R/methods-trouvelot.R
In mchiapello/Ramf: Arbuscular Mycorrhizal colonization calculation
Defines functions
am_dotplot.trouvelot
am_boxplot.trouvelot
am_barplot.trouvelot
am_stat.trouvelot
am_dotplot2.trouvelot
am_boxplot2.trouvelot
am_barplot2.trouvelot
am_summary.trouvelot
#' @export
am_summary.trouvelot <- function(x){
A <- M <- a <- num <- Samples <- n <- NULL
tmp <- trouvelot_summary(x)
# Final table
final <- tmp %>%
group_by(Samples) %>%
mutate(num = dplyr::n()) %>%
summarise(`Mean F` = round(mean(F, na.rm = TRUE), 2),
`Standard error F` = round(sd(F, na.rm = TRUE) / sqrt(mean(num, na.rm = TRUE)), 2),
`Mean M` = round(mean(M, na.rm = TRUE), 2),
`Standard error M` = round(sd(M, na.rm = TRUE) / sqrt(mean(num, na.rm = TRUE)), 2),
`Mean a` = round(mean(a, na.rm = TRUE), 2),
`Standar error a` = round(sd(a, na.rm = TRUE) / sqrt(mean(num, na.rm = TRUE)), 2),
`Mean A` = round(mean(A, na.rm = TRUE), 2),
`Standard error A` = round(sd(A, na.rm = TRUE) / sqrt(mean(num, na.rm = TRUE)), 2)
)
final <- final[match(unique(x$Samples), final$Samples), ]
l <- list(tmp, final)
names(l) <- c("Summary per Replicate", "Summary per Sample")
class(l) <- c("am_summary", "list")
return(l)
}
#' @export
am_barplot2.trouvelot <- function(x, cbPalette = c("#999999", "#E69F00", "#56B4E9",
"#009E73", "#F0E442", "#0072B2",
"#D55E00", "#CC79A7"),
alpha = 0.05,
annot = c("none", "asterisks", "letters"),
annot_size = 5,
method = c("none","holm","hommel", "hochberg",
"bonferroni", "BH", "BY", "fdr"),
main = "Trouvelot method", ...){
A <- Abundance <- Colonization <- M <- M1 <- a <- feature <- features <- final_a <- m <- NULL
mA <- n_myc <- nn <- num <- perc <- Replicates <- Samples <- Scoring <- tmpa <- tot <- tot2 <- value <- n <- NULL
values <- means <- se <- num <- NULL
alpha <- alpha
annot <- match.arg(annot)
method <- match.arg(method)
# Create summary table
tmp <- trouvelot_summary(x)
if (annot == "none"){
d <- rep("", length(unique(tmp$Samples)) * 4)
dimen <- annot_size
}
if (annot == "asterisks"){
stat <- .trouvelot_stat(x, method = method, group = FALSE, alpha = alpha)
stat_ctr <- stat[stat$group1 == tmp$Samples[1], ]
stat_l <- ifelse(as.numeric(as.matrix(stat_ctr[, 3:6])) < alpha, "*", "")
ll <- split(stat_l, rep(1:4, each = length(unique(tmp$Samples)) - 1))
d <- NULL
for (i in seq_along(ll)){
d <- append(d, c("", ll[[i]]))
}
dimen <- annot_size
}
if (annot == "letters"){
stat <- .trouvelot_stat(x, method = method, group = TRUE, alpha = alpha)
d <- as.vector(as.matrix(stat[,2:5]))
dimen <- annot_size
}
z <- tmp %>% tidyr::gather(features, values, -Samples, -Replicates)
final <- z %>% group_by(Samples, features) %>%
mutate(num = dplyr::n()) %>%
summarize(means = mean(values, na.rm = TRUE),
se = sd(values, na.rm = TRUE) / sqrt(mean(num, na.rm = TRUE))) %>%
ungroup %>%
mutate(Samples = factor(Samples, levels = unique(x$Samples))) %>%
arrange(features, Samples) %>%
group_by(Samples, features)
g <- ggplot(data = final, aes(x = interaction(factor(final$Samples, levels = unique(x$Samples)),
factor(final$features, levels = c("F", "M", "a", "A"))),
y = means, fill = Samples))
a1 <- g + geom_col() + theme(axis.text.x = element_text(angle = 90, vjust = .5, hjust = 1)) +
geom_errorbar(aes(ymin = means - se, ymax = means + se), width = .1) +
theme_bw() +
theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1),
plot.title = element_text(size = 19),
panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
legend.position = "none") +
geom_vline(xintercept = seq(length(unique(final$Samples)) + .5, length(unique(final$Samples)) * 3 + .5,
length(unique(final$Samples))), colour = "lightgrey") +
# geom_hline(yintercept = 105, colour = "lightgrey") +
labs(title = main,
# subtitle = "Trouvelot method",
x = "",
y = "root colonization [%]") +
annotate("text", x = seq(length(unique(final$Samples)) * .5 + .5, length(unique(final$Samples)) * 5 + .5,
length(unique(final$Samples)))[1:4],
y = 110, label = c("F%", "M%", "a%", "A%")) +
annotate("text", x = 1:(length(unique(tmp$Samples)) * 4),
y = -Inf, vjust = -0.5, label = d, size = dimen) +
scale_x_discrete(labels = rep(unique(x$Samples), 5)) +
scale_y_continuous(limits = c(ifelse(min(final$means - final$se) < 0,
min(final$means - final$se), 0), 110), breaks = seq(0, 110, 20)) +
scale_fill_manual(values = cbPalette,
breaks = levels(factor(final$Samples, levels = unique(x$Samples))),
name = "")
class(a1) <- c("am_plot", class(a1))
return(a1)
}
#' @export
am_boxplot2.trouvelot <- function(x, cbPalette = c("#999999", "#E69F00", "#56B4E9",
"#009E73", "#F0E442", "#0072B2",
"#D55E00", "#CC79A7"),
alpha = 0.05,
annot = c("none", "asterisks", "letters"),
annot_size = 5,
method = c("none","holm","hommel", "hochberg",
"bonferroni", "BH", "BY", "fdr"),
main = "Trouvelot method", ...){
A <- Abundance <- Colonization <- M <- M1 <- a <- feature <- features <- final <- m <- NULL
mA <- n_myc <- nn <- num <- perc <- Replicates <- Samples <- Scoring <- tmpa <- tot <- tot2 <- value <- NULL
values <- NULL
alpha <- alpha
annot <- match.arg(annot)
method <- match.arg(method)
