R/boxplots_by_perm.R
In adsteen/Lloyd.et.al.Cell.abundance.metaanalysis: Package to reproduce analysis from Lloyd et al (2013), Applied and Environmental Microbiology
##' Creates boxplots of yield and %Archaea by permeabilization method
##' Also runs statistics on those plots
##'
##'@description Creates plots in Fig 3, and calculates relevant statistics
##'@param corrected_seds Data frame of sediments data
##'@param sw_quant Vector of 25% percentile, median, and 75% percentile of all sw yields
##'@param yaxsize Font size of y axis text
##'@param colors Vector of colors for box fills, should be length 5
##'@param print_plot If true, print the plot
##'@param save_plot If true, save the plot
##'@param height Height of the plot, in inches, if plot is saved
##'@param width Width of the plot, in inches, if plot is saved
##'@param res Resolution of the plot, if saved, in dpi
##'@export
boxplots_by_perm <- function(corrected_seds,
sw_quant,
yaxsize=7,
colors=brewer.pal(n=5, name="RdBu"),
print_plot=FALSE, save_plot=FALSE,
height=4, width=clm, res=900) {
# Colors to indicate permeabilization method
box_col <- colors[c(1, 4, 3, 5)]
# Y-axis labels
percent_arc_label <- expression(frac("Archaea (CARD-FISH)", "Bacteria + Archaea (CARD-FISH)"))
yield_label <- expression(frac("Bacteria + Archaea (CARD-FISH)", "Total Cell Count"))
# Want to replace with boxplot of all cardfish % Archaea + Fish, colored by permeabilization method, for sediments only
p_percent_arc_data <- corrected_seds[!is.na(corrected_seds$Arc.permeabilization) &
!is.na(corrected_seds$Fish.or.cardFish) &
!is.na(corrected_seds$Fraction.Arc.CARDFISH) &
!corrected_seds$Arc.permeabilization == "unknown" &
!corrected_seds$Arc.permeabilization == "not measured" &
!corrected_seds$Fish.or.cardFish == "FISH" &
corrected_seds$Environment.Type != "Intertidal" &
corrected_seds$Environment.Type != "Salt marsh",
c("depth", "Arc.permeabilization", "Fraction.Arc.CARDFISH", "paper")]
# Re-order the factor for permeabilization method
p_percent_arc_data$perm <- as.character(p_percent_arc_data$Arc.permeabilization)
p_percent_arc_data$perm <- factor(p_percent_arc_data$perm,
levels=c("proteinase K", "detergent",
"lysozyme/achromopeptidase", "lysozyme"),
labels=c("proteinase K", "detergent",
"lysozyme/\nachromopeptidase", "lysozyme"),
ordered=TRUE)
p_percent_arc_medians <- ddply(p_percent_arc_data, .(perm), summarise, med=median(Fraction.Arc.CARDFISH))
p_percent_arc_data$perm <- factor(p_percent_arc_data$perm, levels=p_percent_arc_medians$perm[order(p_percent_arc_medians$med, decreasing=TRUE)])
pointsAndStudies <- ddply(p_percent_arc_data, .(perm),
function(x) data.frame(nPoints=nrow(x),
nStudies=length(unique(x$paper))))
pointsAndStudies$label <- paste(pointsAndStudies$nPoints, " Points\n", pointsAndStudies$nStudies, " Studies", sep="")
# Add the letters to a data frame in order to display them
pointsAndStudies$letter <- NA
pointsAndStudies[pointsAndStudies$perm=="proteinase K", "letter"] <- "a"
pointsAndStudies[pointsAndStudies$perm=="lysozyme/\nachromopeptidase", "letter"] <- "b"
pointsAndStudies[pointsAndStudies$perm=="detergent", "letter"] <- "b"
