    }
  }
}


df <- data.frame(setting = setting_names, num_go_adj005 = num_go_adj005)
create_summary_plot(df,x_order = setting_names, 
                    columns_to_plot = c("num_go_adj005"), title = "Number of enriched GO terms, adj_p < 0.05")

Past versions of unnamed-chunk-11-1.png

Version	Author	Date
b815d3b	XSun	2025-04-09

SCZ-ieu-b-5102

trait <- "SCZ-ieu-b-5102"

setting_names <- c()
prop_h2g_nonsnp_all <- c()
num_gene_pip08_all <- c()
num_silver_pip08_all <- c()
num_bystander_pip08_all <- c()
imputable_known_all <- c()
imputable_bystander_all <- c()


sts_noother <- "with_susieST"

for (st in sts_noother) {
  for (thin in thins) {
    for (var_struc in var_strucs) {
      for (L in Ls) {
        
        if(st == "with_susieST"){
          folder_results <- folder_results_susieST
        }else{
          folder_results <- folder_results_old
        }
        
        setting_names <- c(setting_names, paste0(st,"_thin",thin,"_",var_struc,"_L",L))
        
        # non-snp %h2g
        param <- readRDS(paste0(folder_results,"/",trait,"/",trait,".",st,".thin",thin,".",var_struc,".param.RDS"))
        
        ctwas_parameters <- summarize_param(param, samplesize[trait])
        prop_h2g <- ctwas_parameters$prop_heritability
        prop_h2g_nonsnp <- 1 - ctwas_parameters$prop_heritability["SNP"]
        prop_h2g_nonsnp_all <- c(prop_h2g_nonsnp_all,prop_h2g_nonsnp)
        
        # num_gene_pip08
        combined_pip_by_group <- readRDS(paste0(folder_results,"/",trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L, ".combined_pip_bytype_final.RDS"))
        combined_pip_sig <- combined_pip_by_group[combined_pip_by_group$combined_pip > 0.8,]
        
        num_gene_pip08_all <- c(num_gene_pip08_all, nrow(combined_pip_sig))
        
        # silver_standard genes
        known <- readRDS(paste0("/project/xinhe/xsun/multi_group_ctwas/data/silverstandard/known_annotations_",traits_silver[trait],".RDS"))
        bystander <- readRDS(paste0("/project/xinhe/xsun/multi_group_ctwas/data/silverstandard/bystanders_",traits_silver[trait],".RDS"))

        num_silver_pip08_all <- c(num_silver_pip08_all,sum(combined_pip_sig$gene_name %in% known))
        num_bystander_pip08_all <- c(num_bystander_pip08_all,sum(combined_pip_sig$gene_name %in% bystander))
        
        # imputable genes
        z_gene <-  readRDS(paste0(folder_results,"/",trait,"/",trait,".",st,".z_gene.RDS"))
        z_gene <- z_gene %>%
                  mutate(molecular_id = sub("\\|.*", "", id)) %>%  # Extract ENSG ID from id
                  left_join(mapping_two %>% dplyr::select(molecular_id, gene_name), by = "molecular_id")
        
        imputable_known_all <- c(imputable_known_all,sum(unique(z_gene$gene_name) %in% known))
        imputable_bystander_all <- c(imputable_bystander_all,sum(unique(z_gene$gene_name) %in% bystander))
        
      }
    }
  }
}


df <- data.frame(setting = setting_names,prop_h2g_nonsnp = prop_h2g_nonsnp_all ,num_gene_pip08 = num_gene_pip08_all,
                 num_silver_total = rep(length(known),length(setting_names)), num_imputable_silver = imputable_known_all, num_silver_pip08 = num_silver_pip08_all,
                 num_bystander_total = rep(length(bystander),length(setting_names)), num_imputable_bystander = imputable_bystander_all, num_bystander_pip08 = num_bystander_pip08_all,
                 TP_rate = num_silver_pip08_all/(num_silver_pip08_all+num_bystander_pip08_all))