# Create summary table
tmp <- trouvelot_summary(x)
if (annot == "none"){
d <- rep("", length(unique(tmp$Samples)) * 4)
dimen <- annot_size
}
if (annot == "asterisks"){
stat <- .trouvelot_stat(x, method = method, group = FALSE, alpha = alpha)
stat_ctr <- stat[stat$group1 == tmp$Samples[1], ]
stat_l <- ifelse(as.numeric(as.matrix(stat_ctr[, 3:6])) < alpha, "*", "")
ll <- split(stat_l, rep(1:4, each = length(unique(tmp$Samples)) - 1))
d <- NULL
for (i in seq_along(ll)){
d <- append(d, c("", ll[[i]]))
}
dimen <- annot_size
}
if (annot == "letters"){
stat <- .trouvelot_stat(x, method = method, group = TRUE, alpha = alpha)
d <- as.vector(as.matrix(stat[,2:5]))
dimen <- annot_size
}
final <- tmp %>% gather(feature, value, -Samples, -Replicates) %>%
ungroup %>%
mutate(Samples = factor(Samples, levels = unique(x$Samples))) %>%
arrange(Samples) %>%
group_by(Samples)
g <- ggplot(data = final, aes(x = interaction(factor(final$Samples, levels = unique(x$Samples)),
factor(final$feature, levels = c("F", "A", "a", "M")),
sep = ": "),
y = value, color = Samples))
a2 <- g +
geom_boxplot() +
theme_bw() +
theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1),
plot.title = element_text(size = 19),
panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
legend.position = "none") +
geom_vline(xintercept = seq(length(unique(final$Samples)) + .5, length(unique(final$Samples)) * 3 + .5,
length(unique(final$Samples))), colour = "lightgrey") +
# geom_hline(yintercept = 105, colour = "lightgrey") +
labs(title = main,
# subtitle = "Trouvelot method",
x = "",
y = "root colonization [%]") +
annotate("text", x = seq(length(unique(final$Samples)) * .5 + .5, length(unique(final$Samples)) * 5 + .5,
length(unique(final$Samples)))[1:4],
y = 110, label = c("F%", "M%", "a%", "A%")) +
annotate("text", x = 1:(length(unique(tmp$Samples)) * 4),
y = -Inf, vjust = -0.5, label = d, size = dimen) +
scale_x_discrete(labels = rep(unique(x$Samples), 5)) +
scale_y_continuous(limits = c(-0.5, 110), breaks = seq(0, 110, 20)) +
scale_colour_manual(values = cbPalette,
breaks = levels(factor(final$Samples,
levels = unique(x$Samples))),
name = "")
class(a2) <- c("am_plot", class(a2))
return(a2)
}
#' @export
am_dotplot2.trouvelot <- function(x, cbPalette = c("#999999", "#E69F00", "#56B4E9",
"#009E73", "#F0E442", "#0072B2",
"#D55E00", "#CC79A7"),
alpha = 0.05,
annot = c("none", "asterisks", "letters"),
annot_size = 5,
method = c("none","holm","hommel", "hochberg",
"bonferroni", "BH", "BY", "fdr"),
main = "Trouvelot method", ...){
A <- Abundance <- Colonization <- M <- M1 <- a <- feature <- features <- final <- m <- NULL
mA <- n_myc <- nn <- num <- perc <- Replicates <- Samples <- Scoring <- tmpa <- tot <- tot2 <- value <- NULL
values <- NULL
alpha <- alpha
annot <- match.arg(annot)
method <- match.arg(method)
# Create summary table
tmp <- trouvelot_summary(x)
if (annot == "none"){
d <- rep("", length(unique(tmp$Samples)) * 4)
dimen <- annot_size
}
if (annot == "asterisks"){
stat <- .trouvelot_stat(x, method = method, group = FALSE, alpha = alpha)
stat_ctr <- stat[stat$group1 == tmp$Samples[1], ]
stat_l <- ifelse(as.numeric(as.matrix(stat_ctr[, 3:6])) < alpha, "*", "")
ll <- split(stat_l, rep(1:4, each = length(unique(tmp$Samples)) - 1))
d <- NULL
for (i in seq_along(ll)){
d <- append(d, c("", ll[[i]]))
}
dimen <- annot_size
}
if (annot == "letters"){
stat <- .trouvelot_stat(x, method = method, group = TRUE, alpha = alpha)
d <- as.vector(as.matrix(stat[,2:5]))
dimen <- annot_size
}
final <- tmp %>% gather(feature, value, -Samples, -Replicates) %>%
ungroup %>%
mutate(Samples = factor(Samples, levels = unique(x$Samples))) %>%
arrange(Samples) %>%
group_by(Samples)
g <- ggplot(data = final, aes(x = interaction(factor(final$Samples, levels = unique(x$Samples)),
factor(final$feature, levels = c("F", "A", "a", "M")),
sep = ": "),
y = value, color = as.factor(Samples)))
a2 <- g +
geom_point(position = position_jitter(width = 0.2)) +
theme_bw() +
theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1),
plot.title = element_text(size = 19),
panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
legend.position = "none") +
geom_vline(xintercept = seq(length(unique(final$Samples)) + .5, length(unique(final$Samples)) * 3 + .5,
length(unique(final$Samples))), colour = "lightgrey") +
# geom_hline(yintercept = 105, colour = "lightgrey") +
labs(title = main,
# subtitle = "Trouvelot method",
x = "",
y = "root colonization [%]") +
annotate("text", x = seq(length(unique(final$Samples)) * .5 + .5, length(unique(final$Samples)) * 5 + .5,
length(unique(final$Samples)))[1:4],
y = 110, label = c("F%", "M%", "a%", "A%")) +
annotate("text", x = 1:(length(unique(tmp$Samples)) * 4),
y = -Inf, vjust = -0.5, label = d, size = dimen) +
scale_x_discrete(labels = rep(unique(x$Samples), 5)) +
scale_y_continuous(limits = c(-0.5, 110), breaks = seq(0, 110, 20)) +
scale_colour_manual(values = cbPalette,
breaks = levels(factor(final$Samples,
levels = unique(x$Samples))),
name = "")
class(a2) <- c("am_plot", class(a2))