pointsAndStudies[pointsAndStudies$perm=="lysozyme", "letter"] <- "c"
# Plot of % Archaea by permeabilization method, all depths
p_percent_arc_all_depths <- ggplot(p_percent_arc_data) +
geom_boxplot(data=p_percent_arc_data, aes(x=perm, y=Fraction.Arc.CARDFISH, fill=perm), outlier.size=1) +
geom_text(data=pointsAndStudies, aes(x=perm, y=1.2, label=label), vjust=1, size=2) +
geom_text(data=pointsAndStudies, aes(x=perm, y=-0.03, label=letter), vjust=1, size=2.5) +
scale_y_continuous(percent_arc_label, limits=c(-0.1, 1.25), breaks=seq(from=0, to=1, by=0.25)) +
scale_x_discrete("All Data") +
scale_fill_manual(values=box_col, name="permeabilization\nmethod") +
theme(legend.position="none",
text=element_text(size=8),
axis.text.x=element_text(angle=0, hjust=0.5),
axis.title.y=element_text(size=yaxsize))#,
#plot.margin=unit(fig2bc_spacing, "in"))
# Calculate % Archaea for all data
percent_arc_all_depths <- ddply(p_percent_arc_data, .(perm), summarise,
median=quantile(Fraction.Arc.CARDFISH, probs=0.50, na.rm=TRUE),
twenty.fifth.percentile=quantile(Fraction.Arc.CARDFISH, probs=0.25, na.rm=TRUE),
seventy.fifth.percentile=quantile(Fraction.Arc.CARDFISH, probs=0.75, na.rm=TRUE))
# Create a data frame to hold all data and < 1 m depth
percent_arc_all_depths$quantity <- "fraction archaea"
percent_arc_all_depths$dataset <- "all depths"
#=========
# Fig 2c: boxplots of percent ARC for only seds < 1 m deep
#=========
p_percent_arc_shallow_data <- p_percent_arc_data[p_percent_arc_data$depth <= 1, ]
# Calculate the number of data points and studies
pointsAndStudies1m <- ddply(p_percent_arc_shallow_data, .(perm),
function(x) data.frame(nPoints=nrow(x),
nStudies=length(unique(x$paper))))
pointsAndStudies1m$label <- paste(pointsAndStudies1m$nPoints, " Points\n", pointsAndStudies1m$nStudies, " Studies", sep="")
# Add letter labels for signifciantly different permeabilization methods
pointsAndStudies1m$letter <- NA
pointsAndStudies1m[pointsAndStudies1m$perm=="proteinase K", "letter"] <- "a"
pointsAndStudies1m[pointsAndStudies1m$perm=="lysozyme/\nachromopeptidase", "letter"] <- "b"
pointsAndStudies1m[pointsAndStudies1m$perm=="detergent", "letter"] <- "b"
pointsAndStudies1m[pointsAndStudies1m$perm=="lysozyme", "letter"] <- "b"
p_percent_arc_shallow <- ggplot(p_percent_arc_shallow_data) +
geom_boxplot(data=p_percent_arc_shallow_data, aes(x=perm, y=Fraction.Arc.CARDFISH, fill=perm), outlier.size=1) +
geom_text(data=pointsAndStudies1m, aes(x=perm, y=1.2, label=label), vjust=1, size=2) +
geom_text(data=pointsAndStudies1m, aes(x=perm, y=-0.03, label=letter), vjust=1, size=2.5) +
scale_y_continuous(percent_arc_label,limits=c(-0.1, 1.25), breaks=seq(from=0, to=1, by=0.25)) +
scale_x_discrete("Shallower than 1 m") +
scale_fill_manual(values=box_col) +
theme(legend.position="none",
text=element_text(size=8),
axis.text.x=element_text(angle=0, hjust=0.5),
axis.text.x=element_blank(),
axis.title.y=element_text(size=yaxsize))#,
#plot.margin=unit(fig2bc_spacing, "in"))
# Calculate % Archaea for data < 1m deep
percent_arc_shallow <- ddply(p_percent_arc_shallow_data, .(perm), summarise,
median=quantile(Fraction.Arc.CARDFISH, probs=0.50, na.rm=TRUE),
