Effect of Torus Prior

Below I compare the effect of prior probabilities generated from Torus.

Breast

sumstats <- suppressMessages(vroom::vroom('../cancer-finemap/susie_finemapping/BRCA_susie_L1.txt.gz'))
sumstats.unif <- suppressMessages(vroom::vroom('../cancer-finemap/susie_finemapping/BRCA_susie_L1_UNIFORM.txt.gz'))

annots <- list.files('../cancer-finemap/torus_bed_files/BRCA', pattern = '*.bed', full.names = T)
sumstats <- annotator_merged(sumstats, annots)
sumstats$isAnnot <- factor(ifelse(sumstats$annots != "",'Annotated','None'))
sumstats$susie_pip_unif <- sumstats.unif$susie_pip

ggplot(sumstats, aes(x=susie_pip_unif, y=susie_pip, col=isAnnot)) + 
  geom_point(alpha=0.7) + 
  xlab('PIP (uniform)') + 
  ylab('PIP') + 
  geom_abline(slope = 1, color="red", linetype="dashed") + 
  scale_color_manual(values = c('red','black')) + 
  theme_bw() + 
  theme(legend.title = element_blank(),
        text = element_text(size=14),
        panel.grid.major = element_blank(), 
        panel.grid.minor = element_blank())

Colorectal

sumstats <- suppressMessages(vroom::vroom('../cancer-finemap/susie_finemapping/COAD_susie_L1.txt.gz'))
sumstats.unif <- suppressMessages(vroom::vroom('../cancer-finemap/susie_finemapping/COAD_susie_L1_UNIFORM.txt.gz'))
annots <- list.files('../cancer-finemap/torus_bed_files/COAD', pattern = '*.bed', full.names = T)

sumstats <- annotator_merged(sumstats, annots)
sumstats$isAnnot <- factor(ifelse(sumstats$annots != "",'Annotated','None'))
sumstats$susie_pip_unif <- sumstats.unif$susie_pip

ggplot(sumstats, aes(x=susie_pip_unif, y=susie_pip, col=isAnnot)) + 
  geom_point(alpha=0.7) + 
  xlab('PIP (uniform)') + 
  ylab('PIP') + 
  geom_abline(slope = 1, color="red", linetype="dashed") + 
  scale_color_manual(values = c('red','black')) + 
  theme_bw() + 
  theme(legend.title = element_blank(),
        text = element_text(size=14),
        panel.grid.major = element_blank(), 
        panel.grid.minor = element_blank())

Prostate

sumstats <- suppressMessages(vroom::vroom('../cancer-finemap/susie_finemapping/PRAD_susie_L1.txt.gz'))
sumstats.unif <- suppressMessages(vroom::vroom('../cancer-finemap/susie_finemapping/PRAD_susie_L1_UNIFORM.txt.gz'))
annots <- list.files('../cancer-finemap/torus_bed_files/PRAD', pattern = '*.bed', full.names = T)

sumstats <- annotator_merged(sumstats, annots)
sumstats$isAnnot <- factor(ifelse(sumstats$annots != "",'Annotated','None'))
sumstats$susie_pip_unif <- sumstats.unif$susie_pip

ggplot(sumstats, aes(x=susie_pip_unif, y=susie_pip, col=isAnnot)) + 
  geom_point(alpha=0.7) + 
  xlab('PIP (uniform)') + 
  ylab('PIP') + 
  geom_abline(slope = 1, color="red", linetype="dashed") + 
  scale_color_manual(values = c('red','black')) + 
  theme_bw() + 
  theme(legend.title = element_blank(),
        text = element_text(size=14),
        panel.grid.major = element_blank(), 
        panel.grid.minor = element_blank())

Ovarian

sumstats <- suppressMessages(vroom::vroom('../cancer-finemap/susie_finemapping/OV_susie_L1.txt.gz'))
sumstats.unif <- suppressMessages(vroom::vroom('../cancer-finemap/susie_finemapping/OV_susie_L1_UNIFORM.txt.gz'))
annots <- list.files('../cancer-finemap/torus_bed_files/OV', pattern = '*.bed', full.names = T)

sumstats <- annotator_merged(sumstats, annots)
sumstats$isAnnot <- factor(ifelse(sumstats$annots != "",'Annotated','None'))
sumstats$susie_pip_unif <- sumstats.unif$susie_pip

ggplot(sumstats, aes(x=susie_pip_unif, y=susie_pip, col=isAnnot)) + 
  geom_point(alpha=0.7) + 
  xlab('PIP (uniform)') + 
  ylab('PIP') + 
  geom_abline(slope = 1, color="red", linetype="dashed") + 
  scale_color_manual(values = c('red','black')) + 
  theme_bw() + 
  theme(legend.title = element_blank(),
        text = element_text(size=14),
        panel.grid.major = element_blank(), 
        panel.grid.minor = element_blank())