Compare ld-mismatch setting
XSun
2025-04-07
Last updated: 2025-04-08
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Knit directory: multigroup_ctwas_analysis/
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Introduction
We compare different ld - mismatch settings
- remove the ld-mismatched snp, recompute the z-scores and re-do the finemapping
- re-finemap without LD
library(ggplot2)
folder_results_susieST <- "/project/xinhe/xsun/multi_group_ctwas/15.susie_weights/snakemake_outputs/"IBD-ebi-a-GCST004131
Setting: shared_all, thin = 0.1, L = 5, susieST
trait <- "IBD-ebi-a-GCST004131"
thin <- 0.1
var_struc <- "shared_all"
st <- "with_susieST"
L <- 5
ctwas_res_origin <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".finemap_regions_res.RDS"))
finemap_res_origin <- ctwas_res_origin$finemap_res
finemap_res_gene_origin <- finemap_res_origin[finemap_res_origin$type != "SNP",]
ctwas_res_regionmerge <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".regionmerge_finemap_regions_res.RDS"))
finemap_res_regionmerge <- ctwas_res_regionmerge$finemap_res
finemap_res_gene_regionmerge <- finemap_res_regionmerge[finemap_res_regionmerge$type != "SNP",]Thresholds for ld mismatch diagnosis: nonSNP PIP = 0.5, SNP p_diff = 5e-8
threshold_nonSNP_PIPs <- 0.5
threshold_SNP_p <- "5e-08"problematic_genes <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".ldmismatch_problematic_genes_genepip",threshold_nonSNP_PIPs,"_snpp_",threshold_SNP_p,".RDS"))
finemap_res_gene_origin$highlight <- ifelse(finemap_res_gene_origin$id %in% problematic_genes, "problematic genes", "good genes")
p1 <- ggplot(data = finemap_res_gene_origin, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("Original ctwas results") +
theme_minimal()
finemap_res_gene_regionmerge$highlight <- ifelse(finemap_res_gene_regionmerge$id %in% problematic_genes, "problematic genes", "good genes")
p2 <- ggplot(data = finemap_res_gene_regionmerge, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("After region merge") +
theme_minimal()
ctwas_res_ldmismatch <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".ldmismatch_finemap_regions_res_genepip",threshold_nonSNP_PIPs,"_snpp_",threshold_SNP_p,".RDS"))
finemap_res_ldmismatch <- ctwas_res_ldmismatch$finemap_res
finemap_res_gene_ldmismatch <- finemap_res_ldmismatch[finemap_res_ldmismatch$type != "SNP",]
finemap_res_gene_ldmismatch$highlight <- ifelse(finemap_res_gene_ldmismatch$id %in% problematic_genes, "problematic genes", "good genes")
p3 <- ggplot(data = finemap_res_gene_ldmismatch, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("LD mismatch fixed -- remove the snp") +
theme_minimal()
ctwas_res_ldmismatchnoLD <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".ldmismatch_noLD_finemap_regions_res_genepip",threshold_nonSNP_PIPs,"_snpp_",threshold_SNP_p,".RDS"))
finemap_res_ldmismatchnoLD <- ctwas_res_ldmismatchnoLD$finemap_res
finemap_res_gene_ldmismatchnoLD <- finemap_res_ldmismatchnoLD[finemap_res_ldmismatchnoLD$type != "SNP",]
finemap_res_gene_ldmismatchnoLD$highlight <- ifelse(finemap_res_gene_ldmismatchnoLD$id %in% problematic_genes, "problematic genes", "good genes")
p4 <- ggplot(data = finemap_res_gene_ldmismatchnoLD, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("LD mismatch fixed -- remove the snp") +
theme_minimal()
grid::grid.newpage()
