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4_unconstrained PCoA.R
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4_unconstrained PCoA.R
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##Calculate contribution of each factor to compositional varations estimated by beta diversity (PCoA)
order.diagnosis <- c("control", "RA")
order.active_disease <- c('control', '0', "1", '2','3')
b.meta <- sample_data(bac.clean.log)
b.meta <- data.frame(b.meta)
b.meta$exercise_light <- as.character(b.meta$exercise_light)
b.meta$exercise_oderate <- as.character(b.meta$exercise_oderate)
b.meta$exercise_heavy <- as.character(b.meta$exercise_heavy)
b.meta$active_disease <- as.character(b.meta$active_disease)
b.meta$Duration <- as.character(b.meta$Duration)
b.meta$TNF_inhibitor <- as.character(b.meta$TNF_inhibitor)
b.meta$GC <- as.character(b.meta$GC)
b.meta$MTX <- as.character(b.meta$MTX)
b.meta$seropositive_RA <- as.character(b.meta$seropositive_RA)
b.meta$Diagnosis <- factor(b.meta$Diagnosis, levels = order.diagnosis)
b.meta$active_disease <- factor(b.meta$active_disease, levels = order.active_disease)
sample_data(bac.clean.log) <- sample_data(b.meta)
sample_data(bac.clean.ss) <- sample_data(b.meta)
sample_data(bac.clean.nolog) <-sample_data(b.meta)
bac.clean.log
bac.clean.nolog
bac.clean.ss.rel
bray1.bac <- ordinate(bac.clean.log, 'PCoA', 'bray')
sample_data(bac.clean.log) <- sample_data(b.meta)
#cap_uni <- ordinate(bac.clean.log, 'CAP', 'unifrac', weight = TRUE, ~ Diagnosis)
write.csv(bray1.bac$vectors, "Supplementary Fig. A_PCoA.csv")
write.csv(b.meta, "Source data for PCoA and CAP_bac.csv")
write.csv(f.meta, "Source data for PCoA and CAP_fun.csv")
#bray3.bac <- ordinate(bac.clean.log, 'PCoA', 'unifrac')
##Unconstrained PCoA
#Control vs RA
plot_ordination(bac.clean.log, bray1.bac, type = "samples", color='Diagnosis', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+ scale_color_manual(values=c("control" = "#6699CC", "RA" = "#CC9900"))+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
#Treatment
plot_ordination(bac.clean.log, bray1.bac, type = "samples", color='treatment', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+ #scale_color_manual(values=c("control" = "#6699CC", "RA" = "#CC9900"))+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
#Age
plot_ordination(bac.clean.ss.rel, bray1.bac, type = "samples", color='Age', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+
scale_colour_gradient(low = "darkgreen",
high = "gold3",
space = "Lab",
na.value = "grey50",
guide = "colourbar",
aesthetics = "colour")+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
## MTX
plot_ordination(bac.clean.log, bray1.bac, type = "samples", color='MTX', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+ #scale_color_manual(values=c("control" = "#6699CC", "RA" = "#CC9900"))+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
### CAP (Canonical analysis of principals)
##Relative abundance
b.cap.diagnosis <- ordinate(bac.clean.ss.rel, "CAP", "bray", ~ Diagnosis)
perm_anova.ord <- anova.cca(b.cap.diagnosis)
perm_anova.ord2 <- permutest(b.cap.diagnosis)
## Plotting
# Diagnosis
plot.b.cap.type <- plot_ordination(bac.clean.ss.rel, b.cap.diagnosis, type = "samples", color='Diagnosis', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+ scale_color_manual(values=c("control" = "#6699CC", "RA" = "#CC9900"))+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
