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Description:

  1. Logistic gwas result for all asthma, childhood asthma and adulthood asthma

  2. Survival gwas result for all asthma, childhood asthma and adulthood asthma

  3. Compare logistic and survival gwas on all asthma

  4. Compare logistic and survival gwas on COA

  5. Compare logistic and survival gwas on AOA

library(stringr)

1. Logistic gwas

file.aoa <- list.files(path="/Users/nicholeyang/Downloads/survivalsusie/data/gwas_logistic_out/aoa", pattern = "\\.glm\\.logistic$", full.names = TRUE)
file.coa <- list.files(path="/Users/nicholeyang/Downloads/survivalsusie/data/gwas_logistic_out/coa", pattern = "\\.glm\\.logistic$", full.names = TRUE)

file <- list.files(path="/Users/nicholeyang/Downloads/survivalsusie/data/gwas_logistic_out/all", pattern = "\\.glm\\.logistic$", full.names = TRUE)
par(mfrow = c(6,2))
for (i in 1:length(file)){
  region = file[i]
  region_name = strsplit(region, "/")[[1]][9]
  gwas = read.csv(region, header = TRUE, sep = "\t")
  plot(gwas$POS, -log10(gwas$P), pch = 20, cex = 0.5, main = region_name, ylab = "log10-pval", xlab = "Position")
}

Version Author Date
1e17a25 yunqiyang0215 2024-06-17 
par(mfrow = c(6,2))
for (i in 1:length(file.aoa)){
  region.aoa = file.aoa[i]
  region.coa = file.coa[i]
  region_name = strsplit(region.aoa, "/")[[1]][9]
  gwas.aoa = read.csv(region.aoa, header = TRUE, sep = "\t")
  gwas.coa = read.csv(region.coa, header = TRUE, sep = "\t")
  ymin = min(log10(gwas.aoa$P)) - 1
  ymax = max(-log10(gwas.coa$P)) + 2
  plot(gwas.aoa$POS, log10(gwas.aoa$P), ylim = c(ymin, ymax), pch = 20, cex = 0.5, col = "#2c7fb8", main = region_name, ylab = "log10-pval", xlab = "Position")
  points(gwas.coa$POS, -log10(gwas.coa$P), pch = 20, cex = 0.5, col = "#de2d26")
  legend("topright", legend = c("COA", "AOA"), col = c("#de2d26", "#2c7fb8"), pch = 20)
}

Version Author Date
1e17a25 yunqiyang0215 2024-06-17

2. Survival gwas

path_to_files = "/Users/nicholeyang/Downloads/survivalsusie/result/gwas_surv"
file.aoa <- list.files(path = path_to_files, pattern = "^aoa.*\\.rds$", full.names = TRUE)
file.coa <- list.files(path = path_to_files, pattern = "^coa.*\\.rds$", full.names = TRUE)
file <- list.files(path = path_to_files, pattern = "^all.*\\.rds$", full.names = TRUE)
par(mfrow = c(6,2))
pattern <- "chr[0-9XYM]+_[0-9]+_[0-9]+"
for (i in 1:length(file)){
  region = file[i]
  region_name = str_extract(region, pattern)
  gwas = readRDS(region)
  plot(-log10(gwas[, 'p.value.spa']), pch = 20, cex = 0.5, main = region_name, ylab = "log10-pval", xlab = "Position")
}

Version Author Date
d61db5c yunqiyang0215 2024-07-03
7c1eda4 yunqiyang0215 2024-06-18
1455c77 yunqiyang0215 2024-06-18
bd3def9 yunqiyang0215 2024-06-17
1e17a25 yunqiyang0215 2024-06-17 
par(mfrow = c(6,2))
for (i in 1:length(file.aoa)){
  region.aoa = file.aoa[i]
  region.coa = file.coa[i]
  region_name = str_extract(region.aoa, pattern)
  gwas.aoa = readRDS(region.aoa)
  gwas.coa = readRDS(region.coa)
  ymin = min(log10(gwas.aoa[, 'p.value.spa']), na.rm = TRUE) - 1
  ymax = max(-log10(gwas.coa[, 'p.value.spa']), na.rm = TRUE) + 2
  plot(log10(gwas.aoa[, 'p.value.spa']), ylim = c(ymin, ymax), pch = 20, cex = 0.5, col = "#2c7fb8", main = region_name, ylab = "log10-pval", xlab = "Position")
  points(-log10(gwas.coa[, 'p.value.spa']), pch = 20, cex = 0.5, col = "#de2d26")
  legend("topright", legend = c("COA", "AOA"), col = c("#de2d26", "#2c7fb8"), pch = 20)
}

