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Conclusions_RWU_TNC_PJ_16S_analysis_FiguresV6toV8.R
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Conclusions_RWU_TNC_PJ_16S_analysis_FiguresV6toV8.R
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# 16S data from RWU, TNC and PJ projects combined
# Analyzed with QIIME
# RJS 3/24/2019
# Figures V-6 to V-8
library(tidyr)
library(dplyr)
library(ggplot2)
library(RColorBrewer)
library(phyloseq)
library(plyr)
library(vegan)
library(openxlsx)
library(ggpubr)
library(ggbiplot)
## phylum ----------------
data<-read.xlsx("RWU_TNC_PJ_16S_Phyladata.xlsx")
datag<-gather(data, taxa, value, "Acidobacteria":"Unknown")
# use only gut and control data at first.
#datag<-filter(datag, SampleType=="gut" & Treatment=="Control")
#phylum top 30
datatop30<-read.xlsx("RWU_TNC_PJ_16S_Phyladata.xlsx", sheet="norm-strip")
datagtopg<-gather(datatop30, taxa, value, "Acidobacteria":"Unknown")
#datatopg<-filter(datagtopg, SampleType=="gut" & Treatment=="Control")
datagtopg$taxa = factor(datagtopg$taxa, levels = unique(datagtopg$taxa))
# define palette
palette<-c("#8fe1c7",
"#4e736a",
"#803435",
"#48211f",
"#cdd99e",
"#2b3826",
"#d8ad93",
"#4c652d",
"#c27a7b",
"#61a178",
"#7f572f",
"#72becb",
"#a79459")
datagtopgavg<-datagtopg %>%group_by(taxa,Treatment,BucketDay, OysterStage,SpecSampleType,StationTrial,Treatment) %>%
dplyr::summarise(meanvalue=mean(value)) %>%
ungroup()
# Percent abundances of top taxa, averaged per rep.
# Figure V-7.
ggplot(arrange(datagtopgavg,taxa),aes(Treatment,meanvalue,fill=taxa))+
geom_col(position="fill")+
theme(legend.text = element_text(size=12, colour="gray20"),
legend.position = "bottom", axis.text.x = element_blank(),
# axis.text.y=element_text(angle=90, hjust=0.5),
axis.ticks.x = element_blank(),
axis.ticks.length = unit(0.6, 'lines'),
panel.spacing = unit(0.01, "lines"))+
facet_grid(.~OysterStage+SpecSampleType+StationTrial+BucketDay, scales="free", space="free")+
scale_fill_manual(values=c(paletteall))+labs(y="Percent \nabundance",x=NULL,fill=NULL)+
scale_y_continuous(labels = scales::percent, expand = c(0,0))
ggplot(arrange(datagtopg,taxa),aes(SampleName,value,fill=taxa))+
geom_col(position="fill")+
theme(legend.text = element_text(size=12, colour="gray20"),
legend.position = "bottom", axis.text.x = element_blank(),
# axis.text.y=element_text(angle=90, hjust=0.5),
axis.ticks.x = element_blank(),
axis.ticks.length = unit(0.6, 'lines'),
panel.spacing = unit(0.01, "lines"))+
facet_grid(.~OysterStage+SpecSampleType+StationTrial+Treatment, scales="free", space="free")+
scale_fill_manual(values=c(paletteall))+labs(y="Percent \nabundance",x=NULL,fill=NULL)+
scale_y_continuous(labels = scales::percent, expand = c(0,0))
# heatmap of top 20 phyla
datatopg_norm<-ddply(datagtopg,.(SampleName),transform,rescale=sqrt(value))
datagtopgavg_norm<-ddply(datagtopgavg,.(Group),transform,rescale=sqrt(meanvalue))