twenty.fifth.percentile=quantile(Fraction.Arc.CARDFISH, probs=0.25, na.rm=TRUE),
seventy.fifth.percentile=quantile(Fraction.Arc.CARDFISH, probs=0.75, na.rm=TRUE))
percent_arc_shallow$quantity <- "fraction archaea"
percent_arc_shallow$dataset <- "< 1 m"
#====================
# Fig 2d and 2e: same as Fig 2b and c, but with yield
#====================
p_yield_data <- corrected_seds[!is.na(corrected_seds$Arc.permeabilization) &
!is.na(corrected_seds$Fish.or.cardFish) &
!is.na(corrected_seds$FISH.yield) &
!corrected_seds$Arc.permeabilization=="unknown" &
!corrected_seds$Arc.permeabilization=="not measured" &
!corrected_seds$Fish.or.cardFish=="FISH" &
corrected_seds$Environment.Type != "Intertidal" &
corrected_seds$Environment.Type != "Salt marsh", ]
#p_yield_data <- fig2b_data
p_yield_data$perm <- as.character(p_yield_data$Arc.permeabilization)
#fig2b_data$perm[fig2b_data$Fish.or.cardFish=="FISH"] <- "FISH"
p_yield_data$perm <- factor(p_yield_data$perm,
levels=c("proteinase K", "lysozyme/achromopeptidase", "detergent", "lysozyme"),
labels=c("proteinase K", "lysozyme/\nachromopeptidase", "detergent", "lysozyme"),
ordered=TRUE)
p_yield_shallow_data <- p_yield_data[!is.na(p_yield_data$depth) &
p_yield_data$depth <= 1, ]
# proteinase K gets A
# lysozyme-achromopeptidase gets B
# detergent gets B
# lysozyme gets C
pointsAndStudiesYield <- ddply(p_yield_data, .(perm),
function(x) data.frame(nPoints=nrow(x),
nStudies=length(unique(x$paper))))
pointsAndStudiesYield$label <- paste(pointsAndStudies$nPoints, " Points\n", pointsAndStudies$nStudies, " Studies", sep="")
pointsAndStudiesYield$letter <- NA
pointsAndStudiesYield[pointsAndStudiesYield$perm=="proteinase K", "letter"] <- "a"
pointsAndStudiesYield[pointsAndStudiesYield$perm=="lysozyme/\nachromopeptidase", "letter"] <- "b"
pointsAndStudiesYield[pointsAndStudiesYield$perm=="detergent", "letter"] <- "b"
pointsAndStudiesYield[pointsAndStudiesYield$perm=="lysozyme", "letter"] <- "c"
swDF <- data.frame(perm=c(0, 1, 2, 5), #perm = levels(p_yield_data$perm), #
ymin=rep(sw_quant[1], nlevels(p_yield_data$perm)),
ymed=rep(sw_quant[2], nlevels(p_yield_data$perm)),
ymax=rep(sw_quant[3], nlevels(p_yield_data$perm)))
p_yield_all <- ggplot(p_yield_data) +
geom_blank(data=p_yield_data, aes(x=perm, y=FISH.yield, fill=perm)) +
geom_ribbon(data=swDF, aes(x=perm, ymin=ymin, ymax=ymax), fill="skyblue") +
geom_line(data=swDF, aes(x=perm, y=ymed)) +
geom_boxplot(data=p_yield_data, aes(x=perm, y=FISH.yield, fill=perm), outlier.size=1) +
geom_text(data=pointsAndStudiesYield, aes(x=perm, y=1.4, label=label), vjust=1, size=2) +
geom_text(data=pointsAndStudiesYield, aes(x=perm, y=0, label=letter), vjust=1, size=2.5) +
#scale_y_continuous("yield", limits=c(-0.1, 1.25)) +
coord_cartesian(xlim=c(0.25, 4.75), ylim=c(-0.1, 1.5)) +
xlab("All data") +
ylab(yield_label) +
scale_fill_manual(values=box_col, name="permeabilization\nmethod") +
theme(legend.position="none",
text=element_text(size=8),
axis.text.x=element_text(angle=0, hjust=0.5),
axis.text.x=element_blank(),
axis.title.y=element_text(size=yaxsize),
#plot.margin=unit(fig2bc_spacing, "in"),
axis.title.x=element_blank())