plot.b.cap.type
##Duration
b.cap.duration <- ordinate(bac.clean.ss.rel, "CAP", "bray", ~ Duration)
perm_anova.ord <- anova.cca(b.cap.duration)
perm_anova.ord2 <- permutest(b.cap.duration)
## Plotting
plot.b.cap.duration <- plot_ordination(bac.clean.ss.rel, b.cap.duration, type = "samples", color='Duration', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+ #scale_color_manual(values=c("control" = "#6699CC", "RA" = "#CC9900"))+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
plot.b.cap.duration
##Active disease
b.cap.active <- ordinate(bac.clean.ss.rel, "CAP", "bray", ~ active_disease)
perm_anova.ord <- anova.cca(b.cap.active)
perm_anova.ord2 <- permutest(b.cap.active)
## Plotting
plot.b.cap.active <- plot_ordination(bac.clean.ss.rel, b.cap.active, type = "samples", color='active_disease', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+ #scale_color_manual(values=c("control" = "#6699CC", "RA" = "#CC9900"))+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
plot.b.cap.active
##Age
b.cap.age <- ordinate(bac.clean.ss.rel, "CAP", "bray", ~ Age)
perm_anova.ord <- anova.cca(b.cap.age)
perm_anova.ord2 <- permutest(b.cap.age)
## Plotting
plot.b.cap.age <- plot_ordination(bac.clean.ss.rel, b.cap.age, type = "samples", color='Age', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+
scale_colour_gradient(low = "darkgreen",
high = "gold3",
space = "Lab",
na.value = "grey50",
guide = "colourbar",
aesthetics = "colour")+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
plot.b.cap.age
##Normalized abundance
b.cap.diagnosis <- ordinate(bac.clean.nolog, "CAP", "bray", ~ Diagnosis)
perm_anova.ord <- anova.cca(b.cap.diagnosis)
perm_anova.ord2 <- permutest(b.cap.diagnosis)
## Plotting
# Diagnosis
plot.b.cap.type <- plot_ordination(bac.clean.nolog, b.cap.diagnosis, type = "samples", color='Diagnosis', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+ scale_color_manual(values=c("control" = "#6699CC", "RA" = "#CC9900"))+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
plot.b.cap.type
##Duration
b.cap.duration <- ordinate(bac.clean.nolog, "CAP", "bray", ~ Duration)
perm_anova.ord <- anova.cca(b.cap.duration)
perm_anova.ord2 <- permutest(b.cap.duration)
## Plotting
plot.b.cap.duration <- plot_ordination(bac.clean.nolog, b.cap.duration, type = "samples", color='Duration', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+ #scale_color_manual(values=c("control" = "#6699CC", "RA" = "#CC9900"))+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
plot.b.cap.duration
##Active disease
b.cap.active <- ordinate(bac.clean.nolog, "CAP", "bray", ~ active_disease)
perm_anova.ord <- anova.cca(b.cap.active)
perm_anova.ord2 <- permutest(b.cap.active)
## Plotting
plot.b.cap.active <- plot_ordination(bac.clean.nolog, b.cap.active, type = "samples", color='active_disease', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+ #scale_color_manual(values=c("control" = "#6699CC", "RA" = "#CC9900"))+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
plot.b.cap.active
##Age
b.cap.age <- ordinate(bac.clean.nolog, "CAP", "bray", ~ Age)
perm_anova.ord <- anova.cca(b.cap.age)
perm_anova.ord2 <- permutest(b.cap.age)
## Plotting
plot.b.cap.age <- plot_ordination(bac.clean.nolog, b.cap.age, type = "samples", color='Age', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+
scale_colour_gradient(low = "darkgreen",