gridExtra::grid.arrange(p1,p2,p3,p4,
ncol = 4,
top = paste0(trait,"-nonSNP_PIPs:",threshold_nonSNP_PIPs,"-SNP_p:",threshold_SNP_p))
Thresholds for ld mismatch diagnosis: nonSNP PIP = 0.5, SNP p_diff = 5e-6
threshold_nonSNP_PIPs <- 0.5
threshold_SNP_p <- "5e-06"problematic_genes <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".ldmismatch_problematic_genes_genepip",threshold_nonSNP_PIPs,"_snpp_",threshold_SNP_p,".RDS"))
finemap_res_gene_origin$highlight <- ifelse(finemap_res_gene_origin$id %in% problematic_genes, "problematic genes", "good genes")
p1 <- ggplot(data = finemap_res_gene_origin, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("Original ctwas results") +
theme_minimal()
finemap_res_gene_regionmerge$highlight <- ifelse(finemap_res_gene_regionmerge$id %in% problematic_genes, "problematic genes", "good genes")
p2 <- ggplot(data = finemap_res_gene_regionmerge, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("After region merge") +
theme_minimal()
ctwas_res_ldmismatch <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".ldmismatch_finemap_regions_res_genepip",threshold_nonSNP_PIPs,"_snpp_",threshold_SNP_p,".RDS"))
finemap_res_ldmismatch <- ctwas_res_ldmismatch$finemap_res
finemap_res_gene_ldmismatch <- finemap_res_ldmismatch[finemap_res_ldmismatch$type != "SNP",]
finemap_res_gene_ldmismatch$highlight <- ifelse(finemap_res_gene_ldmismatch$id %in% problematic_genes, "problematic genes", "good genes")
p3 <- ggplot(data = finemap_res_gene_ldmismatch, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("LD mismatch fixed -- remove the snp") +
theme_minimal()
ctwas_res_ldmismatchnoLD <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".ldmismatch_noLD_finemap_regions_res_genepip",threshold_nonSNP_PIPs,"_snpp_",threshold_SNP_p,".RDS"))
finemap_res_ldmismatchnoLD <- ctwas_res_ldmismatchnoLD$finemap_res
finemap_res_gene_ldmismatchnoLD <- finemap_res_ldmismatchnoLD[finemap_res_ldmismatchnoLD$type != "SNP",]
finemap_res_gene_ldmismatchnoLD$highlight <- ifelse(finemap_res_gene_ldmismatchnoLD$id %in% problematic_genes, "problematic genes", "good genes")
p4 <- ggplot(data = finemap_res_gene_ldmismatchnoLD, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("LD mismatch fixed -- remove the snp") +
theme_minimal()
grid::grid.newpage()
gridExtra::grid.arrange(p1,p2,p3,p4,
ncol = 4,
top = paste0(trait,"-nonSNP_PIPs:",threshold_nonSNP_PIPs,"-SNP_p:",threshold_SNP_p))
Thresholds for ld mismatch diagnosis: nonSNP PIP = 0.2, SNP p_diff = 5e-8
threshold_nonSNP_PIPs <- 0.2
threshold_SNP_p <- "5e-08"problematic_genes <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".ldmismatch_problematic_genes_genepip",threshold_nonSNP_PIPs,"_snpp_",threshold_SNP_p,".RDS"))
finemap_res_gene_origin$highlight <- ifelse(finemap_res_gene_origin$id %in% problematic_genes, "problematic genes", "good genes")
p1 <- ggplot(data = finemap_res_gene_origin, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("Original ctwas results") +
theme_minimal()
finemap_res_gene_regionmerge$highlight <- ifelse(finemap_res_gene_regionmerge$id %in% problematic_genes, "problematic genes", "good genes")
p2 <- ggplot(data = finemap_res_gene_regionmerge, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("After region merge") +
theme_minimal()
