R/methods-grid.R
In mchiapello/Ramf: Arbuscular Mycorrhizal colonization calculation
Defines functions
am_dotplot.grid
am_boxplot.grid
am_barplot.grid
am_dotplot2.grid
am_boxplot2.grid
am_barplot2.grid
am_stat.grid
am_summary.grid
#' @export
am_summary.grid <- function(x){
Arbuscules <- Hyphopodia <- IntrHyphae <- Total <- Vesicles <- comp <-. <- NULL
features <- Replicates <- Samples <- values <- num <- n <- num_mean <- NULL
tmp <- grid_summary(x)
final <- tmp %>%
group_by(Samples) %>%
mutate(num = dplyr::n()) %>%
summarise(across(where(is.numeric), list(~ mean(., na.rm = TRUE),
~ sd(., na.rm = TRUE)))) %>%
mutate(across(contains("_sd"), ~(. / sqrt(num_mean)))) %>%
select(-contains("num"))
names(final)[grepl("_sd", names(final))] <- gsub("_sd", "_se",
names(final)[grepl("_sd", names(final))])
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_stat.grid <- function(x, method = c("none","holm","hommel", "hochberg",
"bonferroni", "BH", "BY", "fdr"),
...){
method <- match.arg(method)
stat <- .grid_stat(x, method = method)
return(stat)
}
#' @export
am_barplot2.grid <- 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 = "Gridline intersect method", ...){
Arbuscules <- Hypopodia <- Intr_Hyphae <- Total <- Vesicles <- comp <- final <- NULL
features <- Replicates <- Samples <- values <- n <- num <- means <- se <- NULL
alpha <- alpha
annot <- match.arg(annot)
method <- match.arg(method)
# Create summary table
y <- grid_summary(x)
num <- ncol(y)-2
if (annot == "none"){
d <- rep("", length(unique(y$Samples)) * num)
dimen <- annot_size
}
if (annot == "asterisks"){
stat <- .grid_stat(x, method = method, group = FALSE, alpha = alpha)
stat_ctr <- stat[stat$group1 == y$Samples[1], ]
stat_l <- ifelse(as.numeric(as.matrix(stat_ctr[, 3:ncol(y)])) < alpha, "*", "")
ll <- split(stat_l, rep(1:num, each = length(unique(y$Samples)) - 1))
d <- NULL
for (i in seq_along(ll)){
d <- append(d, c("", ll[[i]]))
}
dimen <- annot_size
}
if (annot == "letters"){
stat <- .grid_stat(x, method = method, group = TRUE, alpha = alpha)
d <- as.vector(as.matrix(stat[,2:ncol(stat)]))
dimen <- annot_size
}
# Change table shape
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("Total", "Hyphopodia",
"IntrHyphae", "Arbuscules",
"Vesicles")),
Samples = factor(Samples, levels = unique(x$Samples))) %>%
arrange(features, Samples) %>%
group_by(Samples)
g <- ggplot(data = final, aes(x = interaction(factor(final$Samples, levels = unique(x$Samples)),
factor(final$features, levels = c("Total", "Hyphopodia",
"IntrHyphae", "Arbuscules", "Vesicles"))),
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(),
legend.margin=margin(10,10,10,0),
legend.box.margin=margin(-10,-10,-10,-10),
panel.grid.minor.x = element_blank(),
legend.position = "none") +
geom_vline(xintercept = seq(length(unique(z$Samples)) + .5,
(length(unique(z$Samples)) + .5) * (num - 1),
length(unique(z$Samples))),
colour = "lightgrey") +
labs(title = main,
color = "",
x = "",
y = "root length colonized [%]") +
annotate("text", x = seq(length(unique(z$Samples)) * .5 + .5,
length(unique(z$Samples)) * num + .5,
length(unique(z$Samples))),
y = 110, label = unique(final$features[order(match(final$features,
factor(c("Total",
"Hyphopodia",
"IntrHyphae",
"Arbuscules",
"Vesicles"),
levels = c("Total",
"Hyphopodia",
"IntrHyphae",
"Arbuscules",
"Vesicles"))))])) +
annotate("text", x = 1:(length(unique(y$Samples)) * num),
y = -Inf, vjust = -0.5, label = d, size = dimen) +
scale_x_discrete(labels = rep(unique(x$Samples), 5)) +
scale_y_continuous(limits = c(-0.5, 110),
breaks = seq(0, 110, 20))+
scale_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.grid <- 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 = "Gridline intersect method", ...){
Arbuscules <- Hypopodia <- Intr_Hyphae <- Total <- Vesicles <- comp <- NULL
features <- Replicates <- Samples <- values <- NULL
alpha <- alpha
annot <- match.arg(annot)
method <- match.arg(method)
# Create summary table
y <- grid_summary(x)
num <- ncol(y)-2
if (annot == "none"){
d <- rep("", length(unique(y$Samples)) * num)
dimen <- annot_size
}
if (annot == "asterisks"){
stat <- .grid_stat(x, method = method, group = FALSE, alpha = alpha)
stat_ctr <- stat[stat$group1 == y$Samples[1], ]
stat_l <- ifelse(as.numeric(as.matrix(stat_ctr[, 3:ncol(y)])) < alpha, "*", "")
ll <- split(stat_l, rep(1:num, each = length(unique(y$Samples)) - 1))
d <- NULL
for (i in seq_along(ll)){
d <- append(d, c("", ll[[i]]))
}
dimen <- annot_size
}
if (annot == "letters"){
stat <- .grid_stat(x, method = method, group = TRUE, alpha = alpha)
d <- as.vector(as.matrix(stat[,2:ncol(stat)]))
dimen <- annot_size
}
# Change table shape
z <- y %>% tidyr::gather(features, values, -Samples, -Replicates) %>%
mutate(features = factor(features, levels = c("Total", "Hyphopodia",
"IntrHyphae", "Arbuscules",
"Vesicles")),
Samples = factor(Samples, levels = unique(x$Samples))) %>%
arrange(features, Samples)
g <- ggplot(data = z,
aes(x = interaction(factor(z$Samples, levels = unique(x$Samples)),
factor(z$features, levels = c("Total", "Hyphopodia",
"IntrHyphae", "Arbuscules", "Vesicles")),
sep = ": "),
y = values, 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(),
legend.margin=margin(10,10,10,0),
legend.box.margin=margin(-10,-10,-10,-10),
panel.grid.minor.x = element_blank()) +
geom_vline(xintercept = seq(length(unique(z$Samples)) + .5,
(length(unique(z$Samples)) + .5) * (num - 1),
length(unique(z$Samples))),
colour = "lightgrey") +
labs(title = main,
color = "",
x = "",
y = "root length colonized [%]") +
annotate("text", x = seq(length(unique(z$Samples)) * .5 + .5,
length(unique(z$Samples)) * num + .5,
length(unique(z$Samples))),
y = 110, label = unique(z$features[order(match(z$features,
factor(c("Total",
"Hyphopodia",
"IntrHyphae",
"Arbuscules",
"Vesicles"),
levels = c("Total",
"Hyphopodia",
"IntrHyphae",
"Arbuscules",
"Vesicles"))))])) +
annotate("text", x = 1:(length(unique(y$Samples)) * num),
y = -Inf, vjust = -0.5, label = d, size = dimen) +
scale_x_discrete(labels = rep(unique(x$Samples), 5)) +
scale_y_continuous(limits = c(-0.5, 110),
breaks = seq(0, 110, 20))+
scale_colour_manual(values = cbPalette,
breaks = levels(factor(z$features,
levels = c("Total", "Hyphopodia",
"IntrHyphae", "Arbuscules", "Vesicles"))),
name = "")