high = "gold3",
space = "Lab",
na.value = "grey50",
guide = "colourbar",
aesthetics = "colour")+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
plot.b.cap.age
##Normalized abundance and log transformed
b.cap.diagnosis <- ordinate(bac.clean.log.2, "CAP", "bray", ~ Diagnosis)
b.cap.diagnosis$CCA$Xbar
write.csv(f.cap.diagnosis$CCA$Xbar,"Fig. 2A_fun.csv")
perm_anova.ord <- anova.cca(b.cap.diagnosis)
perm_anova.ord2 <- permutest(b.cap.diagnosis)
## Plotting
# Diagnosis
plot.b.cap.type <- plot_ordination(bac.clean.log.2, b.cap.diagnosis, type = "samples", color='Blautia', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+ #scale_color_manual(values=c("control" = "#6699CC", "RA" = "#CC9900"))+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
plot.b.cap.type
##Duration
b.cap.duration <- ordinate(bac.clean.log, "CAP", "bray", ~ Duration)
perm_anova.ord <- anova.cca(b.cap.duration)
perm_anova.ord2 <- permutest(b.cap.duration)
## Plotting
plot.b.cap.duration <- plot_ordination(bac.clean.log, b.cap.duration, type = "samples", color='Duration', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+ #scale_color_manual(values=c("control" = "#6699CC", "RA" = "#CC9900"))+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
plot.b.cap.duration
##Active disease
b.cap.active <- ordinate(bac.clean.log, "CAP", "bray", ~ active_disease)
perm_anova.ord <- anova.cca(b.cap.active)
perm_anova.ord2 <- permutest(b.cap.active)
## Plotting
plot.b.cap.active <- plot_ordination(bac.clean.log, b.cap.active, type = "samples", color='active_disease', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+ #scale_color_manual(values=c("control" = "#6699CC", "RA" = "#CC9900"))+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
plot.b.cap.active
##Age
b.cap.age <- ordinate(bac.clean.log, "CAP", "bray", ~ Age)
perm_anova.ord <- anova.cca(b.cap.age)
perm_anova.ord2 <- permutest(b.cap.age)
## Plotting
plot.b.cap.age <- plot_ordination(bac.clean.log, b.cap.age, type = "samples", color='Age', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+
scale_colour_gradient(low = "darkgreen",
high = "gold3",
space = "Lab",
na.value = "grey50",
guide = "colourbar",
aesthetics = "colour")+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
plot.b.cap.age
##Active disease
b.cap.active <- ordinate(bac.clean.log, "CAP", "bray", ~ TX)
perm_anova.ord <- anova.cca(b.cap.active)
perm_anova.ord2 <- permutest(b.cap.active)
## Plotting
plot.b.cap.active <- plot_ordination(bac.clean.log, b.cap.active, type = "samples", color='TX', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+ #scale_color_manual(values=c("control" = "#6699CC", "RA" = "#CC9900"))+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
plot.b.cap.active
##MTX
b.cap.active <- ordinate(bac.clean.log, "CAP", "bray", ~ MTX)
perm_anova.ord <- anova.cca(b.cap.active)
perm_anova.ord2 <- permutest(b.cap.active)
## Plotting
plot.b.cap.active <- plot_ordination(bac.clean.log, b.cap.active, type = "samples", color='MTX', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+ #scale_color_manual(values=c("control" = "#6699CC", "RA" = "#CC9900"))+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
plot.b.cap.active
## Only RA samples
bac.clean.log.RA
b.meta.ra$active_disease <- as.character(b.meta.ra$active_disease)
sample_data(bac.clean.log.RA) <- sample_data(b.meta.ra)
#Active disease