ctwas_res_ldmismatch <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".ldmismatch_finemap_regions_res_genepip",threshold_nonSNP_PIPs,"_snpp_",threshold_SNP_p,".RDS"))
finemap_res_ldmismatch <- ctwas_res_ldmismatch$finemap_res
finemap_res_gene_ldmismatch <- finemap_res_ldmismatch[finemap_res_ldmismatch$type != "SNP",]
finemap_res_gene_ldmismatch$highlight <- ifelse(finemap_res_gene_ldmismatch$id %in% problematic_genes, "problematic genes", "good genes")
p3 <- ggplot(data = finemap_res_gene_ldmismatch, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("LD mismatch fixed -- remove the snp") +
theme_minimal()
ctwas_res_ldmismatchnoLD <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".ldmismatch_noLD_finemap_regions_res_genepip",threshold_nonSNP_PIPs,"_snpp_",threshold_SNP_p,".RDS"))
finemap_res_ldmismatchnoLD <- ctwas_res_ldmismatchnoLD$finemap_res
finemap_res_gene_ldmismatchnoLD <- finemap_res_ldmismatchnoLD[finemap_res_ldmismatchnoLD$type != "SNP",]
finemap_res_gene_ldmismatchnoLD$highlight <- ifelse(finemap_res_gene_ldmismatchnoLD$id %in% problematic_genes, "problematic genes", "good genes")
p4 <- ggplot(data = finemap_res_gene_ldmismatchnoLD, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("LD mismatch fixed -- remove the snp") +
theme_minimal()
grid::grid.newpage()
gridExtra::grid.arrange(p1,p2,p3,p4,
ncol = 4,
top = paste0(trait,"-nonSNP_PIPs:",threshold_nonSNP_PIPs,"-SNP_p:",threshold_SNP_p))
Thresholds for ld mismatch diagnosis: nonSNP PIP = 0.2, SNP p_diff = 5e-6
threshold_nonSNP_PIPs <- 0.2
threshold_SNP_p <- "5e-06"problematic_genes <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".ldmismatch_problematic_genes_genepip",threshold_nonSNP_PIPs,"_snpp_",threshold_SNP_p,".RDS"))
finemap_res_gene_origin$highlight <- ifelse(finemap_res_gene_origin$id %in% problematic_genes, "problematic genes", "good genes")
p1 <- ggplot(data = finemap_res_gene_origin, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("Original ctwas results") +
theme_minimal()
finemap_res_gene_regionmerge$highlight <- ifelse(finemap_res_gene_regionmerge$id %in% problematic_genes, "problematic genes", "good genes")
p2 <- ggplot(data = finemap_res_gene_regionmerge, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("After region merge") +
theme_minimal()
ctwas_res_ldmismatch <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".ldmismatch_finemap_regions_res_genepip",threshold_nonSNP_PIPs,"_snpp_",threshold_SNP_p,".RDS"))
finemap_res_ldmismatch <- ctwas_res_ldmismatch$finemap_res
finemap_res_gene_ldmismatch <- finemap_res_ldmismatch[finemap_res_ldmismatch$type != "SNP",]
finemap_res_gene_ldmismatch$highlight <- ifelse(finemap_res_gene_ldmismatch$id %in% problematic_genes, "problematic genes", "good genes")
p3 <- ggplot(data = finemap_res_gene_ldmismatch, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("LD mismatch fixed -- remove the snp") +
theme_minimal()
ctwas_res_ldmismatchnoLD <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".ldmismatch_noLD_finemap_regions_res_genepip",threshold_nonSNP_PIPs,"_snpp_",threshold_SNP_p,".RDS"))
finemap_res_ldmismatchnoLD <- ctwas_res_ldmismatchnoLD$finemap_res
finemap_res_gene_ldmismatchnoLD <- finemap_res_ldmismatchnoLD[finemap_res_ldmismatchnoLD$type != "SNP",]
finemap_res_gene_ldmismatchnoLD$highlight <- ifelse(finemap_res_gene_ldmismatchnoLD$id %in% problematic_genes, "problematic genes", "good genes")