Version Author Date
6c46561 yunqiyang0215 2024-07-25
d61db5c yunqiyang0215 2024-07-03
7c1eda4 yunqiyang0215 2024-06-18
1455c77 yunqiyang0215 2024-06-18
bd3def9 yunqiyang0215 2024-06-17
1e17a25 yunqiyang0215 2024-06-17 
pdf("/Users/nicholeyang/Downloads/survival-data-analysis/output/Fig_gwas_coa_aoa.pdf", width = 10, height = 8)
par(mfrow = c(2,2))
indx = c(1, 2, 4, 9)
labels = c("(a)", "(b)", "(c)", "(d)")
region_name = c("1q21.3", "10p14", "12q13.11", "2q12.1")
for (i in 1:length(indx)){
  region.aoa = file.aoa[indx[i]]
  region.coa = file.coa[indx[i]]
  gwas.aoa = readRDS(region.aoa)
  gwas.coa = readRDS(region.coa)
  
  ymin = min(log10(gwas.aoa[, 'p.value.spa']), na.rm = TRUE) - 1
  ymax = max(-log10(gwas.coa[, 'p.value.spa']), na.rm = TRUE) + 2
  
  plot(log10(gwas.aoa[, 'p.value.spa']), ylim = c(ymin, ymax), pch = 20, cex = 0.5, col = "#2c7fb8", main = region_name[i], ylab = "-log10(P value)", xlab = "", axes = FALSE)
  points(-log10(gwas.coa[, 'p.value.spa']), pch = 20, cex = 0.5, col = "#de2d26")
  
  # Custom y-axis ticks and labels
  y_ticks_pos <- seq(0, ymax, by = 5)
  y_ticks_neg <- seq(0, abs(ymin), by = 5)
  
  axis(2, at = c(-rev(y_ticks_neg), y_ticks_pos), labels = c(rev(y_ticks_neg), y_ticks_pos), las = 1)
  
  box()  # Adding box around the plot
  
  legend("topright", legend = c("COA", "AOA"), col = c("#de2d26", "#2c7fb8"), pch = 20)
  mtext("Position", side = 1, line = 3, adj = 0.5, cex = 0.8)
  mtext(labels[i], side = 1, line = 4, adj = 0.5, cex = 1)
}

3. Compare logistic gwas and survival gwas

file.logistic <- list.files(path="/Users/nicholeyang/Downloads/survivalsusie/data/gwas_logistic_out/all", pattern = "\\.glm\\.logistic$", full.names = TRUE)
file.survival <- list.files(path = "/Users/nicholeyang/Downloads/survivalsusie/result/gwas_surv", pattern = "^all.*\\.rds$", full.names = TRUE)
par(mfrow = c(6,2))

pattern <- "chr[0-9XYM]+_[0-9]+_[0-9]+"
for (i in 1:length(file.survival)){
  region = file.survival[i]
  region_name = str_extract(region, pattern)

  path.logistic = paste0("/Users/nicholeyang/Downloads/survivalsusie/data/gwas_logistic_out/all/gwas_", 
                         region_name, ".asthma.glm.logistic")
  
  # read in gwas results
  gwas.logistic = read.csv(path.logistic, header = TRUE, sep = "\t")
  gwas.survival = data.frame(readRDS(region))
  
  # merge two datasets
  snp_ids = sapply(rownames(gwas.survival), function(x) unlist(strsplit(x, "_"))[1])
  gwas.survival$ID = snp_ids
  dat = merge(gwas.logistic, gwas.survival, by = "ID")
  plot(dat$POS, -log10(dat$P), pch = 20, cex = 0.5, main = region_name, ylab = "log10-pval", xlab = "Position", ylim = c(0, max(-log10(dat$P), -log10(dat$p.value.spa)) + 1), col = "#de2d26")
  points(dat$POS, -log10(dat$p.value.spa), pch = 20, cex = 0.5)
  
  legend("topright", legend = c("logistic.gwas", "survival.gwas"), col = c("#de2d26", 1), pch = 20)
}

Version Author Date
f68b8d1 yunqiyang0215 2024-07-03

4. Compare logistic gwas and survival gwas on COA

file.logistic <- list.files(path="/Users/nicholeyang/Downloads/survivalsusie/data/gwas_logistic_out/coa", pattern = "\\.glm\\.logistic$", full.names = TRUE)
file.survival <- list.files(path = "/Users/nicholeyang/Downloads/survivalsusie/result/gwas_surv", pattern = "^coa.*\\.rds$", full.names = TRUE)
par(mfrow = c(6,2))

pattern <- "chr[0-9XYM]+_[0-9]+_[0-9]+"
for (i in 1:length(file.survival)){
  region = file.survival[i]
  region_name = str_extract(region, pattern)

  path.logistic = paste0("/Users/nicholeyang/Downloads/survivalsusie/data/gwas_logistic_out/coa/gwas_", 
                         region_name, ".asthma_coa.glm.logistic")
  