# Calculate median and IQR of yield for all data
yield_all_data <- ddply(p_yield_data, .(perm), summarise,
median=quantile(FISH.yield, probs=0.50, na.rm=TRUE),
twenty.fifth.percentile=quantile(FISH.yield, probs=0.25, na.rm=TRUE),
seventy.fifth.percentile=quantile(FISH.yield, probs=0.75, na.rm=TRUE))
yield_all_data$quantity <- "yield"
yield_all_data$dataset <- "all data"
pointsAndStudiesYield1m <- ddply(p_yield_shallow_data, .(perm),
function(x) data.frame(nPoints=nrow(x),
nStudies=length(unique(x$paper))))
pointsAndStudiesYield1m$label <- paste(pointsAndStudies$nPoints, " Points\n", pointsAndStudies$nStudies, " Studies", sep="")
pointsAndStudiesYield1m$letter <- NA
pointsAndStudiesYield1m[pointsAndStudiesYield1m$perm=="proteinase K", "letter"] <- "a"
pointsAndStudiesYield1m[pointsAndStudiesYield1m$perm=="lysozyme/\nachromopeptidase", "letter"] <- "b"
pointsAndStudiesYield1m[pointsAndStudiesYield1m$perm=="detergent", "letter"] <- "b"
pointsAndStudiesYield1m[pointsAndStudiesYield1m$perm=="lysozyme", "letter"] <- "c"
p_yield_shallow <- ggplot(p_yield_shallow_data) +
geom_blank(data=p_yield_shallow_data, aes(x=perm, y=FISH.yield, fill=perm)) +
geom_ribbon(data=swDF, aes(x=perm, ymin=ymin, ymax=ymax), fill="skyblue") +
geom_line(data=swDF, aes(x=perm, y=ymed)) +
geom_boxplot(data=p_yield_shallow_data, aes(x=perm, y=FISH.yield, fill=perm), outlier.size=1) +
geom_text(data=pointsAndStudies1m, aes(x=perm, y=1.4, label=label), vjust=1, size=2) +
geom_text(data=pointsAndStudies1m, aes(x=perm, y=0, label=letter), vjust=1, size=2.5) +
#scale_y_continuous("yield", limits=c(-0.1, 1.25)) +
coord_cartesian(xlim=c(0.25, 4.75), ylim=c(-0.1, 1.5)) +
#xlab("Shallower than 1 m") +
ylab(yield_label) +
scale_fill_manual(values=box_col, name="permeabilization\nmethod") +
theme(legend.position="none",
text=element_text(size=8),
axis.text.x=element_text(angle=0, hjust=0.5),
axis.text.x=element_blank(),
axis.title.y=element_text(size=yaxsize),
#plot.margin=unit(fig2bc_spacing, "in"),
#plot.margin=unit(c(0, 0, 0, 0), "in"),
axis.title.x=element_blank())
# Calculate median and IQR opf yield for <1 m data
yield_shallow <- ddply(p_yield_shallow_data, .(perm), summarise,
median=quantile(FISH.yield, probs=0.50, na.rm=TRUE),
twenty.fifth.percentile=quantile(FISH.yield, probs=0.25, na.rm=TRUE),
seventy.fifth.percentile=quantile(FISH.yield, probs=0.75, na.rm=TRUE))
yield_shallow$quantity <- "yield"
yield_shallow$dataset <- "< 1 m"
# Bind the summary data frames into a single frame
permeabilization_methods_summary <- rbind(percent_arc_all_depths,
percent_arc_shallow)#,
permeabilization_methods_summary <- rbind(permeabilization_methods_summary,
yield_all_data)
permeabilization_methods_summary <- rbind(permeabilization_methods_summary,
yield_shallow)
permeabilization_methods_summary$perm <- as.character(permeabilization_methods_summary$perm)
permeabilization_methods_summary$perm[permeabilization_methods_summary$perm=="lysozyme/\nachromopeptidase"] <- "lys/achrom"
# Return values
list(p_percent_arc_all_depths=p_percent_arc_all_depths,
p_percent_arc_shallow=p_percent_arc_shallow,
p_yield_all=p_yield_all,
p_yield_shallow=p_yield_shallow,
permeabilization_methods_summary=permeabilization_methods_summary)