p4 <- ggplot(data = finemap_res_gene_ldmismatchnoLD, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("LD mismatch fixed -- remove the snp") +
theme_minimal()
grid::grid.newpage()
gridExtra::grid.arrange(p1,p2,p3,p4,
ncol = 4,
top = paste0(trait,"-nonSNP_PIPs:",threshold_nonSNP_PIPs,"-SNP_p:",threshold_SNP_p)) 
gene_weird <- finemap_res_gene_origin[abs(finemap_res_gene_origin$z)< 1 & finemap_res_gene_origin$susie_pip > 0.3,]$id
gene_weird_ldmismatch <- finemap_res_gene_ldmismatch[finemap_res_gene_ldmismatch$id %in% gene_weird,]
prob_gene <- finemap_res_gene_origin[finemap_res_gene_origin$id %in% problematic_genes,]
DT::datatable(gene_weird_ldmismatch,caption = htmltools::tags$caption( style = 'caption-side: left; text-align: left; color:black; font-size:150% ;','Gene disappeared'),options = list(pageLength = 10) )DT::datatable(prob_gene,caption = htmltools::tags$caption( style = 'caption-side: left; text-align: left; color:black; font-size:150% ;','Problematic genes'),options = list(pageLength = 10) )Thresholds for ld mismatch diagnosis: nonSNP PIP = 0.2, SNP p_diff = 5e-4
threshold_nonSNP_PIPs <- 0.2
threshold_SNP_p <- "5e-04"problematic_genes <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".ldmismatch_problematic_genes_genepip",threshold_nonSNP_PIPs,"_snpp_",threshold_SNP_p,".RDS"))
finemap_res_gene_origin$highlight <- ifelse(finemap_res_gene_origin$id %in% problematic_genes, "problematic genes", "good genes")
p1 <- ggplot(data = finemap_res_gene_origin, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("Original ctwas results") +
theme_minimal()
finemap_res_gene_regionmerge$highlight <- ifelse(finemap_res_gene_regionmerge$id %in% problematic_genes, "problematic genes", "good genes")
p2 <- ggplot(data = finemap_res_gene_regionmerge, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("After region merge") +
theme_minimal()
ctwas_res_ldmismatch <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".ldmismatch_finemap_regions_res_genepip",threshold_nonSNP_PIPs,"_snpp_",threshold_SNP_p,".RDS"))
finemap_res_ldmismatch <- ctwas_res_ldmismatch$finemap_res
finemap_res_gene_ldmismatch <- finemap_res_ldmismatch[finemap_res_ldmismatch$type != "SNP",]
finemap_res_gene_ldmismatch$highlight <- ifelse(finemap_res_gene_ldmismatch$id %in% problematic_genes, "problematic genes", "good genes")
p3 <- ggplot(data = finemap_res_gene_ldmismatch, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("LD mismatch fixed -- remove the snp") +
theme_minimal()
ctwas_res_ldmismatchnoLD <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".ldmismatch_noLD_finemap_regions_res_genepip",threshold_nonSNP_PIPs,"_snpp_",threshold_SNP_p,".RDS"))
finemap_res_ldmismatchnoLD <- ctwas_res_ldmismatchnoLD$finemap_res
finemap_res_gene_ldmismatchnoLD <- finemap_res_ldmismatchnoLD[finemap_res_ldmismatchnoLD$type != "SNP",]
finemap_res_gene_ldmismatchnoLD$highlight <- ifelse(finemap_res_gene_ldmismatchnoLD$id %in% problematic_genes, "problematic genes", "good genes")
p4 <- ggplot(data = finemap_res_gene_ldmismatchnoLD, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("LD mismatch fixed -- remove the snp") +
theme_minimal()
grid::grid.newpage()
gridExtra::grid.arrange(p1,p2,p3,p4,
ncol = 4,
top = paste0(trait,"-nonSNP_PIPs:",threshold_nonSNP_PIPs,"-SNP_p:",threshold_SNP_p)) 