class(a2) <- c("am_plot", class(a2))
return(a2)
}
#' @export
am_dotplot2.grid <- function(x, cbPalette = c("#999999", "#E69F00", "#56B4E9",
"#009E73", "#F0E442", "#0072B2",
"#D55E00", "#CC79A7"),
alpha = 0.05,
annot = c("none", "asterisks", "letters"),
annot_size = 5,
method = c("none","holm","hommel", "hochberg",
"bonferroni", "BH", "BY", "fdr"),
main = "Gridline intersect method", ...){
Arbuscules <- Hypopodia <- Intr_Hyphae <- Total <- Vesicles <- comp <- NULL
features <- Replicates <- Samples <- values <- final <- NULL
alpha <- alpha
annot <- match.arg(annot)
method <- match.arg(method)
# Create summary table
y <- grid_summary(x)
num <- ncol(y)-2
if (annot == "none"){
d <- rep("", length(unique(y$Samples)) * num)
dimen <- annot_size
}
if (annot == "asterisks"){
stat <- .grid_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:ncol(y)])) < alpha, "*", "")
ll <- split(stat_l, rep(1:num, each = length(unique(y$Samples)) - 1))
d <- NULL
for (i in seq_along(ll)){
d <- append(d, c("", ll[[i]]))
}
dimen <- annot_size
}
if (annot == "letters"){
stat <- .grid_stat(x, method = method, group = TRUE, alpha = alpha)
d <- as.vector(as.matrix(stat[,2:ncol(stat)]))
dimen <- annot_size
}
# Change table shape
z <- y %>% tidyr::gather(features, values, -Samples, -Replicates) %>%
mutate(features = factor(features, levels = c("Total", "Hyphopodia",
"IntrHyphae", "Arbuscules",
"Vesicles")),
Samples = factor(Samples, levels = unique(x$Samples))) %>%
arrange(features, Samples)
g <- ggplot(data = z,
aes(x = interaction(factor(z$Samples, levels = unique(x$Samples)),
factor(z$features, levels = c("Total", "Hyphopodia",
"IntrHyphae", "Arbuscules", "Vesicles")),
sep = ": "),
y = values, color = Samples))
a2 <- g +
geom_point(position = position_jitter(width = 0.2)) +
theme_bw() +
theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1),
plot.title = element_text(size = 19),
panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
panel.grid.major.x = element_blank(),
legend.margin=margin(10,10,10,0),
legend.box.margin=margin(-10,-10,-10,-10),
panel.grid.minor.x = element_blank()) +
geom_vline(xintercept = seq(length(unique(z$Samples)) + .5,
(length(unique(z$Samples)) + .5) * (num - 1),
length(unique(z$Samples))),
colour = "lightgrey") +
labs(title = main,
color = "",
x = "",
y = "root length colonized [%]") +
annotate("text", x = seq(length(unique(z$Samples)) * .5 + .5,
length(unique(z$Samples)) * num + .5,
length(unique(z$Samples))),
y = 110, label = unique(z$features[order(match(z$features,
factor(c("Total",
"Hyphopodia",
"IntrHyphae",
"Arbuscules",
"Vesicles"),
levels = c("Total",
"Hyphopodia",
"IntrHyphae",
"Arbuscules",
"Vesicles"))))])) +
annotate("text", x = 1:(length(unique(y$Samples)) * num),
y = -Inf, vjust = -0.5, label = d, size = dimen) +
scale_x_discrete(labels = rep(unique(x$Samples), 5)) +
scale_y_continuous(limits = c(-0.5, 110),
breaks = seq(0, 110, 20))+
scale_colour_manual(values = cbPalette,
breaks = levels(factor(z$features,
levels = c("Total", "Hyphopodia",
"IntrHyphae", "Arbuscules", "Vesicles"))),
name = "")
class(a2) <- c("am_plot", class(a2))
return(a2)
}
###############################################################################
# #' @export
# am_summary.gridTime <- function(x){
# Arbuscules <- Hyphopodia <- IntrHyphae <- Total <- Vesicles <- comp <- . <- NULL
# features <- Replicates <- Samples <- values <- num <- n <- num_mean <- NULL
# y <- x %>%
# group_by(Samples, time, Replicates) %>%
# summarise_if(is.numeric, mean, na.rm = TRUE) %>%
# ungroup
# final <- y %>%
# group_by(Samples, time) %>%
# mutate(num = n()) %>%
# summarise_if(is.numeric, funs(mean, sd), na.rm = TRUE) %>%
# mutate_at(vars(contains("_sd")), funs(. / sqrt(num_mean))) %>%
# select(-contains("num"))
# names(final)[grepl("_sd", names(final))] <- gsub("_sd", "_se",
# names(final)[grepl("_sd", names(final))])
# # final <- final[match(unique(x$Samples), final$Samples), ]
# l <- list(y, final)
# names(l) <- c("Summary per Replicate", "Summary per Sample")
# class(l) <- c("am_summary", "list")
# return(l)
# }
#
# #' @export
# am_stat.gridTime <- function(x, method = c("none","holm","hommel", "hochberg",
# "bonferroni", "BH", "BY", "fdr"),
# ...){
# Samples <- comb <- NULL
# method <- match.arg(method)
# stat <- .grid_statime(x, method = method)
# return(stat)
# }
#
# #' @export
# am_barplot.gridTime <- function(x, cbPalette = c("#999999", "#E69F00", "#56B4E9",
# "#009E73", "#F0E442", "#0072B2",
# "#D55E00", "#CC79A7"),
# alpha = 0.05,
# annot = c("none", "asterisks", "letters"),
# method = c("none","holm","hommel", "hochberg",
# "bonferroni", "BH", "BY", "fdr"),
# main = "Gridline intersect method",
# lab = "days", ...){
# Arbuscules <- Hypopodia <- Intr_Hyphae <- Total <- Vesicles <- comp <- NULL
# features <- Replicates <- Samples <- values <- n <- num <- means <- se <- NULL
# dimen <- math <- sterr <- 0
# alpha <- alpha
# annot <- match.arg(annot)
# method <- match.arg(method)
# # Create summary table
# final <- am_summary(x)[[2]]
# tmp <- final %>%
# select("Samples", "time", contains("_mean")) %>%
# gather(features, means, -Samples, -time) %>%
# separate(features, c("features", "math")) %>% select(-math)
# tmp2 <- final %>%
# select("Samples", "time", contains("_se")) %>%
# gather(features, sterr, -Samples, -time) %>%
# separate(features, c("features", "math")) %>% select(-math)
# final <- inner_join(tmp, tmp2, by = c("Samples", "time", "features")) %>%
# mutate(group = paste(Samples, features, time, sep = "_"))
# final <- final[order(match(final$features, c("Total", "Hyphopodia", "IntrHyphae",
# "Arbuscules", "Vesicles")),
# final$time,
# match(final$Samples,unique(x$Samples ))), ]
# final$order <- 1:nrow(final)
# num <- ncol(x)-3
# if (annot == "none"){
# d <- rep("", nrow(final))
# }
# if (annot == "asterisks"){
# stop("Asterisks do not work with an object of class gridTime")
# }
# if (annot == "letters"){
# stat <- .grid_statime(x, method = method, group = TRUE, alpha = alpha)
# stat <- stat %>% separate(sample, c("sample", "time"), "_")
# stat <- stat[order(stat$time, match(stat$sample, unique(x$Samples))), ]
# d <- as.vector(as.matrix(stat[,3:ncol(stat)]))
# dimen <- 3
# }
# # Change table shape
# # if (annot == "none"){
# g <- ggplot(data = final, aes(x = as.factor(order), 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 - sterr, ymax = means + sterr), 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)) + .5) *
# ((length(unique(final$features)) *
# length(unique(final$time))) - 1)) -1,
# length(unique(final$Samples))),
# colour = "lightgrey") +
# labs(title = main,
# # subtitle = "Grid method",
# x = "",
# y = "root length colonized [%]") +
# scale_x_discrete(labels = rep(unique(final$Samples),
# length(unique(final$time)) *
# length(unique(final$features)))) +
# # scale_x_continuous(breaks = 1:nrow(final), labels = rep(unique(final$Samples),
# # ((length(unique(final$features)) *
# # length(unique(final$Samples)))))) +
# annotate("text", x = seq(length(unique(final$Samples)) * .5 + .5,
# (length(unique(final$Samples)) *
# length(unique(final$features)) *
# length(unique(final$time)) + .5),
# length(unique(final$Samples))),
# y = 110, label = rep(unique(final$features),
# each = length(unique(final$time)))) +
# annotate("text", x = seq(length(unique(final$Samples)) * .5 + .5,
# (length(unique(final$Samples)) *
# length(unique(final$features)) *
# length(unique(final$time)) + .5),
# length(unique(final$Samples))),
# y = 106.5, label = paste0(rep(unique(final$time),
# length(unique(final$features))),
# " ", lab), size = 3) +
# scale_y_continuous(limits = c(-0.5, 110),
# breaks = seq(0, 110, 20)) +
# scale_fill_manual(values = cbPalette,
# breaks = levels(factor(final$Samples,
# levels = unique(x$Samples)))) +
# annotate("text", x = 1:nrow(final),
# y = -Inf, vjust = -0.5, label = d, size = dimen)
# class(a1) <- c("am_plot", class(a1))
# return(a1)
# }
#
# #' @export
# am_boxplot.gridTime <- function(x, cbPalette = c("#999999", "#E69F00", "#56B4E9",
# "#009E73", "#F0E442", "#0072B2",
# "#D55E00", "#CC79A7"),
# alpha = 0.05,
# annot = c("none", "asterisks", "letters"),
# method = c("none","holm","hommel", "hochberg",
# "bonferroni", "BH", "BY", "fdr"),
# main = "Gridline intersect method",
# lab = "days", ...){
# Arbuscules <- Hypopodia <- Intr_Hyphae <- Total <- Vesicles <- comp <- NULL
# features <- Replicates <- Samples <- values <- NULL
# dimen <- 0
# alpha <- alpha
# annot <- match.arg(annot)
# method <- match.arg(method)
# # Create summary table
# final <- am_summary(x)[[1]]
# num <- ncol(x)-3
# if (annot == "none"){
# d <- rep("", length(table(paste(final$Samples, final$time))) * num)
# }
# if (annot == "asterisks"){
# stop("Asterisks do not work with an object of class gridTime")
# }
# if (annot == "letters"){
# stat <- .grid_statime(x, method = method, group = TRUE, alpha = alpha)
# stat <- stat %>% separate(sample, c("sample", "time"), "_")
# stat <- stat[order(stat$time, match(stat$sample, unique(x$Samples))), ]
# d <- as.vector(as.matrix(stat[,3:ncol(stat)]))
# dimen <- 3
# }
# # Change table shape
# z <- final %>% tidyr::gather(features, values, -Samples, -time, -Replicates)
# z$group <- paste(z$Samples, z$time, z$features, sep = "_")
# z <- z[order(match(z$features, c("Total", "Hyphopodia", "IntrHyphae",
# "Arbuscules", "Vesicles")),
# z$time,
# match(z$Samples,unique(x$Samples ))), ]
# z$order <- rep(1:length(table(z$group)), table(z$group))
# g <- ggplot(data = z,
# aes(x = factor(z$group, levels=unique(z$group)),
# y = values, color = Samples))
# a2 <- g +
# geom_boxplot() +
# theme_bw() +
# theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1),
# plot.title = element_text(size = 19),
# panel.grid.major.y = element_blank(),
# panel.grid.minor.y = element_blank(),
# panel.grid.major.x = element_blank(),
# panel.grid.minor.x = element_blank(),
# legend.position = "none") +
# geom_vline(xintercept = seq(length(unique(z$Samples)) + .5,
# length(unique(z$features)) *
# length(unique(z$Samples)) *
# length(unique(z$time)),
# length(unique(z$Samples))),
# colour = "lightgrey") +
# labs(title = main,
# # subtitle = "Grid method",
# x = "",
# y = "root length colonized [%]") +
# scale_x_discrete(labels = rep(unique(z$Samples),
# ((length(unique(z$features)) *
# length(unique(z$Samples)))))) +
# annotate("text", x = seq(length(unique(z$Samples)) * .5 + .5,
# (length(unique(z$Samples)) *
# length(unique(z$features)) *
# length(unique(z$time)) + .5),
# length(unique(z$Samples))),
# y = 110, label = rep(unique(z$features),
# each = length(unique(z$time)))) +
# annotate("text", x = seq(length(unique(z$Samples)) * .5 + .5,
# (length(unique(z$Samples)) *
# length(unique(z$features)) *
# length(unique(z$time)) + .5),
# length(unique(z$Samples))),
# y = 106.5, label = paste0(rep(unique(z$time),
# length(unique(z$features))),
# " ", lab)) +
# scale_y_continuous(limits = c(-0.5, 110),
# breaks = seq(0, 110, 20)) +
# scale_colour_manual(values = cbPalette,
# breaks = levels(factor(z$Samples,
# levels = unique(x$Samples)))) +
# annotate("text", x = 1:length(table(z$group)),
# y = -Inf, vjust = -0.5, label = d, size = dimen)
# class(a2) <- c("am_plot", class(a2))
# return(a2)
# }
#
# #' @export
# am_dotplot.gridTime <- function(x, cbPalette = c("#999999", "#E69F00", "#56B4E9",
# "#009E73", "#F0E442", "#0072B2",
# "#D55E00", "#CC79A7"),
# alpha = 0.05,
# annot = c("none", "asterisks", "letters"),
# method = c("none","holm","hommel", "hochberg",
# "bonferroni", "BH", "BY", "fdr"),
# main = "Gridline intersect method",
# lab = "days", ...){
# Arbuscules <- Hypopodia <- Intr_Hyphae <- Total <- Vesicles <- comp <- NULL
# features <- Replicates <- Samples <- values <- NULL
# dimen <- 0
# alpha <- alpha
# annot <- match.arg(annot)
# method <- match.arg(method)
# # Create summary table
# final <- am_summary(x)[[1]]
# num <- ncol(x)-3
# if (annot == "none"){
# d <- rep("", length(table(paste(final$Samples, final$time))) * num)
# }
# if (annot == "asterisks"){
# stop("Asterisks do not work with an object of class gridTime")
# }
# if (annot == "letters"){
# stat <- .grid_statime(x, method = method, group = TRUE, alpha = alpha)
# stat <- stat %>% separate(sample, c("sample", "time"), "_")
# stat <- stat[order(stat$time, match(stat$sample, unique(x$Samples))), ]
# d <- as.vector(as.matrix(stat[,3:ncol(stat)]))
# dimen <- 3
# }
# # Change table shape
# z <- final %>% tidyr::gather(features, values, -Samples, -time, -Replicates)
# z$group <- paste(z$Samples, z$time, z$features, sep = "_")
# # Order