}
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##' Creates boxplots of yield and %Archaea by permeabilization method
##' Also runs statistics on those plots
##'
##'@description Creates plots in Fig 3, and calculates relevant statistics
##'@param corrected_seds Data frame of sediments data
##'@param sw_quant Vector of 25% percentile, median, and 75% percentile of all sw yields
##'@param yaxsize Font size of y axis text
##'@param colors Vector of colors for box fills, should be length 5
##'@param print_plot If true, print the plot
##'@param save_plot If true, save the plot
##'@param height Height of the plot, in inches, if plot is saved
##'@param width Width of the plot, in inches, if plot is saved
##'@param res Resolution of the plot, if saved, in dpi
##'@export
boxplots_by_perm <- function(corrected_seds,
sw_quant,
yaxsize=7,
colors=brewer.pal(n=5, name="RdBu"),
print_plot=FALSE, save_plot=FALSE,
height=4, width=clm, res=900) {
# Colors to indicate permeabilization method
box_col <- colors[c(1, 4, 3, 5)]
# Y-axis labels
percent_arc_label <- expression(frac("Archaea (CARD-FISH)", "Bacteria + Archaea (CARD-FISH)"))
yield_label <- expression(frac("Bacteria + Archaea (CARD-FISH)", "Total Cell Count"))
# Want to replace with boxplot of all cardfish % Archaea + Fish, colored by permeabilization method, for sediments only
p_percent_arc_data <- corrected_seds[!is.na(corrected_seds$Arc.permeabilization) &
!is.na(corrected_seds$Fish.or.cardFish) &
!is.na(corrected_seds$Fraction.Arc.CARDFISH) &
!corrected_seds$Arc.permeabilization == "unknown" &
!corrected_seds$Arc.permeabilization == "not measured" &
!corrected_seds$Fish.or.cardFish == "FISH" &
corrected_seds$Environment.Type != "Intertidal" &
corrected_seds$Environment.Type != "Salt marsh",
c("depth", "Arc.permeabilization", "Fraction.Arc.CARDFISH", "paper")]
# Re-order the factor for permeabilization method
p_percent_arc_data$perm <- as.character(p_percent_arc_data$Arc.permeabilization)
p_percent_arc_data$perm <- factor(p_percent_arc_data$perm,
levels=c("proteinase K", "detergent",
"lysozyme/achromopeptidase", "lysozyme"),
labels=c("proteinase K", "detergent",
"lysozyme/\nachromopeptidase", "lysozyme"),
ordered=TRUE)
p_percent_arc_medians <- ddply(p_percent_arc_data, .(perm), summarise, med=median(Fraction.Arc.CARDFISH))
p_percent_arc_data$perm <- factor(p_percent_arc_data$perm, levels=p_percent_arc_medians$perm[order(p_percent_arc_medians$med, decreasing=TRUE)])
pointsAndStudies <- ddply(p_percent_arc_data, .(perm),
function(x) data.frame(nPoints=nrow(x),
nStudies=length(unique(x$paper))))
pointsAndStudies$label <- paste(pointsAndStudies$nPoints, " Points\n", pointsAndStudies$nStudies, " Studies", sep="")
# Add the letters to a data frame in order to display them
pointsAndStudies$letter <- NA
pointsAndStudies[pointsAndStudies$perm=="proteinase K", "letter"] <- "a"
pointsAndStudies[pointsAndStudies$perm=="lysozyme/\nachromopeptidase", "letter"] <- "b"
pointsAndStudies[pointsAndStudies$perm=="detergent", "letter"] <- "b"
pointsAndStudies[pointsAndStudies$perm=="lysozyme", "letter"] <- "c"