aFib-ebi-a-GCST006414
Setting: shared_all, thin = 0.1, L = 5, susieST
trait <- "aFib-ebi-a-GCST006414"
thin <- 0.1
var_struc <- "shared_all"
st <- "with_susieST"
L <- 5
ctwas_res_origin <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".finemap_regions_res.RDS"))
finemap_res_origin <- ctwas_res_origin$finemap_res
finemap_res_gene_origin <- finemap_res_origin[finemap_res_origin$type != "SNP",]
ctwas_res_regionmerge <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".regionmerge_finemap_regions_res.RDS"))
finemap_res_regionmerge <- ctwas_res_regionmerge$finemap_res
finemap_res_gene_regionmerge <- finemap_res_regionmerge[finemap_res_regionmerge$type != "SNP",]Thresholds for ld mismatch diagnosis: nonSNP PIP = 0.5, SNP p_diff = 5e-8
threshold_nonSNP_PIPs <- 0.5
threshold_SNP_p <- "5e-08"problematic_genes <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".ldmismatch_problematic_genes_genepip",threshold_nonSNP_PIPs,"_snpp_",threshold_SNP_p,".RDS"))
finemap_res_gene_origin$highlight <- ifelse(finemap_res_gene_origin$id %in% problematic_genes, "problematic genes", "good genes")
p1 <- ggplot(data = finemap_res_gene_origin, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("Original ctwas results") +
theme_minimal()
finemap_res_gene_regionmerge$highlight <- ifelse(finemap_res_gene_regionmerge$id %in% problematic_genes, "problematic genes", "good genes")
p2 <- ggplot(data = finemap_res_gene_regionmerge, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("After region merge") +
theme_minimal()
ctwas_res_ldmismatch <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".ldmismatch_finemap_regions_res_genepip",threshold_nonSNP_PIPs,"_snpp_",threshold_SNP_p,".RDS"))
finemap_res_ldmismatch <- ctwas_res_ldmismatch$finemap_res
finemap_res_gene_ldmismatch <- finemap_res_ldmismatch[finemap_res_ldmismatch$type != "SNP",]
finemap_res_gene_ldmismatch$highlight <- ifelse(finemap_res_gene_ldmismatch$id %in% problematic_genes, "problematic genes", "good genes")
p3 <- ggplot(data = finemap_res_gene_ldmismatch, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("LD mismatch fixed -- remove the snp") +
theme_minimal()
ctwas_res_ldmismatchnoLD <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".ldmismatch_noLD_finemap_regions_res_genepip",threshold_nonSNP_PIPs,"_snpp_",threshold_SNP_p,".RDS"))
finemap_res_ldmismatchnoLD <- ctwas_res_ldmismatchnoLD$finemap_res
finemap_res_gene_ldmismatchnoLD <- finemap_res_ldmismatchnoLD[finemap_res_ldmismatchnoLD$type != "SNP",]
finemap_res_gene_ldmismatchnoLD$highlight <- ifelse(finemap_res_gene_ldmismatchnoLD$id %in% problematic_genes, "problematic genes", "good genes")
p4 <- ggplot(data = finemap_res_gene_ldmismatchnoLD, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("LD mismatch fixed -- remove the snp") +
theme_minimal()
grid::grid.newpage()
gridExtra::grid.arrange(p1,p2,p3,p4,
ncol = 4,
top = paste0(trait,"-nonSNP_PIPs:",threshold_nonSNP_PIPs,"-SNP_p:",threshold_SNP_p))
Thresholds for ld mismatch diagnosis: nonSNP PIP = 0.5, SNP p_diff = 5e-6
threshold_nonSNP_PIPs <- 0.5
threshold_SNP_p <- "5e-06"problematic_genes <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".ldmismatch_problematic_genes_genepip",threshold_nonSNP_PIPs,"_snpp_",threshold_SNP_p,".RDS"))