# z <- z[order(match(z$features, c("Total", "Hyphopodia", "IntrHyphae",
# "Arbuscules", "Vesicles")),
# z$time,
# match(z$Samples,unique(x$Samples ))), ]
# z$order <- rep(1:length(table(z$group)), table(z$group))
# # Plot
# g <- ggplot(data = z,
# aes(x = factor(z$group, levels=unique(z$group)),
# y = values, color = Samples))
# a2 <- g +
# geom_jitter() +
# 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(z$Samples)) + .5,
# length(unique(z$features)) *
# length(unique(z$Samples)) *
# length(unique(z$time)),
# length(unique(z$Samples))),
# colour = "lightgrey") +
# labs(title = main,
# x = "",
# y = "root length colonized [%]") +
# scale_x_discrete(labels = rep(unique(z$Samples),
# ((length(unique(z$features)) *
# length(unique(z$Samples)))))) +
# annotate("text", x = seq(length(unique(z$Samples)) * .5 + .5,
# (length(unique(z$Samples)) *
# length(unique(z$features)) *
# length(unique(z$time)) + .5),
# length(unique(z$Samples))),
# y = 110, label = rep(unique(z$features),
# each = length(unique(z$time)))) +
# annotate("text", x = seq(length(unique(z$Samples)) * .5 + .5,
# (length(unique(z$Samples)) *
# length(unique(z$features)) *
# length(unique(z$time)) + .5),
# length(unique(z$Samples))),
# y = 106.5, label = paste0(rep(unique(z$time),
# length(unique(z$features))),
# " ", lab), size = 3) +
# scale_y_continuous(limits = c(-0.5, 110),
# breaks = seq(0, 110, 20)) +
# scale_colour_manual(values = cbPalette,
# breaks = levels(factor(z$Samples,
# levels = unique(x$Samples)))) +
# annotate("text", x = 1:length(table(z$group)),
# y = -Inf, vjust = -0.5, label = d, size = dimen)
# class(a2) <- c("am_plot", class(a2))
# return(a2)
# }
###############################################################################
#' @export
am_barplot.grid <- function(x, cbPalette = c("#999999", "#E69F00", "#56B4E9",
"#009E73", "#F0E442", "#0072B2",
"#D55E00", "#CC79A7"),
alpha = 0.05,
annot = c("none", "asterisks", "letters"),
annot_size = 5,
method = c("none","holm","hommel", "hochberg",
"bonferroni", "BH", "BY", "fdr"),
legend = c("right", "left", "top", "bottom"),
main = "Gridline intersect method", ...){
Arbuscules <- Hypopodia <- Intr_Hyphae <- Total <- Vesicles <- comp <- NULL
features <- Replicates <- Samples <- values <- n <- num <- means <- se <- NULL
alpha <- alpha
annot <- match.arg(annot)
method <- match.arg(method)
legend <- match.arg(legend)
# Create summary table
y <- grid_summary(x)
num <- ncol(y)-2
# Change table shape
z <- y %>% tidyr::gather(features, values, -Samples, -Replicates)
final <- z %>% group_by(Samples, features) %>%
mutate(num = dplyr::n()) %>%
summarize(means = mean(values, na.rm = TRUE),
se = sd(values, na.rm = TRUE) / sqrt(mean(num, na.rm = TRUE))) %>%
ungroup %>%
mutate(features = factor(features, levels = c("Total", "Hyphopodia",
"IntrHyphae", "Arbuscules",
"Vesicles")),
Samples = factor(Samples, levels = unique(x$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 <- .grid_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:ncol(y)])) < alpha, "*", "")
ll <- split(stat_l, rep(1:num, each = length(unique(y$Samples)) - 1))
d <- NULL
for (i in seq_along(ll)){
d <- append(d, c("", ll[[i]]))
}
final <- final %>%
mutate(annot = d) %>%
group_by(Samples)
dimen <- annot_size
}
if (annot == "letters"){
stat <- .grid_stat(x, method = method, group = TRUE, alpha = alpha)
d <- as.vector(as.matrix(stat[,2:ncol(stat)]))
final <- final %>%
mutate(annot = d) %>%
group_by(Samples)
dimen <- annot_size
}
g <- ggplot(data = final, aes(x = features,
y = means, fill = Samples))
dodge <- position_dodge(width=0.9)
a1 <- g + geom_col(position = dodge) + theme(axis.text.x = element_text(angle = 90, vjust = .5, hjust = 1)) +
geom_errorbar(aes(ymin = means - se, ymax = means + se), width = .1, position = dodge) +
theme_bw() +
theme(plot.title = element_text(size = 19),
panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
panel.grid.major.x = element_blank(),
legend.margin=margin(10,10,10,0),
legend.box.margin=margin(-10,-10,-10,-10),
panel.grid.minor.x = element_blank(),
legend.position = legend) +
labs(title = main,
fill = "",
x = "",
y = "root length colonized [%]") +
geom_text(aes( label = annot, y = (means + se)), vjust = -0.5, position = dodge,
show.legend = FALSE, size = dimen) +
scale_y_continuous(limits = c(-0.5, 110),
breaks = seq(0, 110, 20))+
scale_fill_manual(values = cbPalette,
breaks = levels(factor(final$Samples,
levels = unique(x$Samples))),
name = "")
class(a1) <- c("am_plot", class(a1))
return(a1)
}
#' @export
am_boxplot.grid <- function(x, cbPalette = c("#999999", "#E69F00", "#56B4E9",
"#009E73", "#F0E442", "#0072B2",
"#D55E00", "#CC79A7"),
alpha = 0.05,
annot = c("none", "asterisks", "letters"),
annot_size = 5,
method = c("none","holm","hommel", "hochberg",
"bonferroni", "BH", "BY", "fdr"),
legend = c("right", "left", "top", "bottom"),
main = "Gridline intersect method", ...){
Arbuscules <- Hypopodia <- Intr_Hyphae <- Total <- Vesicles <- comp <- NULL
features <- Replicates <- Samples <- values <- n <- num <- Var1 <- NULL
alpha <- alpha
annot <- match.arg(annot)
method <- match.arg(method)
legend <- match.arg(legend)
# Create summary table
y <- grid_summary(x)
num <- ncol(y)-2
# Change table shape
z <- y %>% tidyr::gather(features, values, -Samples, -Replicates) %>%
mutate(features = factor(features, levels = c("Total", "Hyphopodia",
"IntrHyphae", "Arbuscules",
"Vesicles")),
Samples = factor(Samples, levels = unique(x$Samples))) %>%
arrange(features, Samples)
# Add annotations
if (annot == "none"){
tmp <- expand.grid(unique(z$features), unique(z$Samples)) %>%
arrange(Var1) %>%
mutate(annot = "")
an <- z %>%
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 <- .grid_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:ncol(y)])) < alpha, "*", "")
ll <- split(stat_l, rep(1:num, each = length(unique(y$Samples)) - 1))
d <- NULL
for (i in seq_along(ll)){
d <- append(d, c("", ll[[i]]))
}
tmp <- expand.grid(unique(z$features), unique(z$Samples)) %>%
arrange(Var1) %>%
mutate(annot = d)
an <- z %>%
left_join(tmp, by = c("features" = "Var1", "Samples" = "Var2")) %>%
group_by(Samples, features) %>%
dplyr::filter(values == max(values)) %>%
arrange(features, Samples) %>%
dplyr::top_n(1, Replicates)
dimen <- annot_size
}