## plot Non-SNP %h2g
create_summary_plot(df,x_order = setting_names, 
                    columns_to_plot = c("prop_h2g_nonsnp"), title = "%h2g -- NON-SNP")

Past versions of unnamed-chunk-12-1.png

Version	Author	Date
b815d3b	XSun	2025-04-09

# 
# ## silver standard gene
# create_summary_plot(df,x_order = setting_names, 
#                     columns_to_plot = c("num_gene_pip08","num_imputable_silver","num_silver_pip08"),
#                     title = "Silver standard genes")
# 
# ## bystander genes
# create_summary_plot(df,x_order = setting_names, 
#                     columns_to_plot = c("num_gene_pip08","num_bystander_pip08"),
#                     title = "Bystander genes")
# 
# ## tp
# create_summary_plot(df,x_order = setting_names, 
#                     columns_to_plot = c("num_silver_pip08"),
#                     title = "True positive rate")

create_summary_plot_withTP(df,x_order = setting_names, 
                    columns_to_plot =  c("num_gene_pip08","num_silver_pip08","TP_rate","num_imputable_silver"))

Past versions of unnamed-chunk-12-2.png

Version	Author	Date
b815d3b	XSun	2025-04-09

if(max(as.numeric(df$num_bystander_pip08)) != 0){
  create_summary_plot_withTP(df,x_order = setting_names, 
                    columns_to_plot =  c("num_bystander_pip08","TP_rate"))
}

Past versions of unnamed-chunk-12-3.png

Version	Author	Date
b815d3b	XSun	2025-04-09

DT::datatable(df,caption = htmltools::tags$caption( style = 'caption-side: left; text-align: left; color:black;  font-size:150% ;',trait),options = list(pageLength = 10) )

db <- "GO_Biological_Process_2023"

num_go_adj005 <- c()
setting_names <- c()
for (st in sts_noother) {
  for (thin in thins) {
    for (var_struc in var_strucs) {
      for (L in Ls) {

        if(st == "with_susieST"){
          folder_results <- folder_results_susieST
        }else{
          folder_results <- folder_results_old
        }
        
        setting_names <- c(setting_names, paste0(st,"_thin",thin,"_",var_struc,"_L",L))
        
        file_enrich <- paste0(folder_results,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L, ".enrichr_",db,".RDS")
        if(file.exists(file_enrich)) {
          
          enrich_results <- readRDS(file_enrich)
          num_go_adj005 <- c(num_go_adj005,nrow(enrich_results))
        }else{
          num_go_adj005 <- c(num_go_adj005,0)
        }
        
        
        
      }
    }
  }
}


df <- data.frame(setting = setting_names, num_go_adj005 = num_go_adj005)
create_summary_plot(df,x_order = setting_names, 
                    columns_to_plot = c("num_go_adj005"), title = "Number of enriched GO terms, adj_p < 0.05")

Past versions of unnamed-chunk-13-1.png

Version	Author	Date
b815d3b	XSun	2025-04-09

Session information

sessionInfo()

R version 4.2.0 (2022-04-22)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Red Hat Enterprise Linux 8.4 (Ootpa)

Matrix products: default
BLAS/LAPACK: /software/openblas-0.3.13-el8-x86_64/lib/libopenblas_skylakexp-r0.3.13.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] scales_1.2.0     tidyr_1.3.0      dplyr_1.1.2      ggplot2_3.4.2   
[5] ctwas_0.5.5.9001 workflowr_1.7.1 