return(a2)
}
#' @export
am_stat.trouvelot <- function(x, method = c("none","holm","hommel", "hochberg",
"bonferroni", "BH", "BY", "fdr"), ...){
method <- match.arg(method)
stat <- .trouvelot_stat(x, method = method)
return(stat)
}
###############################################################################
#' @export
am_barplot.trouvelot <- function(x, cbPalette = c("#999999", "#E69F00", "#56B4E9",
"#009E73", "#F0E442", "#0072B2",
"#D55E00", "#CC79A7"),
alpha = 0.05,
annot = c("none", "asterisks", "letters"),
annot_size = 5,
method = c("none","holm","hommel", "hochberg",
"bonferroni", "BH", "BY", "fdr"),
legend = c("right", "left", "top", "bottom"),
main = "Trouvelot method", ...){
A <- Abundance <- Colonization <- M <- M1 <- a <- feature <- features <- final_a <- m <- NULL
mA <- n_myc <- nn <- num <- perc <- Replicates <- Samples <- Scoring <- tmpa <- tot <- tot2 <- value <- n <- NULL
values <- means <- se <- num <- NULL
alpha <- alpha
annot <- match.arg(annot)
method <- match.arg(method)
legend <- match.arg(legend)
# Create summary table
y <- trouvelot_summary(x)
z <- y %>% tidyr::gather(features, values, -Samples, -Replicates)
final <- z %>% group_by(Samples, features) %>%
mutate(num = dplyr::n()) %>%
summarize(means = mean(values, na.rm = TRUE),
se = sd(values, na.rm = TRUE) / sqrt(mean(num, na.rm = TRUE))) %>%
ungroup %>%
mutate(features = factor(features, levels = c("F", "M", "a", "A")),
Samples = factor(Samples, levels = unique(x$Samples))) %>%
arrange(features, Samples)
# Add annotations
if (annot == "none"){
final <- final %>%
mutate(annot = rep("", nrow(final))) %>%
group_by(Samples)
dimen <- annot_size
}
if (annot == "asterisks"){
stat <- .trouvelot_stat(x, method = method, group = FALSE, alpha = alpha)
stat_ctr <- stat[stat$group1 == y$Samples[1], ]
stat_l <- ifelse(as.numeric(as.matrix(stat_ctr[, 3:6])) < alpha, "*", "")
ll <- split(stat_l, rep(1:4, each = length(unique(y$Samples)) - 1))
d <- NULL
for (i in seq_along(ll)){
d <- append(d, c("", ll[[i]]))
}
final <- final %>%
mutate(annot = d) %>%
group_by(Samples)
dimen <- annot_size
}
if (annot == "letters"){
stat <- .trouvelot_stat(x, method = method, group = TRUE, alpha = alpha)
d <- as.vector(as.matrix(stat[,2:5]))
final <- final %>%
mutate(annot = d) %>%
group_by(Samples)
dimen <- annot_size
}
g <- ggplot(data = final, aes(x = features, y = means, fill = Samples))
dodge <- position_dodge(width=0.9)
a1 <- g + geom_col(position = dodge) + theme(axis.text.x = element_text(angle = 90, vjust = .5, hjust = 1)) +
geom_errorbar(aes(ymin = means - se, ymax = means + se), width = .1, position = dodge) +
theme_bw() +
theme(plot.title = element_text(size = 19),
panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
legend.position = legend) +
labs(title = main,
# subtitle = "Grid method",
x = "",
y = "root colonization [%]") +
geom_text(aes( label = annot, y = (means + se)), vjust = -0.5, position = dodge,
show.legend = FALSE, size = dimen) +
scale_y_continuous(limits = c(-0.5, 110),
breaks = seq(0, 110, 20))+
scale_fill_manual(values = cbPalette,
breaks = levels(factor(final$Samples,
levels = unique(x$Samples))),
name = "")
class(a1) <- c("am_plot", class(a1))
return(a1)
}
#' @export
am_boxplot.trouvelot <- function(x, cbPalette = c("#999999", "#E69F00", "#56B4E9",
"#009E73", "#F0E442", "#0072B2",
"#D55E00", "#CC79A7"),
alpha = 0.05,
annot = c("none", "asterisks", "letters"),
annot_size = 5,
method = c("none","holm","hommel", "hochberg",
"bonferroni", "BH", "BY", "fdr"),
legend = c("right", "left", "top", "bottom"),
main = "Trouvelot method", ...){
A <- Abundance <- Colonization <- M <- M1 <- a <- feature <- features <- final_a <- m <- NULL
mA <- n_myc <- nn <- num <- perc <- Replicates <- Samples <- Scoring <- tmpa <- tot <- tot2 <- value <- Var1 <- NULL
values <- NULL
alpha <- alpha
annot <- match.arg(annot)
method <- match.arg(method)
legend <- match.arg(legend)
# Create summary table
y <- trouvelot_summary(x)
final <- y %>%
gather(features, values, -Samples, -Replicates) %>%
ungroup %>%
mutate(features = factor(features, levels = c("F", "M", "a", "A")),
Samples = factor(Samples, levels = unique(x$Samples))) %>%
arrange(features, Samples)
# Add annotations
if (annot == "none"){
tmp <- expand.grid(unique(final$features), unique(final$Samples)) %>%
arrange(Var1) %>%
mutate(annot = "")
an <- final %>%
left_join(tmp, by = c("features" = "Var1", "Samples" = "Var2")) %>%
group_by(Samples, features) %>%
dplyr::filter(values == max(values)) %>%
arrange(features, Samples) %>%
dplyr::top_n(1, Replicates)
dimen <- annot_size
}
if (annot == "asterisks"){
stat <- .trouvelot_stat(x, method = method, group = FALSE, alpha = alpha)
stat_ctr <- stat[stat$group1 == y$Samples[1], ]
stat_l <- ifelse(as.numeric(as.matrix(stat_ctr[, 3:6])) < alpha, "*", "")
ll <- split(stat_l, rep(1:4, each = length(unique(y$Samples)) - 1))
d <- NULL
for (i in seq_along(ll)){
d <- append(d, c("", ll[[i]]))
}
tmp <- expand.grid(unique(final$features), unique(final$Samples)) %>%
arrange(Var1) %>%
mutate(annot = d)