# Plot of % Archaea by permeabilization method, all depths
p_percent_arc_all_depths <- ggplot(p_percent_arc_data) +
geom_boxplot(data=p_percent_arc_data, aes(x=perm, y=Fraction.Arc.CARDFISH, fill=perm), outlier.size=1) +
geom_text(data=pointsAndStudies, aes(x=perm, y=1.2, label=label), vjust=1, size=2) +
geom_text(data=pointsAndStudies, aes(x=perm, y=-0.03, label=letter), vjust=1, size=2.5) +
scale_y_continuous(percent_arc_label, limits=c(-0.1, 1.25), breaks=seq(from=0, to=1, by=0.25)) +
scale_x_discrete("All Data") +
scale_fill_manual(values=box_col, name="permeabilization\nmethod") +
theme(legend.position="none",
text=element_text(size=8),
axis.text.x=element_text(angle=0, hjust=0.5),
axis.title.y=element_text(size=yaxsize))#,
#plot.margin=unit(fig2bc_spacing, "in"))
# Calculate % Archaea for all data
percent_arc_all_depths <- ddply(p_percent_arc_data, .(perm), summarise,
median=quantile(Fraction.Arc.CARDFISH, probs=0.50, na.rm=TRUE),
twenty.fifth.percentile=quantile(Fraction.Arc.CARDFISH, probs=0.25, na.rm=TRUE),
seventy.fifth.percentile=quantile(Fraction.Arc.CARDFISH, probs=0.75, na.rm=TRUE))
# Create a data frame to hold all data and < 1 m depth
percent_arc_all_depths$quantity <- "fraction archaea"
percent_arc_all_depths$dataset <- "all depths"
#=========
# Fig 2c: boxplots of percent ARC for only seds < 1 m deep
#=========
p_percent_arc_shallow_data <- p_percent_arc_data[p_percent_arc_data$depth <= 1, ]
# Calculate the number of data points and studies
pointsAndStudies1m <- ddply(p_percent_arc_shallow_data, .(perm),
function(x) data.frame(nPoints=nrow(x),
nStudies=length(unique(x$paper))))
pointsAndStudies1m$label <- paste(pointsAndStudies1m$nPoints, " Points\n", pointsAndStudies1m$nStudies, " Studies", sep="")
# Add letter labels for signifciantly different permeabilization methods
pointsAndStudies1m$letter <- NA
pointsAndStudies1m[pointsAndStudies1m$perm=="proteinase K", "letter"] <- "a"
pointsAndStudies1m[pointsAndStudies1m$perm=="lysozyme/\nachromopeptidase", "letter"] <- "b"
pointsAndStudies1m[pointsAndStudies1m$perm=="detergent", "letter"] <- "b"
pointsAndStudies1m[pointsAndStudies1m$perm=="lysozyme", "letter"] <- "b"
p_percent_arc_shallow <- ggplot(p_percent_arc_shallow_data) +
geom_boxplot(data=p_percent_arc_shallow_data, aes(x=perm, y=Fraction.Arc.CARDFISH, fill=perm), outlier.size=1) +
geom_text(data=pointsAndStudies1m, aes(x=perm, y=1.2, label=label), vjust=1, size=2) +
geom_text(data=pointsAndStudies1m, aes(x=perm, y=-0.03, label=letter), vjust=1, size=2.5) +
scale_y_continuous(percent_arc_label,limits=c(-0.1, 1.25), breaks=seq(from=0, to=1, by=0.25)) +
scale_x_discrete("Shallower than 1 m") +
scale_fill_manual(values=box_col) +
theme(legend.position="none",
text=element_text(size=8),
axis.text.x=element_text(angle=0, hjust=0.5),
axis.text.x=element_blank(),
axis.title.y=element_text(size=yaxsize))#,
#plot.margin=unit(fig2bc_spacing, "in"))
# Calculate % Archaea for data < 1m deep
percent_arc_shallow <- ddply(p_percent_arc_shallow_data, .(perm), summarise,
median=quantile(Fraction.Arc.CARDFISH, probs=0.50, na.rm=TRUE),
twenty.fifth.percentile=quantile(Fraction.Arc.CARDFISH, probs=0.25, na.rm=TRUE),