if (annot == "letters"){
stat <- .grid_stat(x, method = method, group = TRUE, alpha = alpha)
d <- as.vector(as.matrix(stat[,2:ncol(stat)]))
tmp <- expand.grid(unique(z$features), unique(z$Samples)) %>%
arrange(Var1) %>%
mutate(annot = d)
an <- z %>%
left_join(tmp, by = c("features" = "Var1", "Samples" = "Var2")) %>%
group_by(Samples, features) %>%
dplyr::filter(values == max(values)) %>%
arrange(features, Samples) %>%
dplyr::top_n(1, Replicates)
dimen <- annot_size
}
g <- ggplot(data = z,
aes(x = features,
y = values,
colour = Samples))
dodge <- position_dodge(width=0.75)
a2 <- g +
geom_boxplot() +
theme_bw() +
theme(plot.title = element_text(size = 19),
panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
panel.grid.major.x = element_blank(),
legend.margin=margin(10,10,10,0),
legend.box.margin=margin(-10,-10,-10,-10),
panel.grid.minor.x = element_blank(),
legend.position = legend) +
geom_vline(xintercept = seq(1.5, length(unique(an$features))-0.5, 1),
colour = "lightgrey") +
labs(title = main,
color = "",
x = "",
y = "root length colonized [%]") +
scale_y_continuous(limits = c(-0.5, 105),
breaks = seq(0, 105, 20))+
scale_colour_manual(values = cbPalette,
breaks = levels(factor(z$Samples,
levels = unique(x$Samples))),
name = "") +
geom_text(data = an, aes(x = features, label = annot, y = values), vjust = -0.8,
position = dodge, show.legend = FALSE, size = dimen)
class(a2) <- c("am_plot", class(a2))
return(a2)
}
#' @export
am_dotplot.grid <- 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 = "Gridline intersect method", ...){
Arbuscules <- Hypopodia <- Intr_Hyphae <- Total <- Vesicles <- comp <- NULL
features <- Replicates <- Samples <- values <- Var1 <- NULL
alpha <- alpha
annot <- match.arg(annot)
method <- match.arg(method)
legend <- match.arg(legend)
# Create summary table
y <- grid_summary(x)
num <- ncol(y)-2
# Change table shape
z <- y %>% tidyr::gather(features, values, -Samples, -Replicates) %>%
mutate(features = factor(features, levels = c("Total", "Hyphopodia",
"IntrHyphae", "Arbuscules",
"Vesicles")),
Samples = factor(Samples, levels = unique(x$Samples))) %>%
arrange(features, Samples)
# Add annotations
if (annot == "none"){
tmp <- expand.grid(unique(z$features), unique(z$Samples)) %>%
arrange(Var1) %>%
mutate(annot = "")
an <- z %>%
left_join(tmp, by = c("features" = "Var1", "Samples" = "Var2")) %>%
group_by(Samples, features) %>%
dplyr::filter(values == max(values)) %>%
arrange(features, Samples) %>%
dplyr::top_n(1, Replicates)
dimen <- annot_size
}
if (annot == "asterisks"){
stat <- .grid_stat(x, method = method, group = FALSE, alpha = alpha)
stat_ctr <- stat[stat$group1 == y$Samples[1], ]
stat_l <- ifelse(as.numeric(as.matrix(stat_ctr[, 3:ncol(y)])) < alpha, "*", "")
ll <- split(stat_l, rep(1:num, each = length(unique(y$Samples)) - 1))
d <- NULL
for (i in seq_along(ll)){
d <- append(d, c("", ll[[i]]))
}
tmp <- expand.grid(unique(z$features), unique(z$Samples)) %>%
arrange(Var1) %>%
mutate(annot = d)
an <- z %>%
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 <- .grid_stat(x, method = method, group = TRUE, alpha = alpha)
d <- as.vector(as.matrix(stat[,2:ncol(stat)]))
tmp <- expand.grid(unique(z$features), unique(z$Samples)) %>%
arrange(Var1) %>%
mutate(annot = d)
an <- z %>%
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 = z,
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(),
legend.margin=margin(10,10,10,0),
legend.box.margin=margin(-10,-10,-10,-10),
panel.grid.minor.x = element_blank(),
legend.position = legend) +
geom_vline(xintercept = seq(1.5, length(unique(an$features))-0.5, 1),
colour = "lightgrey") +
labs(title = main,
color = "",
x = "",
y = "root length colonized [%]") +
geom_text(data = an, aes(label = annot, y = values), vjust = -0.8,
position = dodge, show.legend = FALSE, size = dimen) +
scale_y_continuous(limits = c(-0.5, 105),
breaks = seq(0, 105, 20))+
scale_colour_manual(values = cbPalette,
breaks = levels(factor(z$Samples,
levels = unique(x$Samples))),
name = "")
class(a2) <- c("am_plot", class(a2))
return(a2)
}
mchiapello/Ramf documentation built on April 9, 2022, 5:07 p.m.
R Package Documentation
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Defines functions am_dotplot.grid am_boxplot.grid am_barplot.grid am_dotplot2.grid am_boxplot2.grid am_barplot2.grid am_stat.grid am_summary.grid
#' @export
am_summary.grid <- function(x){
Arbuscules <- Hyphopodia <- IntrHyphae <- Total <- Vesicles <- comp <-. <- NULL
features <- Replicates <- Samples <- values <- num <- n <- num_mean <- NULL
tmp <- grid_summary(x)
final <- tmp %>%
group_by(Samples) %>%
mutate(num = dplyr::n()) %>%
summarise(across(where(is.numeric), list(~ mean(., na.rm = TRUE),
~ sd(., na.rm = TRUE)))) %>%
mutate(across(contains("_sd"), ~(. / sqrt(num_mean)))) %>%
select(-contains("num"))
names(final)[grepl("_sd", names(final))] <- gsub("_sd", "_se",
names(final)[grepl("_sd", names(final))])
final <- final[match(unique(x$Samples), final$Samples), ]
l <- list(tmp, final)
names(l) <- c("Summary per Replicate", "Summary per Sample")
class(l) <- c("am_summary", "list")
return(l)
}
#' @export
am_stat.grid <- function(x, method = c("none","holm","hommel", "hochberg",
"bonferroni", "BH", "BY", "fdr"),
...){
method <- match.arg(method)
stat <- .grid_stat(x, method = method)
return(stat)
}
#' @export
am_barplot2.grid <- function(x, cbPalette = c("#999999", "#E69F00", "#56B4E9",
"#009E73", "#F0E442", "#0072B2",
"#D55E00", "#CC79A7"),
alpha = 0.05,
annot = c("none", "asterisks", "letters"),
annot_size = 5,
method = c("none","holm","hommel", "hochberg",
"bonferroni", "BH", "BY", "fdr"),
main = "Gridline intersect method", ...){
Arbuscules <- Hypopodia <- Intr_Hyphae <- Total <- Vesicles <- comp <- final <- NULL
features <- Replicates <- Samples <- values <- n <- num <- means <- se <- NULL
alpha <- alpha
annot <- match.arg(annot)
method <- match.arg(method)
# Create summary table
y <- grid_summary(x)
num <- ncol(y)-2
if (annot == "none"){
d <- rep("", length(unique(y$Samples)) * num)
dimen <- annot_size
}
if (annot == "asterisks"){
stat <- .grid_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:ncol(y)])) < alpha, "*", "")
ll <- split(stat_l, rep(1:num, each = length(unique(y$Samples)) - 1))
d <- NULL
for (i in seq_along(ll)){