an <- final %>%
left_join(tmp, by = c("features" = "Var1", "Samples" = "Var2")) %>%
group_by(Samples, features) %>%
dplyr::filter(values == max(values)) %>%
arrange(features, Samples) %>%
dplyr::top_n(1, Replicates)
dimen <- annot_size
}
if (annot == "letters"){
stat <- .trouvelot_stat(x, method = method, group = TRUE, alpha = alpha)
d <- as.vector(as.matrix(stat[,2:5]))
tmp <- expand.grid(unique(final$features), unique(final$Samples)) %>%
arrange(Var1) %>%
mutate(annot = d)
an <- final %>%
left_join(tmp, by = c("features" = "Var1", "Samples" = "Var2")) %>%
group_by(Samples, features) %>%
dplyr::filter(values == max(values)) %>%
arrange(features, Samples) %>%
dplyr::top_n(1, Replicates)
dimen <- annot_size
}
g <- ggplot(data = final, aes(x = features,
y = values, color = Samples))
dodge <- position_dodge(width=0.75)
a2 <- g +
geom_boxplot() +
theme_bw() +
theme(plot.title = element_text(size = 19),
panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
legend.position = legend) +
geom_vline(xintercept = seq(1.5, length(unique(an$features))-0.5, 1),
colour = "lightgrey") +
labs(title = main,
# subtitle = "Grid method",
x = "",
y = "root colonization [%]") +
geom_text(data = an, aes(x = features, label = annot, y = values), vjust = -0.8,
position = dodge, show.legend = FALSE, size = dimen) +
scale_y_continuous(limits = c(-0.5, 105),
breaks = seq(0, 105, 20))+
scale_colour_manual(values = cbPalette,
breaks = levels(factor(final$Samples,
levels = unique(x$Samples))),
name = "")
class(a2) <- c("am_plot", class(a2))
return(a2)
}
#' @export
am_dotplot.trouvelot <- function(x, cbPalette = c("#999999", "#E69F00", "#56B4E9",
"#009E73", "#F0E442", "#0072B2",
"#D55E00", "#CC79A7"),
alpha = 0.05,
annot = c("none", "asterisks", "letters"),
annot_size = 5,
method = c("none","holm","hommel", "hochberg",
"bonferroni", "BH", "BY", "fdr"),
legend = c("right", "left", "top", "bottom"),
main = "Trouvelot method", ...){
A <- Abundance <- Colonization <- M <- M1 <- a <- feature <- features <- final_a <- m <- NULL
mA <- n_myc <- nn <- num <- perc <- Replicates <- Samples <- Scoring <- tmpa <- tot <- tot2 <- value <- Var1 <- NULL
values <- NULL
alpha <- alpha
annot <- match.arg(annot)
method <- match.arg(method)
legend <- match.arg(legend)
# Create summary table
y <- trouvelot_summary(x)
final <- y %>%
gather(features, values, -Samples, -Replicates) %>%
ungroup %>%
mutate(features = factor(features, levels = c("F", "M", "a", "A")),
Samples = factor(Samples, levels = unique(x$Samples))) %>%
arrange(features, Samples)
# Add annotations
if (annot == "none"){
tmp <- expand.grid(unique(final$features), unique(final$Samples)) %>%
arrange(Var1) %>%
mutate(annot = "")
an <- final %>%
left_join(tmp, by = c("features" = "Var1", "Samples" = "Var2")) %>%
group_by(Samples, features) %>%
dplyr::filter(values == max(values)) %>%
arrange(features, Samples) %>%
dplyr::top_n(1, Replicates)
dimen <- annot_size
}
if (annot == "asterisks"){
stat <- .trouvelot_stat(x, method = method, group = FALSE, alpha = alpha)
stat_ctr <- stat[stat$group1 == y$Samples[1], ]
stat_l <- ifelse(as.numeric(as.matrix(stat_ctr[, 3:6])) < alpha, "*", "")
ll <- split(stat_l, rep(1:4, each = length(unique(y$Samples)) - 1))
d <- NULL
for (i in seq_along(ll)){
d <- append(d, c("", ll[[i]]))
}
tmp <- expand.grid(unique(final$features), unique(final$Samples)) %>%
arrange(Var1) %>%
mutate(annot = d)
an <- final %>%
left_join(tmp, by = c("features" = "Var1", "Samples" = "Var2")) %>%
group_by(Samples, features) %>%
dplyr::filter(values == max(values)) %>%
arrange(features, Samples) %>%
dplyr::top_n(1, Replicates)
dimen <- annot_size
}
if (annot == "letters"){
stat <- .trouvelot_stat(x, method = method, group = TRUE, alpha = alpha)
d <- as.vector(as.matrix(stat[,2:5]))
tmp <- expand.grid(unique(final$features), unique(final$Samples)) %>%
arrange(Var1) %>%
mutate(annot = d)
an <- final %>%
left_join(tmp, by = c("features" = "Var1", "Samples" = "Var2")) %>%
group_by(Samples, features) %>%
dplyr::filter(values == max(values)) %>%
arrange(features, Samples) %>%
dplyr::top_n(1, Replicates)
dimen <- annot_size
}
g <- ggplot(data = final, aes(x = features,
y = values, color = Samples))
dodge <- position_dodge(width=0.9)
a2 <- g +
geom_point(position = position_jitterdodge(dodge.width = 0.9,
jitter.width = 0.1)) +
theme_bw() +
theme(plot.title = element_text(size = 19),
panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
legend.position = legend) +
geom_vline(xintercept = seq(1.5, length(unique(an$features))-0.5, 1),
colour = "lightgrey") +
labs(title = main,
# subtitle = "Grid method",
x = "",
y = "root colonization [%]") +
geom_text(data = an, aes(label = annot, y = values), vjust = -0.8,
position = dodge, show.legend = FALSE, size = dimen) +
scale_y_continuous(limits = c(-0.5, 105),
breaks = seq(0, 105, 20))+
scale_colour_manual(values = cbPalette,
breaks = levels(factor(final$Samples,
levels = unique(x$Samples))),
name = "")
class(a2) <- c("am_plot", class(a2))
return(a2)
}