  # read in gwas results
  gwas.logistic = read.csv(path.logistic, header = TRUE, sep = "\t")
  gwas.survival = data.frame(readRDS(region))
  
  # merge two datasets
  snp_ids = sapply(rownames(gwas.survival), function(x) unlist(strsplit(x, "_"))[1])
  gwas.survival$ID = snp_ids
  dat = merge(gwas.logistic, gwas.survival, by = "ID")
  plot(dat$POS, -log10(dat$P), pch = 20, cex = 0.5, main = region_name, ylab = "log10-pval", xlab = "Position", ylim = c(0, max(-log10(dat$P), -log10(dat$p.value.spa), na.rm = TRUE) + 1), col = "#de2d26")
  points(dat$POS, -log10(dat$p.value.spa), pch = 20, cex = 0.5)
  
  legend("topright", legend = c("logistic.gwas", "survival.gwas"), col = c("#de2d26", 1), pch = 20)
}

Version Author Date
6c46561 yunqiyang0215 2024-07-25
f68b8d1 yunqiyang0215 2024-07-03

5. Compare logistic gwas and survival gwas on AOA

file.logistic <- list.files(path="/Users/nicholeyang/Downloads/survivalsusie/data/gwas_logistic_out/aoa", pattern = "\\.glm\\.logistic$", full.names = TRUE)
file.survival <- list.files(path = "/Users/nicholeyang/Downloads/survivalsusie/result/gwas_surv", pattern = "^aoa.*\\.rds$", full.names = TRUE)
par(mfrow = c(6,2))

pattern <- "chr[0-9XYM]+_[0-9]+_[0-9]+"
for (i in 1:length(file.survival)){
  region = file.survival[i]
  region_name = str_extract(region, pattern)

  path.logistic = paste0("/Users/nicholeyang/Downloads/survivalsusie/data/gwas_logistic_out/aoa/gwas_", 
                         region_name, ".asthma_aoa.glm.logistic")
  
  # read in gwas results
  gwas.logistic = read.csv(path.logistic, header = TRUE, sep = "\t")
  gwas.survival = data.frame(readRDS(region))
  
  # merge two datasets
  snp_ids = sapply(rownames(gwas.survival), function(x) unlist(strsplit(x, "_"))[1])
  gwas.survival$ID = snp_ids
  dat = merge(gwas.logistic, gwas.survival, by = "ID")
  plot(dat$POS, -log10(dat$P), pch = 20, cex = 0.5, main = region_name, ylab = "log10-pval", xlab = "Position", ylim = c(0, max(-log10(dat$P), -log10(dat$p.value.spa), na.rm = TRUE) + 1), col = "#de2d26")
  points(dat$POS, -log10(dat$p.value.spa), pch = 20, cex = 0.5)
  
  legend("topright", legend = c("logistic.gwas", "survival.gwas"), col = c("#de2d26", 1), pch = 20)
}

Version Author Date
6c46561 yunqiyang0215 2024-07-25
f68b8d1 yunqiyang0215 2024-07-03 

sessionInfo()
R version 4.1.1 (2021-08-10)
Platform: x86_64-apple-darwin20.6.0 (64-bit)
Running under: macOS Monterey 12.0.1

Matrix products: default
BLAS:   /usr/local/Cellar/openblas/0.3.18/lib/libopenblasp-r0.3.18.dylib
LAPACK: /usr/local/Cellar/r/4.1.1_1/lib/R/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

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

other attached packages:
[1] stringr_1.4.0   workflowr_1.6.2

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.8.3     rstudioapi_0.13  whisker_0.4      knitr_1.36      
 [5] magrittr_2.0.1   R6_2.5.1         rlang_1.1.1      fastmap_1.1.0   
 [9] fansi_0.5.0      highr_0.9        tools_4.1.1      xfun_0.27       
[13] utf8_1.2.2       cli_3.6.1        git2r_0.28.0     jquerylib_0.1.4 
[17] htmltools_0.5.5  ellipsis_0.3.2   rprojroot_2.0.2  yaml_2.2.1      
[21] digest_0.6.28    tibble_3.1.5     lifecycle_1.0.3  later_1.3.0     
[25] sass_0.4.4       vctrs_0.6.3      promises_1.2.0.1 fs_1.5.0        
[29] cachem_1.0.6     glue_1.4.2       evaluate_0.14    rmarkdown_2.11  
[33] stringi_1.7.5    bslib_0.4.1      compiler_4.1.1   pillar_1.9.0    
[37] jsonlite_1.7.2   httpuv_1.6.3     pkgconfig_2.0.3