b.cap.active <- ordinate(bac.clean.log.RA, "CAP", "bray", ~ active_disease)
perm_anova.ord <- anova.cca(b.cap.active)
perm_anova.ord2 <- permutest(b.cap.active)
## Plotting
# Diagnosis
plot.b.cap.active <- plot_ordination(bac.clean.log.RA, b.cap.active, type = "samples", color='active_disease', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+ #scale_color_manual(values=c("control" = "#6699CC", "RA" = "#CC9900"))+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
plot.b.cap.active
#Duration
b.cap.duration <- ordinate(bac.clean.log.RA, "CAP", "bray", ~ Duration)
perm_anova.ord <- anova.cca(b.cap.duration)
perm_anova.ord2 <- permutest(b.cap.duration)
## Plotting
# Diagnosis
plot.b.cap.duration <- plot_ordination(bac.clean.log.RA, b.cap.duration, type = "samples", color='Duration', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+ #scale_color_manual(values=c("control" = "#6699CC", "RA" = "#CC9900"))+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
plot.b.cap.duration
###PERMANOVA
## ALL
bac.clean.ss.rel
bac.clean.log
bac.clean.nolog
b.otu <- otu_table(bac.clean.log)
b.meta <- sample_data(bac.clean.log)
b.meta <- data.frame(b.meta)
##new variable for active disease
b.meta$active_disease_2 <- b.meta$active_disease
b.meta$active_disease_2<-as.character(b.meta$active_disease_2)
b.meta$active_disease_2[which(b.meta$active_disease_2 %in% c("0", "1"))] <- "low"
b.meta$active_disease_2[which(b.meta$active_disease_2 %in% c("2", "3"))] <- "high"
b.permanova <- adonis(formula = t(b.otu) ~ (Diagnosis+RA_factor+anti_CCP+seropositive_RA+GC+MTX+TNF_inhibitor+exercise_light+exercise_oderate+exercise_heavy+active_disease_2+Duration+Age+BMI+autoimmune_disease+diabetes), data = b.meta, permutations=9999, method = "bray")
b.permanova
b.permanova <- adonis(formula = t(b.otu) ~ (TNF_inhibitor+TX), data = b.meta, permutations=9999, method = "bray")
b.permanova
##Only RA
bac.clean.ss.RA <- subset_samples(bac.clean.ss, Diagnosis == "RA")
bac.clean.ss.RA <- phyloseq::filter_taxa(bac.clean.ss.RA, function(x) sum(x) != 0, TRUE) # 1339 OTUs
bac.clean.ss.RA.rel <- microbiome::transform(bac.clean.ss.RA, "compositional")
t(otu_table(bac.clean.ss.RA.rel))
bac.clean.log.RA <- subset_samples(bac.clean.log, Diagnosis == "RA")
bac.clean.log.RA <- phyloseq::filter_taxa(bac.clean.log.RA, function(x) sum(x) != 0, TRUE) # 1339 OTUs
bac.clean.nolog.RA <- subset_samples(bac.clean.nolog, Diagnosis == "RA")
bac.clean.nolog.RA <- phyloseq::filter_taxa(bac.clean.nolog.RA, function(x) sum(x) != 0, TRUE) # 1339 OTUs
b.meta.ra <- sample_data(bac.clean.ss.RA)
b.meta.ra <- data.frame(b.meta.ra)
b.meta.ra$active_disease_2 <- b.meta.ra$active_disease
b.meta.ra$active_disease_2<-as.character(b.meta.ra$active_disease_2)
b.meta.ra$active_disease_2[which(b.meta.ra$active_disease_2 %in% c("0", "1"))] <- "low"
b.meta.ra$active_disease_2[which(b.meta.ra$active_disease_2 %in% c("2", "3"))] <- "high"
head(b.meta.ra)
class(b.meta.ra$Ds_Duration)
b.meta.ra$Ds_Duration <- as.numeric(as.character(b.meta.ra$Ds_Duration))
b.otu.ra <- otu_table(bac.clean.log.RA)
b.permanova.ra <- adonis(formula = t(b.otu.ra) ~ (RA_factor+anti_CCP+seropositive_RA+GC+TX+TNF_inhibitor+functionalfood_type+exercise_light+exercise_oderate+exercise_heavy+active_disease_2+Duration+Age+BMI+autoimmune_disease+diabetes), data = b.meta.ra, permutations=9999, method = "bray")
b.permanova.ra