mchiapello/Ramf documentation built on April 9, 2022, 5:07 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Defines functions am_dotplot.trouvelot am_boxplot.trouvelot am_barplot.trouvelot am_stat.trouvelot am_dotplot2.trouvelot am_boxplot2.trouvelot am_barplot2.trouvelot am_summary.trouvelot
#' @export
am_summary.trouvelot <- function(x){
A <- M <- a <- num <- Samples <- n <- NULL
tmp <- trouvelot_summary(x)
# Final table
final <- tmp %>%
group_by(Samples) %>%
mutate(num = dplyr::n()) %>%
summarise(`Mean F` = round(mean(F, na.rm = TRUE), 2),
`Standard error F` = round(sd(F, na.rm = TRUE) / sqrt(mean(num, na.rm = TRUE)), 2),
`Mean M` = round(mean(M, na.rm = TRUE), 2),
`Standard error M` = round(sd(M, na.rm = TRUE) / sqrt(mean(num, na.rm = TRUE)), 2),
`Mean a` = round(mean(a, na.rm = TRUE), 2),
`Standar error a` = round(sd(a, na.rm = TRUE) / sqrt(mean(num, na.rm = TRUE)), 2),
`Mean A` = round(mean(A, na.rm = TRUE), 2),
`Standard error A` = round(sd(A, na.rm = TRUE) / sqrt(mean(num, na.rm = TRUE)), 2)
)
final <- final[match(unique(x$Samples), final$Samples), ]
l <- list(tmp, final)
names(l) <- c("Summary per Replicate", "Summary per Sample")
class(l) <- c("am_summary", "list")
return(l)
}
#' @export
am_barplot2.trouvelot <- function(x, cbPalette = c("#999999", "#E69F00", "#56B4E9",
"#009E73", "#F0E442", "#0072B2",
"#D55E00", "#CC79A7"),
alpha = 0.05,
annot = c("none", "asterisks", "letters"),
annot_size = 5,
method = c("none","holm","hommel", "hochberg",
"bonferroni", "BH", "BY", "fdr"),
main = "Trouvelot method", ...){
A <- Abundance <- Colonization <- M <- M1 <- a <- feature <- features <- final_a <- m <- NULL
mA <- n_myc <- nn <- num <- perc <- Replicates <- Samples <- Scoring <- tmpa <- tot <- tot2 <- value <- n <- NULL
values <- means <- se <- num <- NULL
alpha <- alpha
annot <- match.arg(annot)
method <- match.arg(method)
# Create summary table
tmp <- trouvelot_summary(x)
if (annot == "none"){
d <- rep("", length(unique(tmp$Samples)) * 4)
dimen <- annot_size
}
if (annot == "asterisks"){
stat <- .trouvelot_stat(x, method = method, group = FALSE, alpha = alpha)
stat_ctr <- stat[stat$group1 == tmp$Samples[1], ]
stat_l <- ifelse(as.numeric(as.matrix(stat_ctr[, 3:6])) < alpha, "*", "")
ll <- split(stat_l, rep(1:4, each = length(unique(tmp$Samples)) - 1))
d <- NULL
for (i in seq_along(ll)){
d <- append(d, c("", ll[[i]]))
}
dimen <- annot_size
}
if (annot == "letters"){
stat <- .trouvelot_stat(x, method = method, group = TRUE, alpha = alpha)
d <- as.vector(as.matrix(stat[,2:5]))
dimen <- annot_size
}
z <- tmp %>% tidyr::gather(features, values, -Samples, -Replicates)
final <- z %>% group_by(Samples, features) %>%
mutate(num = dplyr::n()) %>%
summarize(means = mean(values, na.rm = TRUE),
se = sd(values, na.rm = TRUE) / sqrt(mean(num, na.rm = TRUE))) %>%
ungroup %>%
mutate(Samples = factor(Samples, levels = unique(x$Samples))) %>%
arrange(features, Samples) %>%
group_by(Samples, features)
g <- ggplot(data = final, aes(x = interaction(factor(final$Samples, levels = unique(x$Samples)),
factor(final$features, levels = c("F", "M", "a", "A"))),
y = means, fill = Samples))
a1 <- g + geom_col() + theme(axis.text.x = element_text(angle = 90, vjust = .5, hjust = 1)) +
geom_errorbar(aes(ymin = means - se, ymax = means + se), width = .1) +
theme_bw() +
theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1),
plot.title = element_text(size = 19),
panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
legend.position = "none") +
geom_vline(xintercept = seq(length(unique(final$Samples)) + .5, length(unique(final$Samples)) * 3 + .5,
length(unique(final$Samples))), colour = "lightgrey") +
# geom_hline(yintercept = 105, colour = "lightgrey") +
labs(title = main,
# subtitle = "Trouvelot method",
x = "",
y = "root colonization [%]") +
annotate("text", x = seq(length(unique(final$Samples)) * .5 + .5, length(unique(final$Samples)) * 5 + .5,
length(unique(final$Samples)))[1:4],
y = 110, label = c("F%", "M%", "a%", "A%")) +
annotate("text", x = 1:(length(unique(tmp$Samples)) * 4),
y = -Inf, vjust = -0.5, label = d, size = dimen) +
scale_x_discrete(labels = rep(unique(x$Samples), 5)) +
scale_y_continuous(limits = c(ifelse(min(final$means - final$se) < 0,
min(final$means - final$se), 0), 110), breaks = seq(0, 110, 20)) +
scale_fill_manual(values = cbPalette,
breaks = levels(factor(final$Samples, levels = unique(x$Samples))),
name = "")
class(a1) <- c("am_plot", class(a1))
return(a1)
}
#' @export
am_boxplot2.trouvelot <- function(x, cbPalette = c("#999999", "#E69F00", "#56B4E9",
"#009E73", "#F0E442", "#0072B2",
"#D55E00", "#CC79A7"),
alpha = 0.05,
annot = c("none", "asterisks", "letters"),
annot_size = 5,
method = c("none","holm","hommel", "hochberg",
"bonferroni", "BH", "BY", "fdr"),
main = "Trouvelot method", ...){
A <- Abundance <- Colonization <- M <- M1 <- a <- feature <- features <- final <- m <- NULL
mA <- n_myc <- nn <- num <- perc <- Replicates <- Samples <- Scoring <- tmpa <- tot <- tot2 <- value <- NULL
values <- NULL
alpha <- alpha
annot <- match.arg(annot)
method <- match.arg(method)