finemap_res_gene_origin$highlight <- ifelse(finemap_res_gene_origin$id %in% problematic_genes, "problematic genes", "good genes")
p1 <- ggplot(data = finemap_res_gene_origin, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("Original ctwas results") +
theme_minimal()
finemap_res_gene_regionmerge$highlight <- ifelse(finemap_res_gene_regionmerge$id %in% problematic_genes, "problematic genes", "good genes")
p2 <- ggplot(data = finemap_res_gene_regionmerge, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("After region merge") +
theme_minimal()
ctwas_res_ldmismatch <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".ldmismatch_finemap_regions_res_genepip",threshold_nonSNP_PIPs,"_snpp_",threshold_SNP_p,".RDS"))
finemap_res_ldmismatch <- ctwas_res_ldmismatch$finemap_res
finemap_res_gene_ldmismatch <- finemap_res_ldmismatch[finemap_res_ldmismatch$type != "SNP",]
finemap_res_gene_ldmismatch$highlight <- ifelse(finemap_res_gene_ldmismatch$id %in% problematic_genes, "problematic genes", "good genes")
p3 <- ggplot(data = finemap_res_gene_ldmismatch, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("LD mismatch fixed -- remove the snp") +
theme_minimal()
ctwas_res_ldmismatchnoLD <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".ldmismatch_noLD_finemap_regions_res_genepip",threshold_nonSNP_PIPs,"_snpp_",threshold_SNP_p,".RDS"))
finemap_res_ldmismatchnoLD <- ctwas_res_ldmismatchnoLD$finemap_res
finemap_res_gene_ldmismatchnoLD <- finemap_res_ldmismatchnoLD[finemap_res_ldmismatchnoLD$type != "SNP",]
finemap_res_gene_ldmismatchnoLD$highlight <- ifelse(finemap_res_gene_ldmismatchnoLD$id %in% problematic_genes, "problematic genes", "good genes")
p4 <- ggplot(data = finemap_res_gene_ldmismatchnoLD, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("LD mismatch fixed -- remove the snp") +
theme_minimal()
grid::grid.newpage()
gridExtra::grid.arrange(p1,p2,p3,p4,
ncol = 4,
top = paste0(trait,"-nonSNP_PIPs:",threshold_nonSNP_PIPs,"-SNP_p:",threshold_SNP_p))
Thresholds for ld mismatch diagnosis: nonSNP PIP = 0.2, SNP p_diff = 5e-8
threshold_nonSNP_PIPs <- 0.2
threshold_SNP_p <- "5e-08"problematic_genes <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".ldmismatch_problematic_genes_genepip",threshold_nonSNP_PIPs,"_snpp_",threshold_SNP_p,".RDS"))
finemap_res_gene_origin$highlight <- ifelse(finemap_res_gene_origin$id %in% problematic_genes, "problematic genes", "good genes")
p1 <- ggplot(data = finemap_res_gene_origin, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("Original ctwas results") +
theme_minimal()
finemap_res_gene_regionmerge$highlight <- ifelse(finemap_res_gene_regionmerge$id %in% problematic_genes, "problematic genes", "good genes")
p2 <- ggplot(data = finemap_res_gene_regionmerge, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("After region merge") +
theme_minimal()
ctwas_res_ldmismatch <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".ldmismatch_finemap_regions_res_genepip",threshold_nonSNP_PIPs,"_snpp_",threshold_SNP_p,".RDS"))
finemap_res_ldmismatch <- ctwas_res_ldmismatch$finemap_res
finemap_res_gene_ldmismatch <- finemap_res_ldmismatch[finemap_res_ldmismatch$type != "SNP",]
finemap_res_gene_ldmismatch$highlight <- ifelse(finemap_res_gene_ldmismatch$id %in% problematic_genes, "problematic genes", "good genes")