b.permanova.ra <- adonis(formula = t(b.otu.ra) ~ (RA_factor+anti_CCP+BMI+Age+Ds_Duration), data = b.meta.ra, permutations=9999, method = "bray")
b.permanova.ra
b.permanova.ra <- adonis(formula = t(b.otu.ra) ~ (TNF_inhibitor+TX), data = b.meta.ra, permutations=9999, method = "bray")
b.permanova.ra
b.meta$Gender
###Only women samples
bac.clean.log.W <- subset_samples(bac.clean.log, Gender == "2")
bac.clean.log.W <- phyloseq::filter_taxa(bac.clean.log.W, function(x) sum(x) != 0, TRUE)
bac.clean.nolog.W <- subset_samples(bac.clean.log, Gender == "2")
bac.clean.nolog.W <- phyloseq::filter_taxa(bac.clean.nolog.W, function(x) sum(x) != 0, TRUE)
bac.clean.ss.rel.W <- subset_samples(bac.clean.ss.rel, Gender == "2")
bac.clean.ss.rel.W <- phyloseq::filter_taxa(bac.clean.ss.rel.W, function(x) sum(x) != 0, TRUE)
b.meta.women$Ds_Duration <- as.numeric(as.character(b.meta.women$Ds_Duration))
b.meta.women$Ds_Duration[is.na(b.meta.women$Ds_Duration)] <- 0
b.otu <- otu_table(bac.clean.log.W)
b.permanova <- adonis(formula = t(b.otu) ~ (Diagnosis+RA_factor+anti_CCP+seropositive_RA+GC+TX+TNF_inhibitor+exercise_light+exercise_oderate+exercise_heavy+active_disease_2+Duration+Age+BMI+autoimmune_disease+diabetes), data = b.meta.women, permutations=9999, method = "bray")
b.permanova
b.permanova <- adonis(formula = t(b.otu) ~ (RA_factor+anti_CCP+BMI+Age+Ds_Duration+active_disease+active_disease_2), data = b.meta.women, permutations=9999, method = "bray")
b.permanova
b.permanova <- adonis(formula = t(b.otu) ~ (TNF_inhibitor+TX), data = b.meta.women, permutations=9999, method = "bray")
b.permanova
### RA and women
bac.clean.log.RA.W <- subset_samples(bac.clean.log.RA, Gender == "2")
bac.clean.log.RA.W <- phyloseq::filter_taxa(bac.clean.log.RA.W, function(x) sum(x) != 0, TRUE)
bac.clean.nolog.RA.W <- subset_samples(bac.clean.nolog.RA, Gender == "2")
bac.clean.nolog.RA.W <- phyloseq::filter_taxa(bac.clean.nolog.RA.W, function(x) sum(x) != 0, TRUE)
bac.clean.ss.RA.rel.W <- subset_samples(bac.clean.ss.RA.rel, Gender == "2")
bac.clean.ss.RA.rel.W <- phyloseq::filter_taxa(bac.clean.ss.RA.rel.W, function(x) sum(x) != 0, TRUE)
b.meta.ra.women$Ds_Duration <- as.numeric(as.character(b.meta.ra.women$Ds_Duration))
b.meta.ra.women$Ds_Duration[is.na(b.meta.ra.women$Ds_Duration)] <- 0
b.otu.ra <- otu_table(bac.clean.log.RA.W)
b.permanova <- adonis(formula = t(b.otu.ra) ~ (RA_factor+Ds_Duration+anti_CCP+seropositive_RA+GC+TX+TNF_inhibitor+exercise_light+exercise_oderate+exercise_heavy+active_disease_2+Duration+Age+BMI+autoimmune_disease+diabetes), data = b.meta.ra.women, permutations=9999, method = "bray")
b.permanova
b.permanova <- adonis(formula = t(b.otu.ra) ~ (RA_factor+anti_CCP+BMI+Age+Ds_Duration+active_disease+active_disease_2), data = b.meta.ra.women, permutations=9999, method = "bray")
b.permanova
b.permanova <- adonis(formula = t(b.otu.ra) ~ (TNF_inhibitor+TX), data = b.meta.ra.women, permutations=9999, method = "bray")
b.permanova
dev.off()
############### Fungal community #################
f.meta <- sample_data(fun.clean.log)
f.meta <- data.frame(f.meta)
f.meta$exercise_light <- as.character(f.meta$exercise_light)
f.meta$exercise_oderate <- as.character(f.meta$exercise_oderate)
f.meta$exercise_heavy <- as.character(f.meta$exercise_heavy)
f.meta$active_disease <- as.character(f.meta$active_disease)
f.meta$Duration <- as.character(f.meta$Duration)
f.meta$TNF_inhibitor <- as.character(f.meta$TNF_inhibitor)
