S-LDSC results for Corspan, Robospan and pRobospan gene prioritizations

Last updated: 2020-06-09

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Here we present S-LDSC results for Corspan, Robospan and pRobospan gene prioritizations.

library(data.table)
library(ggplot2)

Warning: package 'ggplot2' was built under R version 3.5.2

library(latex2exp)
require(gridExtra)

Loading required package: gridExtra

library(xtable)

Warning: package 'xtable' was built under R version 3.5.2

scaleFUN <- function(x) sprintf("%.1f", x)

tau1 = c(0.04, 0.038)
taus1 = c(0.024, 0.02)
tau2 = c(0.086, 0.12)
taus2 = c(0.024, 0.03)
tau3 = c(0.096, 0.11)
taus3 = c(0.028, 0.034)

annots_pre = c("5kb", "100kb")
annots = factor(rep(annots_pre, 3), levels = annots_pre)

model = factor(c(rep("Corspan",2), rep("Robospan",2), rep("pRobospan", 2)),
               levels = c("Corspan", "Robospan", "pRobospan"))

df = data.frame(tau = c(tau1, tau2, tau3),
                tau_sd = c(taus1, taus2, taus3),
                class_annots = model,
                model = model,
                annots = annots)

colors2 =  rep("black", 18)
colors2[1:5] = "gray60"
colors2[6:10] = "red"
colors2[11:15] = "blue"

p3 = ggplot(df, aes(x=annots, y=tau, fill=df$model)) +
  geom_bar(position="dodge", stat="identity", colour = "black", size = 1.3) +
  geom_errorbar(aes(ymin=tau-1.96*tau_sd, ymax=tau+1.96*tau_sd),
                width=.5,
                position = position_dodge(.9)) +
  guides(fill=guide_legend(title="")) +
  labs(x = "", y = TeX('$\\tau^ *$')) +
  theme(axis.title.x = element_text(size=1)) +
  scale_fill_manual(values=c("gray60", "red", "blue")) +
  scale_color_manual(values=c("gray60", "red", "blue")) +
  theme(axis.text.x = element_text(angle = 70, hjust = 1, size = 30,
                                   color="black"), legend.position="top") +
    scale_alpha_continuous(range(0,1), guide = FALSE)  +
    ggtitle(TeX('$\\tau^ *$, meta-analyzed across 11 Blood + Autoimmune traits')) + 
    theme(plot.title = element_text(size = 35, face = "bold", hjust = 0.5)) +
    theme(legend.text=element_text(size=35)) +
    theme(axis.title.y = element_text(size = 40)) + theme(axis.text.y = element_text(size = 40)) + 
    theme(panel.background = element_blank(), axis.line = element_line(colour = "black")) 
p3 

Warning: Use of `df$model` is discouraged. Use `model` instead.

Warning: Use of `df$model` is discouraged. Use `model` instead.

tau1 = c(2.4, 2.1)
taus1 = c(0.15, 0.1)
tau2 = c(2.7, 2.3)
taus2 = c(0.16, 0.12)
tau3 = c(3.2, 2.4)
taus3 = c(0.22, 0.12)

annots_pre = c( "5kb", "100kb")
annots = factor(rep(annots_pre, 3), levels = annots_pre)

model = factor(c(rep("Corspan",2), rep("Robospan",2), rep("pRobospan", 2)),
               levels = c("Corspan", "Robospan", "pRobospan"))

df = data.frame(tau = c(tau1, tau2, tau3),
                tau_sd = c(taus1, taus2, taus3),
                class_annots = model,
                model = model,
                annots = annots)

colors2 =  rep("black", 18)
colors2[1:5] = "gray60"
colors2[6:10] = "red"
colors2[11:15] = "blue"

p3 = ggplot(df, aes(x=annots, y=tau, fill=df$model)) +
  geom_bar(position="dodge", stat="identity", colour = "black", size = 1.3) +
  geom_errorbar(aes(ymin=tau-1.96*tau_sd, ymax=tau+1.96*tau_sd),
                width=.5,
                position = position_dodge(.9)) +
  guides(fill=guide_legend(title="")) +
  labs(x = "", y = TeX('Enrichment')) +
  theme(axis.title.x = element_text(size=1)) +
  scale_fill_manual(values=c("gray60", "red", "blue")) +
  scale_color_manual(values=c("gray60", "red", "blue")) +
  theme(axis.text.x = element_text(angle = 70, hjust = 1, size = 30,
                                   color="black"), legend.position="top") +
    scale_alpha_continuous(range(0,1), guide = FALSE)  +
    ggtitle(TeX('ENR, meta-analyzed across 11 Blood + Autoimmune traits')) + 
    theme(plot.title = element_text(size = 35, face = "bold", hjust = 0.5)) +
    theme(legend.text=element_text(size=35)) +
    theme(axis.title.y = element_text(size = 40)) + theme(axis.text.y = element_text(size = 40)) + 
    theme(panel.background = element_blank(), axis.line = element_line(colour = "black")) +
    geom_hline(yintercept=1,  color = "black", linetype = "dashed")
p3 

Warning: Use of `df$model` is discouraged. Use `model` instead.

Warning: Use of `df$model` is discouraged. Use `model` instead.

sessionInfo()

R version 3.5.1 (2018-07-02)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS High Sierra 10.13.6

Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/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] xtable_1.8-4      gridExtra_2.3     latex2exp_0.4.0   ggplot2_3.3.0    
[5] data.table_1.11.8

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.1        compiler_3.5.1    pillar_1.3.1     
 [4] git2r_0.23.0      workflowr_1.1.1   R.methodsS3_1.7.1
 [7] R.utils_2.7.0     tools_3.5.1       digest_0.6.19    
[10] evaluate_0.12     tibble_2.1.1      gtable_0.3.0     
[13] pkgconfig_2.0.2   rlang_0.4.2       yaml_2.2.0       
[16] withr_2.1.2       stringr_1.4.0     dplyr_0.8.0.1    
[19] knitr_1.20        rprojroot_1.3-2   grid_3.5.1       
[22] tidyselect_0.2.5  glue_1.3.1        R6_2.4.0         
[25] rmarkdown_1.10    purrr_0.3.2       magrittr_1.5     
[28] whisker_0.3-2     backports_1.1.4   scales_1.0.0     
[31] htmltools_0.3.6   assertthat_0.2.1  colorspace_1.4-1 
[34] labeling_0.3      stringi_1.4.3     munsell_0.5.0    
[37] crayon_1.3.4      R.oo_1.22.0      

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