seventy.fifth.percentile=quantile(Fraction.Arc.CARDFISH, probs=0.75, na.rm=TRUE))
percent_arc_shallow$quantity <- "fraction archaea"
percent_arc_shallow$dataset <- "< 1 m"
#====================
# Fig 2d and 2e: same as Fig 2b and c, but with yield
#====================
p_yield_data <- corrected_seds[!is.na(corrected_seds$Arc.permeabilization) &
!is.na(corrected_seds$Fish.or.cardFish) &
!is.na(corrected_seds$FISH.yield) &
!corrected_seds$Arc.permeabilization=="unknown" &
!corrected_seds$Arc.permeabilization=="not measured" &
!corrected_seds$Fish.or.cardFish=="FISH" &
corrected_seds$Environment.Type != "Intertidal" &
corrected_seds$Environment.Type != "Salt marsh", ]
#p_yield_data <- fig2b_data
p_yield_data$perm <- as.character(p_yield_data$Arc.permeabilization)
#fig2b_data$perm[fig2b_data$Fish.or.cardFish=="FISH"] <- "FISH"
p_yield_data$perm <- factor(p_yield_data$perm,
levels=c("proteinase K", "lysozyme/achromopeptidase", "detergent", "lysozyme"),
labels=c("proteinase K", "lysozyme/\nachromopeptidase", "detergent", "lysozyme"),
ordered=TRUE)
p_yield_shallow_data <- p_yield_data[!is.na(p_yield_data$depth) &
p_yield_data$depth <= 1, ]
# proteinase K gets A
# lysozyme-achromopeptidase gets B
# detergent gets B
# lysozyme gets C
pointsAndStudiesYield <- ddply(p_yield_data, .(perm),
function(x) data.frame(nPoints=nrow(x),
nStudies=length(unique(x$paper))))
pointsAndStudiesYield$label <- paste(pointsAndStudies$nPoints, " Points\n", pointsAndStudies$nStudies, " Studies", sep="")
pointsAndStudiesYield$letter <- NA
pointsAndStudiesYield[pointsAndStudiesYield$perm=="proteinase K", "letter"] <- "a"
pointsAndStudiesYield[pointsAndStudiesYield$perm=="lysozyme/\nachromopeptidase", "letter"] <- "b"
pointsAndStudiesYield[pointsAndStudiesYield$perm=="detergent", "letter"] <- "b"
pointsAndStudiesYield[pointsAndStudiesYield$perm=="lysozyme", "letter"] <- "c"
swDF <- data.frame(perm=c(0, 1, 2, 5), #perm = levels(p_yield_data$perm), #
ymin=rep(sw_quant[1], nlevels(p_yield_data$perm)),
ymed=rep(sw_quant[2], nlevels(p_yield_data$perm)),
ymax=rep(sw_quant[3], nlevels(p_yield_data$perm)))
p_yield_all <- ggplot(p_yield_data) +
geom_blank(data=p_yield_data, aes(x=perm, y=FISH.yield, fill=perm)) +
geom_ribbon(data=swDF, aes(x=perm, ymin=ymin, ymax=ymax), fill="skyblue") +
geom_line(data=swDF, aes(x=perm, y=ymed)) +
geom_boxplot(data=p_yield_data, aes(x=perm, y=FISH.yield, fill=perm), outlier.size=1) +
geom_text(data=pointsAndStudiesYield, aes(x=perm, y=1.4, label=label), vjust=1, size=2) +
geom_text(data=pointsAndStudiesYield, aes(x=perm, y=0, label=letter), vjust=1, size=2.5) +
#scale_y_continuous("yield", limits=c(-0.1, 1.25)) +
coord_cartesian(xlim=c(0.25, 4.75), ylim=c(-0.1, 1.5)) +
xlab("All data") +
ylab(yield_label) +
scale_fill_manual(values=box_col, name="permeabilization\nmethod") +
theme(legend.position="none",
text=element_text(size=8),
axis.text.x=element_text(angle=0, hjust=0.5),
axis.text.x=element_blank(),
axis.title.y=element_text(size=yaxsize),
#plot.margin=unit(fig2bc_spacing, "in"),
axis.title.x=element_blank())
# Calculate median and IQR of yield for all data
yield_all_data <- ddply(p_yield_data, .(perm), summarise,
