Chapter 6 Shotgun metagenomic sequencing: Evaluate genes of interest (figure 5, supplement figure 10)

6.1 BSH

6.1.1 Evaluate BSH abundance at peri-GVHD onset

BSH_metalphlan %>% 
  left_join(cohort_BAS) %>% 
  filter(later=="Y") %>% 
  ggplot(aes(x=GI_GVHD, y=log10(cpm+0.55), color=GI_GVHD))+
  geom_boxplot(width=0.2, lwd=0.8, outlier.shape = NA) +
  geom_jitter(width=0.3, alpha=0.3, size=2.5)+
  ylab("log10(BSH)")+
  xlab("")+
  theme_classic()+
  stat_compare_means(comparisons=list(c("Y", "N")),
                     method="wilcox.test",
                     correct=FALSE)+
  scale_color_manual(values=c("dodgerblue4", "red3"))+
  theme(legend.position="none")

6.1.2 Evaluate BSH abundance at peri-engraftment time point

BSH_metalphlan %>% 
  left_join(cohort_BAS) %>% 
  filter(periengr=="Y") %>% 
  ggplot(aes(x=GI_GVHD, y=log10(cpm+0.05), color=GI_GVHD))+
  geom_boxplot(width=0.2, lwd=0.8, outlier.shape = NA) +
  geom_jitter(width=0.3, alpha=0.3, size=2.5)+
  ylab("log10(BSH)")+
  xlab("")+
  theme_classic()+
  stat_compare_means(comparisons=list(c("Y", "N")),
                     method="wilcox.test",
                     correct=FALSE)+
  scale_color_manual(values=c("dodgerblue4", "red3"))+
  theme(legend.position="none")

6.2 Bai operon gene

6.2.1 Evaluate correlation of bai operon gene sum and nonUDCA secondary BAs

bai_genes_clean %>% 
  distinct(sampleid, bai_operon_sum ) %>% 
  inner_join(both_conc_pools_final) %>% 
  ggplot(aes(x=log(secondary_nonUDCA), y=log(bai_operon_sum+0.05)))+
  geom_point(alpha=0.6)+
  stat_cor(method="pearson")+
  geom_smooth(method="lm")+
  theme_classic()+
  ylab("bai operon log10(cpm)")+
  xlab("SBAs* log10(pmol/mg)")

6.2.2 Bai operon gene sum in peri-GVHD onset

bai_genes_clean %>% 
  distinct(sampleid, bai_operon_sum ) %>% 
  inner_join(cohort_BAS %>% select(sampleid, GI_GVHD, later, ursodiol) %>% filter(later=="Y")) %>% 
  ggplot(aes(x=GI_GVHD, y=log(bai_operon_sum+0.01), color=GI_GVHD))+
  geom_boxplot(width=0.2, lwd=0.8, outlier.shape = NA) +
  geom_jitter(width=0.3, alpha=0.3, size=2.5) +
  ylab("log10(bai_operon_sum)") +
  xlab("") +
  theme_classic() +
  stat_compare_means(comparisons=list(c("Y", "N")),
                     method="wilcox.test",
                     correct=FALSE)+
  scale_color_manual(values=c("dodgerblue4", "red3")) +
  theme(legend.position="none")

6.2.3 Bai operon individual gene abundance

bai_genes_clean %>% 
  inner_join(cohort_BAS %>% select(sampleid, GI_GVHD, later) %>% filter(later=="Y")) %>% 
  ggplot(aes(x=GI_GVHD, y=log(cpm+0.01), color=GI_GVHD))+
  geom_boxplot(width=0.2, lwd=0.8, outlier.shape = NA) +
  geom_jitter(width=0.3, alpha=0.3, size=2.5)+
  ylab("log10(cpm)")+
  xlab("")+
  theme_classic()+
  stat_compare_means(comparisons=list(c("Y", "N")),
                     method="wilcox.test",
                     correct=FALSE)+
  scale_color_manual(values=c("dodgerblue4", "red3"))+
  theme(legend.position="none")+
  facet_grid(.~gene)