# Figure V-6.
ggplot(datatopg_norm,aes(taxa,SampleName,fill=rescale))+
geom_tile()+coord_flip()+theme_minimal()+
theme(legend.text = element_text(size=10, colour="gray20"),
axis.text.x = element_blank(),
axis.ticks.x = element_blank(),legend.position = "bottom",
axis.ticks.length = unit(0.2, 'lines'),
panel.spacing = unit(0.01, "lines"))+
facet_grid(.~OysterStage+SpecSampleType+StationTrial+Treatment, scales="free", space="free")+
labs(fill="Percent abundance",x=NULL,y=NULL)+
viridis::scale_fill_viridis(option="B", labels = scales::percent,limits=c(0,1))
ggplot(datagtopgavg_norm,aes(taxa,Group,fill=rescale))+
geom_tile()+coord_flip()+theme_minimal()+
theme(legend.text = element_text(size=12, colour="gray20"),
axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
axis.ticks.length = unit(0.2, 'lines'))+
facet_grid(.~OysterStage+SpecSampleType+StationTrial, scales="free", space="free")+
labs(fill="Percent abundance",x=NULL,y=NULL)+
scale_y_discrete(expand=c(0,0)) + scale_x_discrete(expand=c(0,0))+
scale_fill_gradientn(labels = scales::percent,limits=c(0,1),colours=c("white","#fecc5c","#fd8d3c","#f03b20","#bd0026","darkred"))
# diversity --------------
datagtopg$Simpsons<-diversity(data[,2:30], index="simpson")
ggplot(datagtopg,aes(x=SpecSampleType,y=Simpsons, fill=StationTrial))+
geom_boxplot(aes(fill=factor(StationTrial)))+
facet_grid(~OysterStage, scales="free",space="free") +
labs(x=NULL,y="Simpson's Index of Diversity",fill="Station")+
# scale_fill_manual(values=c("#0c2c84","#225ea8","#1d91c0","#41b6c4","#7fcdbb","#c7e9b4","#ffffcc"),
# labels=c("1.PVD - Bold Point Park", "2.GB - Goddard State Park",
# "3.BIS - Bissel Cove", "4.NAR - Narrow River", "5.PJN - Billington Cove",
# "6.PJS - Bluff Hill Cove","7.NIN - Ninigret Pond"))+
stat_compare_means(method = "anova", label.y = 0.2, label.x="3.BIS") + # Add global annova p-value
theme_bw()+scale_y_continuous(limits=c(0,1))
ggplot(datagtopg,aes(x=StationTrial,y=Simpsons, fill=factor(Treatment))) +
facet_grid(~OysterStage+SpecSampleType, scales="free",space="free") +
geom_point(position=position_dodge(width=0.8), color="grey60")+
geom_boxplot(alpha=0.5)+
labs(x=NULL,y="Simpson's Index of Diversity",fill="Station")+
# scale_fill_manual(values=c("#0c2c84","#225ea8","#1d91c0","#41b6c4","#7fcdbb","#c7e9b4","#ffffcc"),
# labels=c("1.PVD - Bold Point Park", "2.GB - Goddard State Park",
# "3.BIS - Bissel Cove", "4.NAR - Narrow River", "5.PJN - Billington Cove",
# "6.PJS - Bluff Hill Cove","7.NIN - Ninigret Pond"))+
theme_bw()+scale_y_continuous(limits=c(0,1))
# With Phyla-level bacterial data -----------------
pcadataraw <- read.xlsx("RWU_TNC_PJ_16S_Phyladata.xlsx", sheet="norm-strip")
theme_set(theme_grey())
pcadata<-pcadataraw[,1:29]
pca_result <- prcomp(pcadata, scale=TRUE)
pca_result$rotation <- -pca_result$rotation
pca_result$x <- - pca_result$x
aplot<-autoplot(pca_result,size=6, data=pcadataraw,color="StationTrial",
fill="StationTrial",shape="SpecSampleType",
frame=FALSE,frame.colour = "StationTrial",level = 0.95,
loadings=TRUE,loadings.label=TRUE,frame.alpha=0.3,
loadings.label.repel=TRUE,loadings.label.size=4,
loadings.label.colour="black",loadings.colour="black")