f.meta$GC <- as.character(f.meta$GC)
f.meta$MTX <- as.character(f.meta$MTX)
f.meta$seropositive_RA <- as.character(f.meta$seropositive_RA)
f.meta$periodental_score <- as.character(f.meta$periodental_score)
f.meta$periodental <- as.character(f.meta$periodental)
### factor to numeric
f.meta$Age <- as.numeric(as.character(f.meta$Age))
f.meta$BMI <- as.numeric(as.character(f.meta$BMI))
f.meta$RA_factor <- as.numeric(as.character(f.meta$RA_factor))
f.meta$anti_CCP <- as.numeric(as.character(f.meta$anti_CCP))
f.meta$MTX_dose <- as.numeric(as.character(f.meta$MTX_dose))
f.meta$CRP <- as.numeric(as.character(f.meta$CRP))
f.meta$ESR <- as.numeric(as.character(f.meta$ESR))
f.meta$BUN <- as.numeric(as.character(f.meta$BUN))
f.meta$Cr <- as.numeric(as.character(f.meta$Cr))
f.meta$Total_cholesterol <- as.numeric(as.character(f.meta$Total_cholesterol))
f.meta$Triglyceride <- as.numeric(as.character(f.meta$Triglyceride))
f.meta$HDL <- as.numeric(as.character(f.meta$HDL))
##Ordering
f.meta$Diagnosis <- factor(f.meta$Diagnosis, levels = order.diagnosis)
f.meta$active_disease <- factor(f.meta$active_disease, levels = order.active_disease)
sample_data(fun.clean.log) <- sample_data(f.meta)
sample_data(fun.clean.ss) <- sample_data(f.meta)
sample_data(fun.clean.nolog) <-sample_data(f.meta)
fun.clean.log
fun.clean.nolog
fun.clean.ss.rel
bray1.fun <- ordinate(fun.clean.log.2, 'PCoA', 'bray')
write.csv(bray1.fun$vectors, "Supplementary Fig. A_PCoA_fun.csv")
#cap_uni <- ordinate(fun.clean.log, 'CAP', 'unifrac', weight = TRUE, ~ Diagnosis)
#bray3.fun <- ordinate(fun.clean.log, 'PCoA', 'unifrac')
##Unconstrained PCoA
#Control vs RA
plot_ordination(fun.clean.log, bray1.fun, type = "samples", color='Diagnosis', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+ scale_color_manual(values=c("control" = "#6699CC", "RA" = "#CC9900"))+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
#Age
plot_ordination(fun.clean.log.2.its1, bray1.fun, type = "samples", color='Age', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+
scale_colour_gradient(low = "darkgreen",
high = "gold3",
space = "Lab",
na.value = "grey50",
guide = "colourbar",
aesthetics = "colour")+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
## MTX
plot_ordination(fun.clean.log.2.its1, bray1.fun, type = "samples", color='MTX', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+ #scale_color_manual(values=c("control" = "#6699CC", "RA" = "#CC9900"))+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
## TNF inhibitor
plot_ordination(fun.clean.log, bray1.fun, type = "samples", color='TNF_inhibitor', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+ #scale_color_manual(values=c("control" = "#6699CC", "RA" = "#CC9900"))+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
##Active disease
plot_ordination(fun.clean.log, bray1.fun, type = "samples", color='active_disease', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+ #scale_color_manual(values=c("control" = "#6699CC", "RA" = "#CC9900"))+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
### CAP (Canonical analysis of principals)
##Relative abundance
fun.clean.ss.rel <- microbiome::transform(fun.clean.ss, "compositional")
f.cap.diagnosis <- ordinate(fun.clean.ss.rel, "CAP", "bray", ~ Diagnosis)
perm_anova.ord <- anova.cca(f.cap.diagnosis)
perm_anova.ord2 <- permutest(f.cap.diagnosis)