d <- append(d, c("", ll[[i]]))
}
dimen <- annot_size
}
if (annot == "letters"){
stat <- .grid_stat(x, method = method, group = TRUE, alpha = alpha)
d <- as.vector(as.matrix(stat[,2:ncol(stat)]))
dimen <- annot_size
}
# Change table shape
z <- y %>% tidyr::gather(features, values, -Samples, -Replicates)
final <- z %>% group_by(Samples, features) %>%
mutate(num = dplyr::n()) %>%
summarize(means = mean(values, na.rm = TRUE),
se = sd(values, na.rm = TRUE) / sqrt(mean(num, na.rm = TRUE))) %>%
ungroup %>%
mutate(features = factor(features, levels = c("Total", "Hyphopodia",
"IntrHyphae", "Arbuscules",
"Vesicles")),
Samples = factor(Samples, levels = unique(x$Samples))) %>%
arrange(features, Samples) %>%
group_by(Samples)
g <- ggplot(data = final, aes(x = interaction(factor(final$Samples, levels = unique(x$Samples)),
factor(final$features, levels = c("Total", "Hyphopodia",
"IntrHyphae", "Arbuscules", "Vesicles"))),
y = means, fill = Samples))
a1 <- g + geom_col() + theme(axis.text.x = element_text(angle = 90, vjust = .5, hjust = 1)) +
geom_errorbar(aes(ymin = means - se, ymax = means + se), width = .1) +
theme_bw() +
theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1),
plot.title = element_text(size = 19),
panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
panel.grid.major.x = element_blank(),
legend.margin=margin(10,10,10,0),
legend.box.margin=margin(-10,-10,-10,-10),
panel.grid.minor.x = element_blank(),
legend.position = "none") +
geom_vline(xintercept = seq(length(unique(z$Samples)) + .5,
(length(unique(z$Samples)) + .5) * (num - 1),
length(unique(z$Samples))),
colour = "lightgrey") +
labs(title = main,
color = "",
x = "",
y = "root length colonized [%]") +
annotate("text", x = seq(length(unique(z$Samples)) * .5 + .5,
length(unique(z$Samples)) * num + .5,
length(unique(z$Samples))),
y = 110, label = unique(final$features[order(match(final$features,
factor(c("Total",
"Hyphopodia",
"IntrHyphae",
"Arbuscules",
"Vesicles"),
levels = c("Total",
"Hyphopodia",
"IntrHyphae",
"Arbuscules",
"Vesicles"))))])) +
annotate("text", x = 1:(length(unique(y$Samples)) * num),
y = -Inf, vjust = -0.5, label = d, size = dimen) +
scale_x_discrete(labels = rep(unique(x$Samples), 5)) +
scale_y_continuous(limits = c(-0.5, 110),
breaks = seq(0, 110, 20))+
scale_fill_manual(values = cbPalette,
breaks = levels(factor(final$Samples,
levels = unique(x$Samples))),
name = "")
class(a1) <- c("am_plot", class(a1))
return(a1)
}
#' @export
am_boxplot2.grid <- function(x, cbPalette = c("#999999", "#E69F00", "#56B4E9",
"#009E73", "#F0E442", "#0072B2",
"#D55E00", "#CC79A7"),
alpha = 0.05,
annot = c("none", "asterisks", "letters"),
annot_size = 5,
method = c("none","holm","hommel", "hochberg",
"bonferroni", "BH", "BY", "fdr"),
main = "Gridline intersect method", ...){
Arbuscules <- Hypopodia <- Intr_Hyphae <- Total <- Vesicles <- comp <- NULL
features <- Replicates <- Samples <- values <- NULL
alpha <- alpha
annot <- match.arg(annot)
method <- match.arg(method)
# Create summary table
y <- grid_summary(x)
num <- ncol(y)-2
if (annot == "none"){
d <- rep("", length(unique(y$Samples)) * num)
dimen <- annot_size
}
if (annot == "asterisks"){
stat <- .grid_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:ncol(y)])) < alpha, "*", "")
ll <- split(stat_l, rep(1:num, each = length(unique(y$Samples)) - 1))
d <- NULL
for (i in seq_along(ll)){
d <- append(d, c("", ll[[i]]))
}
dimen <- annot_size
}
if (annot == "letters"){
stat <- .grid_stat(x, method = method, group = TRUE, alpha = alpha)
d <- as.vector(as.matrix(stat[,2:ncol(stat)]))
dimen <- annot_size
}
# Change table shape
z <- y %>% tidyr::gather(features, values, -Samples, -Replicates) %>%
mutate(features = factor(features, levels = c("Total", "Hyphopodia",
"IntrHyphae", "Arbuscules",
"Vesicles")),
Samples = factor(Samples, levels = unique(x$Samples))) %>%
arrange(features, Samples)
g <- ggplot(data = z,
aes(x = interaction(factor(z$Samples, levels = unique(x$Samples)),
factor(z$features, levels = c("Total", "Hyphopodia",
"IntrHyphae", "Arbuscules", "Vesicles")),
sep = ": "),
y = values, color = Samples))
a2 <- g +
geom_boxplot() +
theme_bw() +
theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1),
plot.title = element_text(size = 19),
panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
panel.grid.major.x = element_blank(),
legend.margin=margin(10,10,10,0),
legend.box.margin=margin(-10,-10,-10,-10),
panel.grid.minor.x = element_blank()) +
geom_vline(xintercept = seq(length(unique(z$Samples)) + .5,
(length(unique(z$Samples)) + .5) * (num - 1),
length(unique(z$Samples))),
colour = "lightgrey") +
labs(title = main,
color = "",
x = "",
y = "root length colonized [%]") +
annotate("text", x = seq(length(unique(z$Samples)) * .5 + .5,
length(unique(z$Samples)) * num + .5,
length(unique(z$Samples))),
y = 110, label = unique(z$features[order(match(z$features,
factor(c("Total",
"Hyphopodia",
"IntrHyphae",
"Arbuscules",
"Vesicles"),
levels = c("Total",
"Hyphopodia",
"IntrHyphae",
"Arbuscules",
"Vesicles"))))])) +
annotate("text", x = 1:(length(unique(y$Samples)) * num),
y = -Inf, vjust = -0.5, label = d, size = dimen) +
scale_x_discrete(labels = rep(unique(x$Samples), 5)) +
scale_y_continuous(limits = c(-0.5, 110),
breaks = seq(0, 110, 20))+
scale_colour_manual(values = cbPalette,
breaks = levels(factor(z$features,
levels = c("Total", "Hyphopodia",
"IntrHyphae", "Arbuscules", "Vesicles"))),
name = "")
class(a2) <- c("am_plot", class(a2))
return(a2)
}
#' @export
am_dotplot2.grid <- 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 = "Gridline intersect method", ...){
Arbuscules <- Hypopodia <- Intr_Hyphae <- Total <- Vesicles <- comp <- NULL
features <- Replicates <- Samples <- values <- final <- NULL
alpha <- alpha
annot <- match.arg(annot)
method <- match.arg(method)
# Create summary table
y <- grid_summary(x)
num <- ncol(y)-2
if (annot == "none"){
d <- rep("", length(unique(y$Samples)) * num)
dimen <- annot_size
}
if (annot == "asterisks"){
stat <- .grid_stat(x, method = method, group = FALSE, alpha = alpha)
stat_ctr <- stat[stat$group1 == y$Samples[1], ]
stat_l <- ifelse(as.numeric(as.matrix(stat_ctr[, 3:ncol(y)])) < alpha, "*", "")
ll <- split(stat_l, rep(1:num, each = length(unique(y$Samples)) - 1))
d <- NULL
for (i in seq_along(ll)){