# Create summary table
tmp <- trouvelot_summary(x)
if (annot == "none"){
d <- rep("", length(unique(tmp$Samples)) * 4)
dimen <- annot_size
}
if (annot == "asterisks"){
stat <- .trouvelot_stat(x, method = method, group = FALSE, alpha = alpha)
stat_ctr <- stat[stat$group1 == tmp$Samples[1], ]
stat_l <- ifelse(as.numeric(as.matrix(stat_ctr[, 3:6])) < alpha, "*", "")
ll <- split(stat_l, rep(1:4, each = length(unique(tmp$Samples)) - 1))
d <- NULL
for (i in seq_along(ll)){
d <- append(d, c("", ll[[i]]))
}
dimen <- annot_size
}
if (annot == "letters"){
stat <- .trouvelot_stat(x, method = method, group = TRUE, alpha = alpha)
d <- as.vector(as.matrix(stat[,2:5]))
dimen <- annot_size
}
final <- tmp %>% gather(feature, value, -Samples, -Replicates) %>%
ungroup %>%
mutate(Samples = factor(Samples, levels = unique(x$Samples))) %>%
arrange(Samples) %>%
group_by(Samples)
g <- ggplot(data = final, aes(x = interaction(factor(final$Samples, levels = unique(x$Samples)),
factor(final$feature, levels = c("F", "A", "a", "M")),
sep = ": "),
y = value, color = Samples))
a2 <- g +
geom_boxplot() +
theme_bw() +
theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1),
plot.title = element_text(size = 19),
panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
legend.position = "none") +
geom_vline(xintercept = seq(length(unique(final$Samples)) + .5, length(unique(final$Samples)) * 3 + .5,
length(unique(final$Samples))), colour = "lightgrey") +
# geom_hline(yintercept = 105, colour = "lightgrey") +
labs(title = main,
# subtitle = "Trouvelot method",
x = "",
y = "root colonization [%]") +
annotate("text", x = seq(length(unique(final$Samples)) * .5 + .5, length(unique(final$Samples)) * 5 + .5,
length(unique(final$Samples)))[1:4],
y = 110, label = c("F%", "M%", "a%", "A%")) +
annotate("text", x = 1:(length(unique(tmp$Samples)) * 4),
y = -Inf, vjust = -0.5, label = d, size = dimen) +
scale_x_discrete(labels = rep(unique(x$Samples), 5)) +
scale_y_continuous(limits = c(-0.5, 110), breaks = seq(0, 110, 20)) +
scale_colour_manual(values = cbPalette,
breaks = levels(factor(final$Samples,
levels = unique(x$Samples))),
name = "")
class(a2) <- c("am_plot", class(a2))
return(a2)
}
#' @export
am_dotplot2.trouvelot <- function(x, cbPalette = c("#999999", "#E69F00", "#56B4E9",
"#009E73", "#F0E442", "#0072B2",
"#D55E00", "#CC79A7"),
alpha = 0.05,
annot = c("none", "asterisks", "letters"),
annot_size = 5,
method = c("none","holm","hommel", "hochberg",
"bonferroni", "BH", "BY", "fdr"),
main = "Trouvelot method", ...){
A <- Abundance <- Colonization <- M <- M1 <- a <- feature <- features <- final <- m <- NULL
mA <- n_myc <- nn <- num <- perc <- Replicates <- Samples <- Scoring <- tmpa <- tot <- tot2 <- value <- NULL
values <- NULL
alpha <- alpha
annot <- match.arg(annot)
method <- match.arg(method)
# Create summary table
tmp <- trouvelot_summary(x)
if (annot == "none"){
d <- rep("", length(unique(tmp$Samples)) * 4)
dimen <- annot_size
}
if (annot == "asterisks"){
stat <- .trouvelot_stat(x, method = method, group = FALSE, alpha = alpha)
stat_ctr <- stat[stat$group1 == tmp$Samples[1], ]
stat_l <- ifelse(as.numeric(as.matrix(stat_ctr[, 3:6])) < alpha, "*", "")
ll <- split(stat_l, rep(1:4, each = length(unique(tmp$Samples)) - 1))
d <- NULL
for (i in seq_along(ll)){
d <- append(d, c("", ll[[i]]))
}
dimen <- annot_size
}
if (annot == "letters"){
stat <- .trouvelot_stat(x, method = method, group = TRUE, alpha = alpha)
d <- as.vector(as.matrix(stat[,2:5]))
dimen <- annot_size
}
final <- tmp %>% gather(feature, value, -Samples, -Replicates) %>%
ungroup %>%
mutate(Samples = factor(Samples, levels = unique(x$Samples))) %>%
arrange(Samples) %>%
group_by(Samples)
g <- ggplot(data = final, aes(x = interaction(factor(final$Samples, levels = unique(x$Samples)),
factor(final$feature, levels = c("F", "A", "a", "M")),
sep = ": "),
y = value, color = as.factor(Samples)))
a2 <- g +
geom_point(position = position_jitter(width = 0.2)) +
theme_bw() +
theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1),
plot.title = element_text(size = 19),
panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
legend.position = "none") +
geom_vline(xintercept = seq(length(unique(final$Samples)) + .5, length(unique(final$Samples)) * 3 + .5,
length(unique(final$Samples))), colour = "lightgrey") +
# geom_hline(yintercept = 105, colour = "lightgrey") +
labs(title = main,
# subtitle = "Trouvelot method",
x = "",
y = "root colonization [%]") +
annotate("text", x = seq(length(unique(final$Samples)) * .5 + .5, length(unique(final$Samples)) * 5 + .5,
length(unique(final$Samples)))[1:4],
y = 110, label = c("F%", "M%", "a%", "A%")) +
annotate("text", x = 1:(length(unique(tmp$Samples)) * 4),
y = -Inf, vjust = -0.5, label = d, size = dimen) +
scale_x_discrete(labels = rep(unique(x$Samples), 5)) +
scale_y_continuous(limits = c(-0.5, 110), breaks = seq(0, 110, 20)) +
scale_colour_manual(values = cbPalette,
breaks = levels(factor(final$Samples,
levels = unique(x$Samples))),
name = "")
class(a2) <- c("am_plot", class(a2))
return(a2)