## Plotting
# Diagnosis
plot.f.cap.type <- plot_ordination(fun.clean.ss.rel, f.cap.diagnosis, type = "samples", color='Diagnosis', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+ scale_color_manual(values=c("control" = "#6699CC", "RA" = "#CC9900"))+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
plot.f.cap.type
##Duration
f.cap.duration <- ordinate(fun.clean.ss.rel, "CAP", "bray", ~ Duration)
perm_anova.ord <- anova.cca(f.cap.duration)
perm_anova.ord2 <- permutest(f.cap.duration)
## Plotting
plot.f.cap.duration <- plot_ordination(fun.clean.ss.rel, f.cap.duration, type = "samples", color='Duration', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+ #scale_color_manual(values=c("control" = "#6699CC", "RA" = "#CC9900"))+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
plot.f.cap.duration
##Active disease
f.cap.active <- ordinate(fun.clean.ss.rel, "CAP", "bray", ~ active_disease)
perm_anova.ord <- anova.cca(f.cap.active)
perm_anova.ord2 <- permutest(f.cap.active)
## Plotting
plot.f.cap.active <- plot_ordination(fun.clean.ss.rel, f.cap.active, type = "samples", color='active_disease', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+ #scale_color_manual(values=c("control" = "#6699CC", "RA" = "#CC9900"))+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
plot.f.cap.active
##Age
f.cap.age <- ordinate(fun.clean.ss.rel, "CAP", "bray", ~ Age)
perm_anova.ord <- anova.cca(f.cap.age)
perm_anova.ord2 <- permutest(f.cap.age)
## Plotting
plot.f.cap.age <- plot_ordination(fun.clean.ss.rel, f.cap.age, type = "samples", color='Age', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+
scale_colour_gradient(low = "darkgreen",
high = "gold3",
space = "Lab",
na.value = "grey50",
guide = "colourbar",
aesthetics = "colour")+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
plot.f.cap.age
##Normalized abundance
f.cap.diagnosis <- ordinate(fun.clean.nolog, "CAP", "bray", ~ Diagnosis)
perm_anova.ord <- anova.cca(f.cap.diagnosis)
perm_anova.ord2 <- permutest(f.cap.diagnosis)
## Plotting
# Diagnosis
plot.f.cap.type <- plot_ordination(fun.clean.nolog, f.cap.diagnosis, type = "samples", color='Diagnosis', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+ scale_color_manual(values=c("control" = "#6699CC", "RA" = "#CC9900"))+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
plot.f.cap.type
##Duration
f.cap.duration <- ordinate(fun.clean.nolog, "CAP", "bray", ~ Duration)
perm_anova.ord <- anova.cca(f.cap.duration)
perm_anova.ord2 <- permutest(f.cap.duration)
## Plotting
plot.f.cap.duration <- plot_ordination(fun.clean.nolog, f.cap.duration, type = "samples", color='Duration', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+ #scale_color_manual(values=c("control" = "#6699CC", "RA" = "#CC9900"))+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
plot.f.cap.duration
##Active disease
f.cap.active <- ordinate(fun.clean.nolog, "CAP", "bray", ~ active_disease)
perm_anova.ord <- anova.cca(f.cap.active)
perm_anova.ord2 <- permutest(f.cap.active)
## Plotting
plot.f.cap.active <- plot_ordination(fun.clean.nolog, f.cap.active, type = "samples", color='active_disease', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+ #scale_color_manual(values=c("control" = "#6699CC", "RA" = "#CC9900"))+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
plot.f.cap.active
##Age
f.cap.age <- ordinate(fun.clean.nolog, "CAP", "bray", ~ Age)
perm_anova.ord <- anova.cca(f.cap.age)
perm_anova.ord2 <- permutest(f.cap.age)