aplot + scale_fill_manual(values=c("#0c2c84","#225ea8","#1d91c0","#41b6c4","#7fcdbb","#c7e9b4","#ffffcc","black","grey30","grey80"),
labels=c("1.PVD - Bold Point Park", "2.GB - Goddard State Park",
"3.BIS - Bissel Cove", "4.NAR - Narrow River", "5.PJN - Billington Cove",
"6.PJS - Bluff Hill Cove","7.NIN - Ninigret Pond",
"1.RWU - Hatchery Trial 1","2.RWU - Hatchery Trial 2",
"3.RWU - Hatchery Trial 3"))+
scale_color_manual(values=c("#0c2c84","#225ea8","#1d91c0","#41b6c4","#7fcdbb","#c7e9b4","#ffffcc","black","grey40","grey10"),
labels=c("1.PVD - Bold Point Park", "2.GB - Goddard State Park",
"3.BIS - Bissel Cove", "4.NAR - Narrow River", "5.PJN - Billington Cove",
"6.PJS - Bluff Hill Cove","7.NIN - Ninigret Pond",
"1.RWU - Hatchery Trial 1","2.RWU - Hatchery Trial 2",
"3.RWU - Hatchery Trial 3"))+
scale_shape_manual(values = c(24,22,23,25,21,21,9),
limits=c("gut","inner swab","outer swab","LarvalOyster","water",
"RearingWater","TankSwab"),
labels=c("Adult oyster gut","Adult inner shell",
"Adult outer shell","Larval oyster","Seawater",
"Hatchery Rearing Water",
"Hatchery Tank Biofilm Swab"))+
theme(legend.position="right", legend.text = element_text(size=12, color="grey20"))
# With Averaged Phyla-level bacterial data -----------------
pcadataraw <- read.xlsx("RWU_TNC_PJ_16S_Phyladata.xlsx", sheet="norm-strip")
theme_set(theme_grey())
pcadatarawg<-gather(pcadataraw, taxa, value, "Acidobacteria":"Unknown")
pcadatarawavg<-pcadatarawg %>% group_by(taxa,Treatment,SampleType,BucketDay, OysterStage,SpecSampleType,StationTrial,Treatment) %>%
dplyr::summarise(meanvalue=mean(value)) %>%
ungroup()
pcadatarawavgtab<-spread(pcadatarawavg, taxa,meanvalue)
pcadata<-pcadatarawavgtab[,7:35]
pca_result <- prcomp(pcadata, scale=TRUE)
pca_result$rotation <- -pca_result$rotation
pca_result$x <- - pca_result$x
# Figure V-8A
aplot<-autoplot(pca_result,x = 1,y = 2, size=6, data=pcadatarawavgtab,colour="Treatment",
fill="StationTrial",shape="SpecSampleType",
frame=FALSE,frame.colour = "SpecSampleType",level = 0.95,
loadings=TRUE,loadings.label=TRUE,frame.alpha=0.3,
loadings.label.repel=TRUE,loadings.label.size=3.7,
loadings.label.colour="black",loadings.colour="black")
aplot$layers[[1]]$aes_params$stroke <- 1.2
aplot + scale_fill_manual(values=c("#0c2c84","#225ea8","#1d91c0","#41b6c4","#7fcdbb","#c7e9b4","#ffffcc",
"#2b0045","#7e358a","#da70d6"),
labels=c("1.PVD - Bold Point Park", "2.GB - Goddard State Park",
"3.BIS - Bissel Cove", "4.NAR - Narrow River", "5.PJN - Billington Cove",
"6.PJS - Bluff Hill Cove","7.NIN - Ninigret Pond",
"0.RWU.1 - Hatchery Trial 1","0.RWU.2 - Hatchery Trial 2",
"0.RWU.3 - Hatchery Trial 3"))+
scale_color_manual(values=c("grey60","black","black"),
labels=c("Control","Nutrient Enrichment","Probiotic Treatment"))+
scale_shape_manual(values = c(24,22,23,25,21,21,23),
limits=c("gut","inner swab","outer swab","LarvalOyster","water",
"RearingWater","TankSwab"),
labels=c("Adult oyster gut","Adult inner shell",
"Adult outer shell","Larval oyster","Seawater",
"Hatchery Rearing Water",
"Hatchery Tank Biofilm Swab"))+
theme(legend.position="bottom", legend.direction = "vertical", legend.text = element_text(size=12, color="grey20"))