p3 <- ggplot(data = finemap_res_gene_ldmismatch, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("LD mismatch fixed -- remove the snp") +
theme_minimal()
ctwas_res_ldmismatchnoLD <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".ldmismatch_noLD_finemap_regions_res_genepip",threshold_nonSNP_PIPs,"_snpp_",threshold_SNP_p,".RDS"))
finemap_res_ldmismatchnoLD <- ctwas_res_ldmismatchnoLD$finemap_res
finemap_res_gene_ldmismatchnoLD <- finemap_res_ldmismatchnoLD[finemap_res_ldmismatchnoLD$type != "SNP",]
finemap_res_gene_ldmismatchnoLD$highlight <- ifelse(finemap_res_gene_ldmismatchnoLD$id %in% problematic_genes, "problematic genes", "good genes")
p4 <- ggplot(data = finemap_res_gene_ldmismatchnoLD, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("LD mismatch fixed -- remove the snp") +
theme_minimal()
grid::grid.newpage()
gridExtra::grid.arrange(p1,p2,p3,p4,
ncol = 4,
top = paste0(trait,"-nonSNP_PIPs:",threshold_nonSNP_PIPs,"-SNP_p:",threshold_SNP_p))
Thresholds for ld mismatch diagnosis: nonSNP PIP = 0.2, SNP p_diff = 5e-6
threshold_nonSNP_PIPs <- 0.2
threshold_SNP_p <- "5e-06"problematic_genes <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".ldmismatch_problematic_genes_genepip",threshold_nonSNP_PIPs,"_snpp_",threshold_SNP_p,".RDS"))
finemap_res_gene_origin$highlight <- ifelse(finemap_res_gene_origin$id %in% problematic_genes, "problematic genes", "good genes")
p1 <- ggplot(data = finemap_res_gene_origin, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("Original ctwas results") +
theme_minimal()
finemap_res_gene_regionmerge$highlight <- ifelse(finemap_res_gene_regionmerge$id %in% problematic_genes, "problematic genes", "good genes")
p2 <- ggplot(data = finemap_res_gene_regionmerge, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("After region merge") +
theme_minimal()
ctwas_res_ldmismatch <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".ldmismatch_finemap_regions_res_genepip",threshold_nonSNP_PIPs,"_snpp_",threshold_SNP_p,".RDS"))
finemap_res_ldmismatch <- ctwas_res_ldmismatch$finemap_res
finemap_res_gene_ldmismatch <- finemap_res_ldmismatch[finemap_res_ldmismatch$type != "SNP",]
finemap_res_gene_ldmismatch$highlight <- ifelse(finemap_res_gene_ldmismatch$id %in% problematic_genes, "problematic genes", "good genes")
p3 <- ggplot(data = finemap_res_gene_ldmismatch, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("LD mismatch fixed -- remove the snp") +
theme_minimal()
ctwas_res_ldmismatchnoLD <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".ldmismatch_noLD_finemap_regions_res_genepip",threshold_nonSNP_PIPs,"_snpp_",threshold_SNP_p,".RDS"))
finemap_res_ldmismatchnoLD <- ctwas_res_ldmismatchnoLD$finemap_res
finemap_res_gene_ldmismatchnoLD <- finemap_res_ldmismatchnoLD[finemap_res_ldmismatchnoLD$type != "SNP",]
finemap_res_gene_ldmismatchnoLD$highlight <- ifelse(finemap_res_gene_ldmismatchnoLD$id %in% problematic_genes, "problematic genes", "good genes")
p4 <- ggplot(data = finemap_res_gene_ldmismatchnoLD, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("LD mismatch fixed -- remove the snp") +
theme_minimal()
grid::grid.newpage()
gridExtra::grid.arrange(p1,p2,p3,p4,
ncol = 4,
top = paste0(trait,"-nonSNP_PIPs:",threshold_nonSNP_PIPs,"-SNP_p:",threshold_SNP_p)) 
Thresholds for ld mismatch diagnosis: nonSNP PIP = 0.2, SNP p_diff = 5e-4
threshold_nonSNP_PIPs <- 0.2