## Plotting
plot.f.cap.age <- plot_ordination(fun.clean.nolog, f.cap.age, type = "samples", color='Age', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+
scale_colour_gradient(low = "darkgreen",
high = "gold3",
space = "Lab",
na.value = "grey50",
guide = "colourbar",
aesthetics = "colour")+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
plot.f.cap.age
##Normalized abundance and log transformed
f.cap.diagnosis <- ordinate(fun.clean.log.2.its1, "CAP", "bray", ~ Diagnosis)
perm_anova.ord <- anova.cca(f.cap.diagnosis)
perm_anova.ord2 <- permutest(f.cap.diagnosis)
## Plotting
# Diagnosis
plot.f.cap.type <- plot_ordination(fun.clean.log.2.its1, f.cap.diagnosis, type = "samples", color='Diagnosis', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+ scale_color_manual(values=c("control" = "#6699CC", "RA" = "#CC9900"))+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
plot.f.cap.type
plot.f.cap.type <- plot_ordination(fun.clean.log.2.its1, f.cap.diagnosis, type = "samples", color='Candida', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+scale_colour_gradient(low = "#CCCCFF",
high = "#333366",
space = "Lab",
na.value = "grey50",
guide = "colourbar",
aesthetics = "colour")+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
plot.f.cap.type
plot.f.cap.type <- plot_ordination(fun.clean.log.2.its1, f.cap.diagnosis, type = "samples", color='Aspergillus', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+scale_colour_gradient(low = "#CCFFFF",
high = "#003333",
space = "Lab",
na.value = "grey50",
guide = "colourbar",
aesthetics = "colour")+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
plot.f.cap.type
##Duration
f.cap.duration <- ordinate(fun.clean.log, "CAP", "bray", ~ Duration)
perm_anova.ord <- anova.cca(f.cap.duration)
perm_anova.ord2 <- permutest(f.cap.duration)
## Plotting
plot.f.cap.duration <- plot_ordination(fun.clean.log, f.cap.duration, type = "samples", color='Duration', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+ #scale_color_manual(values=c("control" = "#6699CC", "RA" = "#CC9900"))+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
plot.f.cap.duration
##Active disease
f.cap.active <- ordinate(fun.clean.log, "CAP", "bray", ~ active_disease)
perm_anova.ord <- anova.cca(f.cap.active)
perm_anova.ord2 <- permutest(f.cap.active)
## Plotting
plot.f.cap.active <- plot_ordination(fun.clean.log, f.cap.active, type = "samples", color='active_disease', axes = c(1,2))+
theme(plot.title = element_text(size = 20,hjust = 0.5, face="bold")) +
geom_point(size = 3)+ #scale_color_manual(values=c("control" = "#6699CC", "RA" = "#CC9900"))+
theme(aspect.ratio=1)+theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) +
theme(axis.title.x = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.title.y = element_text(size = 15,hjust = 0.5, face='bold')) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, vjust=0.4,size=15, face='bold',color='black'))+
theme(axis.text.y = element_text(size=15, face='bold',color='black'))+
geom_hline(yintercept=0, linetype='dashed', color='black', size = 0.75)+geom_vline(xintercept=0, linetype='dashed', color='black', size = 0.75)+
theme(panel.grid.major = element_blank()) +
theme(panel.grid.minor = element_blank(), panel.background=element_blank(), plot.background=element_blank())
plot.f.cap.active
##Age
f.cap.age <- ordinate(fun.clean.log, "CAP", "bray", ~ Age)