}
#' @export
am_stat.trouvelot <- function(x, method = c("none","holm","hommel", "hochberg",
"bonferroni", "BH", "BY", "fdr"), ...){
method <- match.arg(method)
stat <- .trouvelot_stat(x, method = method)
return(stat)
}
###############################################################################
#' @export
am_barplot.trouvelot <- function(x, cbPalette = c("#999999", "#E69F00", "#56B4E9",
"#009E73", "#F0E442", "#0072B2",
"#D55E00", "#CC79A7"),
alpha = 0.05,
annot = c("none", "asterisks", "letters"),
annot_size = 5,
method = c("none","holm","hommel", "hochberg",
"bonferroni", "BH", "BY", "fdr"),
legend = c("right", "left", "top", "bottom"),
main = "Trouvelot method", ...){
A <- Abundance <- Colonization <- M <- M1 <- a <- feature <- features <- final_a <- m <- NULL
mA <- n_myc <- nn <- num <- perc <- Replicates <- Samples <- Scoring <- tmpa <- tot <- tot2 <- value <- n <- NULL
values <- means <- se <- num <- NULL
alpha <- alpha
annot <- match.arg(annot)
method <- match.arg(method)
legend <- match.arg(legend)
# Create summary table
y <- trouvelot_summary(x)
z <- y %>% tidyr::gather(features, values, -Samples, -Replicates)
final <- z %>% group_by(Samples, features) %>%
mutate(num = dplyr::n()) %>%
summarize(means = mean(values, na.rm = TRUE),
se = sd(values, na.rm = TRUE) / sqrt(mean(num, na.rm = TRUE))) %>%
ungroup %>%
mutate(features = factor(features, levels = c("F", "M", "a", "A")),
Samples = factor(Samples, levels = unique(x$Samples))) %>%
arrange(features, Samples)
# Add annotations
if (annot == "none"){
final <- final %>%
mutate(annot = rep("", nrow(final))) %>%
group_by(Samples)
dimen <- annot_size
}
if (annot == "asterisks"){
stat <- .trouvelot_stat(x, method = method, group = FALSE, alpha = alpha)
stat_ctr <- stat[stat$group1 == y$Samples[1], ]
stat_l <- ifelse(as.numeric(as.matrix(stat_ctr[, 3:6])) < alpha, "*", "")
ll <- split(stat_l, rep(1:4, each = length(unique(y$Samples)) - 1))
d <- NULL
for (i in seq_along(ll)){
d <- append(d, c("", ll[[i]]))
}
final <- final %>%
mutate(annot = d) %>%
group_by(Samples)
dimen <- annot_size
}
if (annot == "letters"){
stat <- .trouvelot_stat(x, method = method, group = TRUE, alpha = alpha)
d <- as.vector(as.matrix(stat[,2:5]))
final <- final %>%
mutate(annot = d) %>%
group_by(Samples)
dimen <- annot_size
}
g <- ggplot(data = final, aes(x = features, y = means, fill = Samples))
dodge <- position_dodge(width=0.9)
a1 <- g + geom_col(position = dodge) + theme(axis.text.x = element_text(angle = 90, vjust = .5, hjust = 1)) +
geom_errorbar(aes(ymin = means - se, ymax = means + se), width = .1, position = dodge) +
theme_bw() +
theme(plot.title = element_text(size = 19),
panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
legend.position = legend) +
labs(title = main,
# subtitle = "Grid method",
x = "",
y = "root colonization [%]") +
geom_text(aes( label = annot, y = (means + se)), vjust = -0.5, position = dodge,
show.legend = FALSE, size = dimen) +
scale_y_continuous(limits = c(-0.5, 110),
breaks = seq(0, 110, 20))+
scale_fill_manual(values = cbPalette,
breaks = levels(factor(final$Samples,
levels = unique(x$Samples))),
name = "")
class(a1) <- c("am_plot", class(a1))
return(a1)
}
#' @export
am_boxplot.trouvelot <- function(x, cbPalette = c("#999999", "#E69F00", "#56B4E9",
"#009E73", "#F0E442", "#0072B2",
"#D55E00", "#CC79A7"),
alpha = 0.05,
annot = c("none", "asterisks", "letters"),
annot_size = 5,
method = c("none","holm","hommel", "hochberg",
"bonferroni", "BH", "BY", "fdr"),
legend = c("right", "left", "top", "bottom"),
main = "Trouvelot method", ...){
A <- Abundance <- Colonization <- M <- M1 <- a <- feature <- features <- final_a <- m <- NULL
mA <- n_myc <- nn <- num <- perc <- Replicates <- Samples <- Scoring <- tmpa <- tot <- tot2 <- value <- Var1 <- NULL
values <- NULL
alpha <- alpha
annot <- match.arg(annot)
method <- match.arg(method)
legend <- match.arg(legend)
# Create summary table
y <- trouvelot_summary(x)
final <- y %>%
gather(features, values, -Samples, -Replicates) %>%
ungroup %>%
mutate(features = factor(features, levels = c("F", "M", "a", "A")),
Samples = factor(Samples, levels = unique(x$Samples))) %>%
arrange(features, Samples)
# Add annotations
if (annot == "none"){
tmp <- expand.grid(unique(final$features), unique(final$Samples)) %>%
arrange(Var1) %>%
mutate(annot = "")
an <- final %>%
left_join(tmp, by = c("features" = "Var1", "Samples" = "Var2")) %>%
group_by(Samples, features) %>%
dplyr::filter(values == max(values)) %>%
arrange(features, Samples) %>%
dplyr::top_n(1, Replicates)
dimen <- annot_size
}
if (annot == "asterisks"){
stat <- .trouvelot_stat(x, method = method, group = FALSE, alpha = alpha)
stat_ctr <- stat[stat$group1 == y$Samples[1], ]
stat_l <- ifelse(as.numeric(as.matrix(stat_ctr[, 3:6])) < alpha, "*", "")
ll <- split(stat_l, rep(1:4, each = length(unique(y$Samples)) - 1))
d <- NULL
for (i in seq_along(ll)){
d <- append(d, c("", ll[[i]]))
}
tmp <- expand.grid(unique(final$features), unique(final$Samples)) %>%
arrange(Var1) %>%
mutate(annot = d)
an <- final %>%