threshold_SNP_p <- "5e-04"problematic_genes <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".ldmismatch_problematic_genes_genepip",threshold_nonSNP_PIPs,"_snpp_",threshold_SNP_p,".RDS"))
finemap_res_gene_origin$highlight <- ifelse(finemap_res_gene_origin$id %in% problematic_genes, "problematic genes", "good genes")
p1 <- ggplot(data = finemap_res_gene_origin, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("Original ctwas results") +
theme_minimal()
finemap_res_gene_regionmerge$highlight <- ifelse(finemap_res_gene_regionmerge$id %in% problematic_genes, "problematic genes", "good genes")
p2 <- ggplot(data = finemap_res_gene_regionmerge, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("After region merge") +
theme_minimal()
ctwas_res_ldmismatch <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".ldmismatch_finemap_regions_res_genepip",threshold_nonSNP_PIPs,"_snpp_",threshold_SNP_p,".RDS"))
finemap_res_ldmismatch <- ctwas_res_ldmismatch$finemap_res
finemap_res_gene_ldmismatch <- finemap_res_ldmismatch[finemap_res_ldmismatch$type != "SNP",]
finemap_res_gene_ldmismatch$highlight <- ifelse(finemap_res_gene_ldmismatch$id %in% problematic_genes, "problematic genes", "good genes")
p3 <- ggplot(data = finemap_res_gene_ldmismatch, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("LD mismatch fixed -- remove the snp") +
theme_minimal()
ctwas_res_ldmismatchnoLD <- readRDS(paste0(folder_results_susieST,trait,"/",trait,".",st,".thin",thin,".",var_struc,".L",L,".ldmismatch_noLD_finemap_regions_res_genepip",threshold_nonSNP_PIPs,"_snpp_",threshold_SNP_p,".RDS"))
finemap_res_ldmismatchnoLD <- ctwas_res_ldmismatchnoLD$finemap_res
finemap_res_gene_ldmismatchnoLD <- finemap_res_ldmismatchnoLD[finemap_res_ldmismatchnoLD$type != "SNP",]
finemap_res_gene_ldmismatchnoLD$highlight <- ifelse(finemap_res_gene_ldmismatchnoLD$id %in% problematic_genes, "problematic genes", "good genes")
p4 <- ggplot(data = finemap_res_gene_ldmismatchnoLD, aes(x= abs(z), y= susie_pip, color = highlight)) +
geom_point() +
scale_color_manual(values = c("problematic genes" = "red", "good genes" = "black")) +
ggtitle("LD mismatch fixed -- remove the snp") +
theme_minimal()
grid::grid.newpage()
gridExtra::grid.arrange(p1,p2,p3,p4,
ncol = 4,
top = paste0(trait,"-nonSNP_PIPs:",threshold_nonSNP_PIPs,"-SNP_p:",threshold_SNP_p)) 
sessionInfo()R version 4.2.0 (2022-04-22)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS Linux 8
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] ggplot2_3.4.2
loaded via a namespace (and not attached):
[1] Rcpp_1.0.14 highr_0.9 pillar_1.9.0 compiler_4.2.0
[5] bslib_0.3.1 later_1.3.0 jquerylib_0.1.4 git2r_0.30.1
[9] workflowr_1.7.1 tools_4.2.0 digest_0.6.29 jsonlite_1.8.9
[13] evaluate_0.15 lifecycle_1.0.4 tibble_3.2.1 gtable_0.3.0
[17] pkgconfig_2.0.3 rlang_1.1.2 cli_3.6.2 rstudioapi_0.14
[21] crosstalk_1.2.0 yaml_2.3.5 xfun_0.38 fastmap_1.1.0
[25] gridExtra_2.3 withr_2.5.0 dplyr_1.1.2 stringr_1.5.0
[29] knitr_1.42 htmlwidgets_1.6.2 generics_0.1.3 fs_1.5.2
[33] vctrs_0.6.1 sass_0.4.1 DT_0.22 tidyselect_1.2.0
[37] rprojroot_2.0.3 grid_4.2.0 glue_1.6.2 R6_2.5.1
[41] fansi_1.0.3 rmarkdown_2.21 farver_2.1.0 magrittr_2.0.3
[45] whisker_0.4 ellipsis_0.3.2 scales_1.2.0 promises_1.2.0.1
[49] htmltools_0.5.7 colorspace_2.0-3 httpuv_1.6.5 labeling_0.4.2
[53] utf8_1.2.2 stringi_1.7.6 munsell_0.5.0