loaded via a namespace (and not attached):
  [1] colorspace_2.0-3            rjson_0.2.21               
  [3] ellipsis_0.3.2              rprojroot_2.0.3            
  [5] XVector_0.38.0              locuszoomr_0.1.5           
  [7] GenomicRanges_1.50.2        base64enc_0.1-3            
  [9] fs_1.5.2                    rstudioapi_0.14            
 [11] farver_2.1.0                DT_0.22                    
 [13] ggrepel_0.9.3               bit64_4.0.5                
 [15] AnnotationDbi_1.60.2        fansi_1.0.3                
 [17] xml2_1.3.3                  logging_0.10-108           
 [19] codetools_0.2-18            cachem_1.0.6               
 [21] knitr_1.42                  jsonlite_1.8.9             
 [23] Rsamtools_2.14.0            dbplyr_2.3.2               
 [25] png_0.1-7                   readr_2.1.4                
 [27] compiler_4.2.0              httr_1.4.7                 
 [29] Matrix_1.6-1.1              fastmap_1.1.0              
 [31] lazyeval_0.2.2              cli_3.6.2                  
 [33] later_1.3.0                 htmltools_0.5.7            
 [35] prettyunits_1.1.1           tools_4.2.0                
 [37] gtable_0.3.0                glue_1.6.2                 
 [39] GenomeInfoDbData_1.2.9      rappdirs_0.3.3             
 [41] Rcpp_1.0.14                 Biobase_2.58.0             
 [43] jquerylib_0.1.4             vctrs_0.6.1                
 [45] Biostrings_2.66.0           rtracklayer_1.58.0         
 [47] crosstalk_1.2.0             xfun_0.38                  
 [49] stringr_1.5.0               ps_1.7.0                   
 [51] irlba_2.3.5                 lifecycle_1.0.4            
 [53] restfulr_0.0.15             ensembldb_2.22.0           
 [55] XML_3.99-0.9                getPass_0.2-2              
 [57] zlibbioc_1.44.0             gggrid_0.2-0               
 [59] hms_1.1.3                   promises_1.2.0.1           
 [61] MatrixGenerics_1.10.0       ProtGenerics_1.30.0        
 [63] parallel_4.2.0              SummarizedExperiment_1.28.0
 [65] RColorBrewer_1.1-3          AnnotationFilter_1.22.0    
 [67] LDlinkR_1.3.0               yaml_2.3.5                 
 [69] curl_4.3.2                  memoise_2.0.1              
 [71] sass_0.4.1                  biomaRt_2.54.1             
 [73] stringi_1.7.6               RSQLite_2.3.1              
 [75] highr_0.9                   S4Vectors_0.36.2           
 [77] BiocIO_1.8.0                GenomicFeatures_1.50.4     
 [79] BiocGenerics_0.44.0         filelock_1.0.2             
 [81] BiocParallel_1.32.6         repr_1.1.4                 
 [83] GenomeInfoDb_1.34.9         rlang_1.1.2                
 [85] pkgconfig_2.0.3             matrixStats_1.2.0          
 [87] bitops_1.0-7                evaluate_0.15              
 [89] lattice_0.20-45             purrr_1.0.1                
 [91] labeling_0.4.2              GenomicAlignments_1.34.1   
 [93] htmlwidgets_1.6.2           cowplot_1.1.1              
 [95] bit_4.0.4                   processx_3.5.3             
 [97] tidyselect_1.2.0            magrittr_2.0.3             
 [99] AMR_2.1.1                   R6_2.5.1                   
[101] IRanges_2.32.0              generics_0.1.3             
[103] DelayedArray_0.24.0         DBI_1.1.2                  
[105] withr_2.5.0                 pgenlibr_0.3.6             
[107] pillar_1.9.0                whisker_0.4                
[109] mixsqp_0.3-48               KEGGREST_1.38.0            
[111] RCurl_1.98-1.12             tibble_3.2.1               
[113] crayon_1.5.1                utf8_1.2.2                 
[115] BiocFileCache_2.6.1         plotly_4.10.0              
[117] tzdb_0.3.0                  rmarkdown_2.21             
[119] progress_1.2.2              grid_4.2.0                 
[121] data.table_1.14.4           blob_1.2.3                 
[123] callr_3.7.0                 git2r_0.30.1               
[125] digest_0.6.29               httpuv_1.6.5               
[127] stats4_4.2.0                munsell_0.5.0              
[129] viridisLite_0.4.0           skimr_2.1.4                
[131] bslib_0.3.1