median=quantile(FISH.yield, probs=0.50, na.rm=TRUE),
twenty.fifth.percentile=quantile(FISH.yield, probs=0.25, na.rm=TRUE),
seventy.fifth.percentile=quantile(FISH.yield, probs=0.75, na.rm=TRUE))
yield_all_data$quantity <- "yield"
yield_all_data$dataset <- "all data"
pointsAndStudiesYield1m <- ddply(p_yield_shallow_data, .(perm),
function(x) data.frame(nPoints=nrow(x),
nStudies=length(unique(x$paper))))
pointsAndStudiesYield1m$label <- paste(pointsAndStudies$nPoints, " Points\n", pointsAndStudies$nStudies, " Studies", sep="")
pointsAndStudiesYield1m$letter <- NA
pointsAndStudiesYield1m[pointsAndStudiesYield1m$perm=="proteinase K", "letter"] <- "a"
pointsAndStudiesYield1m[pointsAndStudiesYield1m$perm=="lysozyme/\nachromopeptidase", "letter"] <- "b"
pointsAndStudiesYield1m[pointsAndStudiesYield1m$perm=="detergent", "letter"] <- "b"
pointsAndStudiesYield1m[pointsAndStudiesYield1m$perm=="lysozyme", "letter"] <- "c"
p_yield_shallow <- ggplot(p_yield_shallow_data) +
geom_blank(data=p_yield_shallow_data, aes(x=perm, y=FISH.yield, fill=perm)) +
geom_ribbon(data=swDF, aes(x=perm, ymin=ymin, ymax=ymax), fill="skyblue") +
geom_line(data=swDF, aes(x=perm, y=ymed)) +
geom_boxplot(data=p_yield_shallow_data, aes(x=perm, y=FISH.yield, fill=perm), outlier.size=1) +
geom_text(data=pointsAndStudies1m, aes(x=perm, y=1.4, label=label), vjust=1, size=2) +
geom_text(data=pointsAndStudies1m, aes(x=perm, y=0, label=letter), vjust=1, size=2.5) +
#scale_y_continuous("yield", limits=c(-0.1, 1.25)) +
coord_cartesian(xlim=c(0.25, 4.75), ylim=c(-0.1, 1.5)) +
#xlab("Shallower than 1 m") +
ylab(yield_label) +
scale_fill_manual(values=box_col, name="permeabilization\nmethod") +
theme(legend.position="none",
text=element_text(size=8),
axis.text.x=element_text(angle=0, hjust=0.5),
axis.text.x=element_blank(),
axis.title.y=element_text(size=yaxsize),
#plot.margin=unit(fig2bc_spacing, "in"),
#plot.margin=unit(c(0, 0, 0, 0), "in"),
axis.title.x=element_blank())
# Calculate median and IQR opf yield for <1 m data
yield_shallow <- ddply(p_yield_shallow_data, .(perm), summarise,
median=quantile(FISH.yield, probs=0.50, na.rm=TRUE),
twenty.fifth.percentile=quantile(FISH.yield, probs=0.25, na.rm=TRUE),
seventy.fifth.percentile=quantile(FISH.yield, probs=0.75, na.rm=TRUE))
yield_shallow$quantity <- "yield"
yield_shallow$dataset <- "< 1 m"
# Bind the summary data frames into a single frame
permeabilization_methods_summary <- rbind(percent_arc_all_depths,
percent_arc_shallow)#,
permeabilization_methods_summary <- rbind(permeabilization_methods_summary,
yield_all_data)
permeabilization_methods_summary <- rbind(permeabilization_methods_summary,
yield_shallow)
permeabilization_methods_summary$perm <- as.character(permeabilization_methods_summary$perm)
permeabilization_methods_summary$perm[permeabilization_methods_summary$perm=="lysozyme/\nachromopeptidase"] <- "lys/achrom"
# Return values
list(p_percent_arc_all_depths=p_percent_arc_all_depths,
p_percent_arc_shallow=p_percent_arc_shallow,
p_yield_all=p_yield_all,
p_yield_shallow=p_yield_shallow,
permeabilization_methods_summary=permeabilization_methods_summary)
}
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