left_join(tmp, by = c("features" = "Var1", "Samples" = "Var2")) %>%
group_by(Samples, features) %>%
dplyr::filter(values == max(values)) %>%
arrange(features, Samples) %>%
dplyr::top_n(1, Replicates)
dimen <- annot_size
}
if (annot == "letters"){
stat <- .trouvelot_stat(x, method = method, group = TRUE, alpha = alpha)
d <- as.vector(as.matrix(stat[,2:5]))
tmp <- expand.grid(unique(final$features), unique(final$Samples)) %>%
arrange(Var1) %>%
mutate(annot = d)
an <- final %>%
left_join(tmp, by = c("features" = "Var1", "Samples" = "Var2")) %>%
group_by(Samples, features) %>%
dplyr::filter(values == max(values)) %>%
arrange(features, Samples) %>%
dplyr::top_n(1, Replicates)
dimen <- annot_size
}
g <- ggplot(data = final, aes(x = features,
y = values, color = Samples))
dodge <- position_dodge(width=0.75)
a2 <- g +
geom_boxplot() +
theme_bw() +
theme(plot.title = element_text(size = 19),
panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
legend.position = legend) +
geom_vline(xintercept = seq(1.5, length(unique(an$features))-0.5, 1),
colour = "lightgrey") +
labs(title = main,
# subtitle = "Grid method",
x = "",
y = "root colonization [%]") +
geom_text(data = an, aes(x = features, label = annot, y = values), vjust = -0.8,
position = dodge, show.legend = FALSE, size = dimen) +
scale_y_continuous(limits = c(-0.5, 105),
breaks = seq(0, 105, 20))+
scale_colour_manual(values = cbPalette,
breaks = levels(factor(final$Samples,
levels = unique(x$Samples))),
name = "")
class(a2) <- c("am_plot", class(a2))
return(a2)
}
#' @export
am_dotplot.trouvelot <- function(x, cbPalette = c("#999999", "#E69F00", "#56B4E9",
"#009E73", "#F0E442", "#0072B2",
"#D55E00", "#CC79A7"),
alpha = 0.05,
annot = c("none", "asterisks", "letters"),
annot_size = 5,
method = c("none","holm","hommel", "hochberg",
"bonferroni", "BH", "BY", "fdr"),
legend = c("right", "left", "top", "bottom"),
main = "Trouvelot method", ...){
A <- Abundance <- Colonization <- M <- M1 <- a <- feature <- features <- final_a <- m <- NULL
mA <- n_myc <- nn <- num <- perc <- Replicates <- Samples <- Scoring <- tmpa <- tot <- tot2 <- value <- Var1 <- NULL
values <- NULL
alpha <- alpha
annot <- match.arg(annot)
method <- match.arg(method)
legend <- match.arg(legend)
# Create summary table
y <- trouvelot_summary(x)
final <- y %>%
gather(features, values, -Samples, -Replicates) %>%
ungroup %>%
mutate(features = factor(features, levels = c("F", "M", "a", "A")),
Samples = factor(Samples, levels = unique(x$Samples))) %>%
arrange(features, Samples)
# Add annotations
if (annot == "none"){
tmp <- expand.grid(unique(final$features), unique(final$Samples)) %>%
arrange(Var1) %>%
mutate(annot = "")
an <- final %>%
left_join(tmp, by = c("features" = "Var1", "Samples" = "Var2")) %>%
group_by(Samples, features) %>%
dplyr::filter(values == max(values)) %>%
arrange(features, Samples) %>%
dplyr::top_n(1, Replicates)
dimen <- annot_size
}
if (annot == "asterisks"){
stat <- .trouvelot_stat(x, method = method, group = FALSE, alpha = alpha)
stat_ctr <- stat[stat$group1 == y$Samples[1], ]
stat_l <- ifelse(as.numeric(as.matrix(stat_ctr[, 3:6])) < alpha, "*", "")
ll <- split(stat_l, rep(1:4, each = length(unique(y$Samples)) - 1))
d <- NULL
for (i in seq_along(ll)){
d <- append(d, c("", ll[[i]]))
}
tmp <- expand.grid(unique(final$features), unique(final$Samples)) %>%
arrange(Var1) %>%
mutate(annot = d)
an <- final %>%
left_join(tmp, by = c("features" = "Var1", "Samples" = "Var2")) %>%
group_by(Samples, features) %>%
dplyr::filter(values == max(values)) %>%
arrange(features, Samples) %>%
dplyr::top_n(1, Replicates)
dimen <- annot_size
}
if (annot == "letters"){
stat <- .trouvelot_stat(x, method = method, group = TRUE, alpha = alpha)
d <- as.vector(as.matrix(stat[,2:5]))
tmp <- expand.grid(unique(final$features), unique(final$Samples)) %>%
arrange(Var1) %>%
mutate(annot = d)
an <- final %>%
left_join(tmp, by = c("features" = "Var1", "Samples" = "Var2")) %>%
group_by(Samples, features) %>%
dplyr::filter(values == max(values)) %>%
arrange(features, Samples) %>%
dplyr::top_n(1, Replicates)
dimen <- annot_size
}
g <- ggplot(data = final, aes(x = features,
y = values, color = Samples))
dodge <- position_dodge(width=0.9)
a2 <- g +
geom_point(position = position_jitterdodge(dodge.width = 0.9,
jitter.width = 0.1)) +
theme_bw() +
theme(plot.title = element_text(size = 19),
panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
legend.position = legend) +
geom_vline(xintercept = seq(1.5, length(unique(an$features))-0.5, 1),
colour = "lightgrey") +
labs(title = main,
# subtitle = "Grid method",
x = "",
y = "root colonization [%]") +
geom_text(data = an, aes(label = annot, y = values), vjust = -0.8,
position = dodge, show.legend = FALSE, size = dimen) +
scale_y_continuous(limits = c(-0.5, 105),
breaks = seq(0, 105, 20))+
scale_colour_manual(values = cbPalette,
breaks = levels(factor(final$Samples,
levels = unique(x$Samples))),
name = "")
class(a2) <- c("am_plot", class(a2))
return(a2)
}
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.