# Figure V-8B.
bplot<-autoplot(pca_result,x = 3,y = 4, size=6, data=pcadatarawavgtab,colour="Treatment",
fill="StationTrial",shape="SpecSampleType",
frame=FALSE,frame.colour = "SpecSampleType",level = 0.95,
loadings=TRUE,loadings.label=TRUE,frame.alpha=0.3,
loadings.label.repel=TRUE,loadings.label.size=3.7,
loadings.label.colour="black",loadings.colour="black")
bplot$layers[[1]]$aes_params$stroke <- 1.2
bplot + scale_fill_manual(values=c("#0c2c84","#225ea8","#1d91c0","#41b6c4","#7fcdbb","#c7e9b4","#ffffcc",
"#2b0045","#7e358a","#da70d6"),
labels=c("1.PVD - Bold Point Park", "2.GB - Goddard State Park",
"3.BIS - Bissel Cove", "4.NAR - Narrow River", "5.PJN - Billington Cove",
"6.PJS - Bluff Hill Cove","7.NIN - Ninigret Pond",
"0.RWU.1 - Hatchery Trial 1","0.RWU.2 - Hatchery Trial 2",
"0.RWU.3 - Hatchery Trial 3"))+
scale_color_manual(values=c("grey60","black","black"),
labels=c("Control","Nutrient Enrichment","Probiotic Treatment"))+
scale_shape_manual(values = c(24,22,23,25,21,21,23),
limits=c("gut","inner swab","outer swab","LarvalOyster","water",
"RearingWater","TankSwab"),
labels=c("Adult oyster gut","Adult inner shell",
"Adult outer shell","Larval oyster","Seawater",
"Hatchery Rearing Water",
"Hatchery Tank Biofilm Swab"))+
theme(legend.position="bottom", legend.direction = "vertical", legend.text = element_text(size=12, color="grey20"))
#1200x1000
cowplot::plot_grid(aplot,bplot)
# Subset of the samples
pcadatarawavg<-pcadatarawg %>% group_by(taxa,Treatment,BucketDay, OysterStage,SpecSampleType,StationTrial,Treatment) %>%
dplyr::summarise(meanvalue=mean(value)) %>%
ungroup() %>%
filter(SpecSampleType!="outer swab" & SpecSampleType!="inner swab")
pcadatarawavgtab<-spread(pcadatarawavg, taxa,meanvalue)
#pcadata<-pcadatarawavgtab[,c(6,7,9:14,16:33)]
pcadata<-pcadatarawavgtab[,6:34]
pca_result <- prcomp(pcadata, scale=TRUE)
pca_result$rotation <- -pca_result$rotation
pca_result$x <- - pca_result$x
aplot<-autoplot(pca_result,size=6, data=pcadatarawavgtab,colour="Treatment",
fill="StationTrial",shape="SpecSampleType",
frame=FALSE,frame.colour = "StationTrial",level = 0.95,
loadings=TRUE,loadings.label=TRUE,frame.alpha=0.3,
loadings.label.repel=TRUE,loadings.label.size=4,
loadings.label.colour="black",loadings.colour="black")
aplot + scale_fill_manual(values=c("#0c2c84","#225ea8","#1d91c0","#41b6c4","#7fcdbb","#c7e9b4","#ffffcc","black","mediumorchid4","plum"),
labels=c("1.PVD - Bold Point Park", "2.GB - Goddard State Park",
"3.BIS - Bissel Cove", "4.NAR - Narrow River", "5.PJN - Billington Cove",
"6.PJS - Bluff Hill Cove","7.NIN - Ninigret Pond",
"1.RWU - Hatchery Trial 1","2.RWU - Hatchery Trial 2",
"3.RWU - Hatchery Trial 3"))+
scale_color_manual(values=c("grey60","black","black"),
labels=c("Control","Nutrient Enrichment","Probiotic Treatment"))+
scale_shape_manual(values = c(21,24,22,23,25),
limits=c("water","gut","LarvalOyster",
"RearingWater","TankSwab"),
labels=c("Adult gut","Seawater","Larval oyster",
"Hatchery Rearing Water",
"Hatchery Tank Biofilm Swab"))+
theme(legend.position="right", legend.text = element_text(size=12, color="grey20"))