d <- append(d, c("", ll[[i]]))
}
dimen <- annot_size
}
if (annot == "letters"){
stat <- .grid_stat(x, method = method, group = TRUE, alpha = alpha)
d <- as.vector(as.matrix(stat[,2:ncol(stat)]))
dimen <- annot_size
}
# Change table shape
z <- y %>% tidyr::gather(features, values, -Samples, -Replicates) %>%
mutate(features = factor(features, levels = c("Total", "Hyphopodia",
"IntrHyphae", "Arbuscules",
"Vesicles")),
Samples = factor(Samples, levels = unique(x$Samples))) %>%
arrange(features, Samples)
g <- ggplot(data = z,
aes(x = interaction(factor(z$Samples, levels = unique(x$Samples)),
factor(z$features, levels = c("Total", "Hyphopodia",
"IntrHyphae", "Arbuscules", "Vesicles")),
sep = ": "),
y = values, color = 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(),
legend.margin=margin(10,10,10,0),
legend.box.margin=margin(-10,-10,-10,-10),
panel.grid.minor.x = element_blank()) +
geom_vline(xintercept = seq(length(unique(z$Samples)) + .5,
(length(unique(z$Samples)) + .5) * (num - 1),
length(unique(z$Samples))),
colour = "lightgrey") +
labs(title = main,
color = "",
x = "",
y = "root length colonized [%]") +
annotate("text", x = seq(length(unique(z$Samples)) * .5 + .5,
length(unique(z$Samples)) * num + .5,
length(unique(z$Samples))),
y = 110, label = unique(z$features[order(match(z$features,
factor(c("Total",
"Hyphopodia",
"IntrHyphae",
"Arbuscules",
"Vesicles"),
levels = c("Total",
"Hyphopodia",
"IntrHyphae",
"Arbuscules",
"Vesicles"))))])) +
annotate("text", x = 1:(length(unique(y$Samples)) * num),
y = -Inf, vjust = -0.5, label = d, size = dimen) +
scale_x_discrete(labels = rep(unique(x$Samples), 5)) +
scale_y_continuous(limits = c(-0.5, 110),
breaks = seq(0, 110, 20))+
scale_colour_manual(values = cbPalette,
breaks = levels(factor(z$features,
levels = c("Total", "Hyphopodia",
"IntrHyphae", "Arbuscules", "Vesicles"))),
name = "")
class(a2) <- c("am_plot", class(a2))
return(a2)
}
###############################################################################
# #' @export
# am_summary.gridTime <- function(x){
# Arbuscules <- Hyphopodia <- IntrHyphae <- Total <- Vesicles <- comp <- . <- NULL
# features <- Replicates <- Samples <- values <- num <- n <- num_mean <- NULL
# y <- x %>%
# group_by(Samples, time, Replicates) %>%
# summarise_if(is.numeric, mean, na.rm = TRUE) %>%
# ungroup
# final <- y %>%
# group_by(Samples, time) %>%
# mutate(num = n()) %>%
# summarise_if(is.numeric, funs(mean, sd), na.rm = TRUE) %>%
# mutate_at(vars(contains("_sd")), funs(. / sqrt(num_mean))) %>%
# select(-contains("num"))
# names(final)[grepl("_sd", names(final))] <- gsub("_sd", "_se",
# names(final)[grepl("_sd", names(final))])
# # final <- final[match(unique(x$Samples), final$Samples), ]
# l <- list(y, final)
# names(l) <- c("Summary per Replicate", "Summary per Sample")
# class(l) <- c("am_summary", "list")
# return(l)
# }
#
# #' @export
# am_stat.gridTime <- function(x, method = c("none","holm","hommel", "hochberg",
# "bonferroni", "BH", "BY", "fdr"),
# ...){
# Samples <- comb <- NULL
# method <- match.arg(method)
# stat <- .grid_statime(x, method = method)
# return(stat)
# }
#
# #' @export
# am_barplot.gridTime <- function(x, cbPalette = c("#999999", "#E69F00", "#56B4E9",
# "#009E73", "#F0E442", "#0072B2",
# "#D55E00", "#CC79A7"),
# alpha = 0.05,
# annot = c("none", "asterisks", "letters"),
# method = c("none","holm","hommel", "hochberg",
# "bonferroni", "BH", "BY", "fdr"),
# main = "Gridline intersect method",
# lab = "days", ...){
# Arbuscules <- Hypopodia <- Intr_Hyphae <- Total <- Vesicles <- comp <- NULL
# features <- Replicates <- Samples <- values <- n <- num <- means <- se <- NULL
# dimen <- math <- sterr <- 0
# alpha <- alpha
# annot <- match.arg(annot)
# method <- match.arg(method)
# # Create summary table
# final <- am_summary(x)[[2]]
# tmp <- final %>%
# select("Samples", "time", contains("_mean")) %>%
# gather(features, means, -Samples, -time) %>%
# separate(features, c("features", "math")) %>% select(-math)
# tmp2 <- final %>%
# select("Samples", "time", contains("_se")) %>%
# gather(features, sterr, -Samples, -time) %>%
# separate(features, c("features", "math")) %>% select(-math)
# final <- inner_join(tmp, tmp2, by = c("Samples", "time", "features")) %>%
# mutate(group = paste(Samples, features, time, sep = "_"))
# final <- final[order(match(final$features, c("Total", "Hyphopodia", "IntrHyphae",
# "Arbuscules", "Vesicles")),
# final$time,
# match(final$Samples,unique(x$Samples ))), ]
# final$order <- 1:nrow(final)
# num <- ncol(x)-3
# if (annot == "none"){
# d <- rep("", nrow(final))
# }
# if (annot == "asterisks"){
# stop("Asterisks do not work with an object of class gridTime")
# }
# if (annot == "letters"){
# stat <- .grid_statime(x, method = method, group = TRUE, alpha = alpha)
# stat <- stat %>% separate(sample, c("sample", "time"), "_")
# stat <- stat[order(stat$time, match(stat$sample, unique(x$Samples))), ]
# d <- as.vector(as.matrix(stat[,3:ncol(stat)]))
# dimen <- 3
# }
# # Change table shape
# # if (annot == "none"){
# g <- ggplot(data = final, aes(x = as.factor(order), y = means, fill = Samples))
# a1 <- g + geom_col() +
# theme(axis.text.x = element_text(angle = 90, vjust = .5, hjust = 1)) +
# geom_errorbar(aes(ymin = means - sterr, ymax = means + sterr), width = .1) +
# theme_bw() +
# theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1),
# plot.title = element_text(size = 19),
# panel.grid.major.y = element_blank(),
# panel.grid.minor.y = element_blank(),
# panel.grid.major.x = element_blank(),
# panel.grid.minor.x = element_blank(),
# legend.position = "none") +
# geom_vline(xintercept = seq(length(unique(final$Samples)) + .5,
# ((length(unique(final$Samples)) + .5) *
# ((length(unique(final$features)) *
# length(unique(final$time))) - 1)) -1,
# length(unique(final$Samples))),
# colour = "lightgrey") +
# labs(title = main,
# # subtitle = "Grid method",
# x = "",
# y = "root length colonized [%]") +
# scale_x_discrete(labels = rep(unique(final$Samples),
# length(unique(final$time)) *
# length(unique(final$features)))) +
# # scale_x_continuous(breaks = 1:nrow(final), labels = rep(unique(final$Samples),
# # ((length(unique(final$features)) *
# # length(unique(final$Samples)))))) +
# annotate("text", x = seq(length(unique(final$Samples)) * .5 + .5,
# (length(unique(final$Samples)) *
# length(unique(final$features)) *
# length(unique(final$time)) + .5),
# length(unique(final$Samples))),
# y = 110, label = rep(unique(final$features),
# each = length(unique(final$time)))) +
# annotate("text", x = seq(length(unique(final$Samples)) * .5 + .5,
# (length(unique(final$Samples)) *
# length(unique(final$features)) *
# length(unique(final$time)) + .5),
# length(unique(final$Samples))),
# y = 106.5, label = paste0(rep(unique(final$time),
# length(unique(final$features))),
# " ", lab), size = 3) +
# 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)))) +
# annotate("text", x = 1:nrow(final),
# y = -Inf, vjust = -0.5, label = d, size = dimen)
# class(a1) <- c("am_plot", class(a1))
# return(a1)
# }
#
# #' @export
# am_boxplot.gridTime <- function(x, cbPalette = c("#999999", "#E69F00", "#56B4E9",
# "#009E73", "#F0E442", "#0072B2",
# "#D55E00", "#CC79A7"),
# alpha = 0.05,
# annot = c("none", "asterisks", "letters"),
# method = c("none","holm","hommel", "hochberg",
# "bonferroni", "BH", "BY", "fdr"),
# main = "Gridline intersect method",
# lab = "days", ...){
# Arbuscules <- Hypopodia <- Intr_Hyphae <- Total <- Vesicles <- comp <- NULL
# features <- Replicates <- Samples <- values <- NULL
# dimen <- 0
# alpha <- alpha
# annot <- match.arg(annot)
# method <- match.arg(method)
# # Create summary table
# final <- am_summary(x)[[1]]
# num <- ncol(x)-3
# if (annot == "none"){
# d <- rep("", length(table(paste(final$Samples, final$time))) * num)
# }
# if (annot == "asterisks"){
# stop("Asterisks do not work with an object of class gridTime")
# }
# if (annot == "letters"){
# stat <- .grid_statime(x, method = method, group = TRUE, alpha = alpha)
# stat <- stat %>% separate(sample, c("sample", "time"), "_")
# stat <- stat[order(stat$time, match(stat$sample, unique(x$Samples))), ]
# d <- as.vector(as.matrix(stat[,3:ncol(stat)]))
# dimen <- 3
# }
# # Change table shape
# z <- final %>% tidyr::gather(features, values, -Samples, -time, -Replicates)
# z$group <- paste(z$Samples, z$time, z$features, sep = "_")
# z <- z[order(match(z$features, c("Total", "Hyphopodia", "IntrHyphae",
# "Arbuscules", "Vesicles")),
# z$time,
# match(z$Samples,unique(x$Samples ))), ]
# z$order <- rep(1:length(table(z$group)), table(z$group))
# g <- ggplot(data = z,
# aes(x = factor(z$group, levels=unique(z$group)),
# y = values, 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(z$Samples)) + .5,
# length(unique(z$features)) *
# length(unique(z$Samples)) *
# length(unique(z$time)),
# length(unique(z$Samples))),
# colour = "lightgrey") +
# labs(title = main,
# # subtitle = "Grid method",
# x = "",
# y = "root length colonized [%]") +
# scale_x_discrete(labels = rep(unique(z$Samples),
# ((length(unique(z$features)) *
# length(unique(z$Samples)))))) +
# annotate("text", x = seq(length(unique(z$Samples)) * .5 + .5,
# (length(unique(z$Samples)) *
# length(unique(z$features)) *
# length(unique(z$time)) + .5),
# length(unique(z$Samples))),
# y = 110, label = rep(unique(z$features),
# each = length(unique(z$time)))) +
# annotate("text", x = seq(length(unique(z$Samples)) * .5 + .5,
# (length(unique(z$Samples)) *
# length(unique(z$features)) *
# length(unique(z$time)) + .5),
# length(unique(z$Samples))),
# y = 106.5, label = paste0(rep(unique(z$time),
# length(unique(z$features))),
# " ", lab)) +
# scale_y_continuous(limits = c(-0.5, 110),
# breaks = seq(0, 110, 20)) +
# scale_colour_manual(values = cbPalette,
# breaks = levels(factor(z$Samples,
# levels = unique(x$Samples)))) +
# annotate("text", x = 1:length(table(z$group)),
# y = -Inf, vjust = -0.5, label = d, size = dimen)
# class(a2) <- c("am_plot", class(a2))
# return(a2)
# }
#
# #' @export
# am_dotplot.gridTime <- function(x, cbPalette = c("#999999", "#E69F00", "#56B4E9",
# "#009E73", "#F0E442", "#0072B2",
# "#D55E00", "#CC79A7"),
# alpha = 0.05,
# annot = c("none", "asterisks", "letters"),
# method = c("none","holm","hommel", "hochberg",
# "bonferroni", "BH", "BY", "fdr"),
# main = "Gridline intersect method",
# lab = "days", ...){
# Arbuscules <- Hypopodia <- Intr_Hyphae <- Total <- Vesicles <- comp <- NULL
# features <- Replicates <- Samples <- values <- NULL
# dimen <- 0
# alpha <- alpha
# annot <- match.arg(annot)
# method <- match.arg(method)
# # Create summary table
# final <- am_summary(x)[[1]]
# num <- ncol(x)-3
# if (annot == "none"){
# d <- rep("", length(table(paste(final$Samples, final$time))) * num)
# }
# if (annot == "asterisks"){
# stop("Asterisks do not work with an object of class gridTime")
# }
# if (annot == "letters"){
# stat <- .grid_statime(x, method = method, group = TRUE, alpha = alpha)
# stat <- stat %>% separate(sample, c("sample", "time"), "_")
# stat <- stat[order(stat$time, match(stat$sample, unique(x$Samples))), ]
# d <- as.vector(as.matrix(stat[,3:ncol(stat)]))
# dimen <- 3
# }
# # Change table shape
# z <- final %>% tidyr::gather(features, values, -Samples, -time, -Replicates)
# z$group <- paste(z$Samples, z$time, z$features, sep = "_")
# # Order
# z <- z[order(match(z$features, c("Total", "Hyphopodia", "IntrHyphae",
# "Arbuscules", "Vesicles")),
# z$time,
# match(z$Samples,unique(x$Samples ))), ]
# z$order <- rep(1:length(table(z$group)), table(z$group))
# # Plot
# g <- ggplot(data = z,
# aes(x = factor(z$group, levels=unique(z$group)),
# y = values, color = Samples))
# a2 <- g +
# geom_jitter() +
# theme_bw() +
# theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1),
# plot.title = element_text(size = 19),
# panel.grid.major.y = element_blank(),
# panel.grid.minor.y = element_blank(),
# panel.grid.major.x = element_blank(),
# panel.grid.minor.x = element_blank(),
# legend.position = "none") +
# geom_vline(xintercept = seq(length(unique(z$Samples)) + .5,
# length(unique(z$features)) *
# length(unique(z$Samples)) *
# length(unique(z$time)),
# length(unique(z$Samples))),
# colour = "lightgrey") +
# labs(title = main,
# x = "",
# y = "root length colonized [%]") +
# scale_x_discrete(labels = rep(unique(z$Samples),
# ((length(unique(z$features)) *
# length(unique(z$Samples)))))) +
# annotate("text", x = seq(length(unique(z$Samples)) * .5 + .5,
# (length(unique(z$Samples)) *
# length(unique(z$features)) *
# length(unique(z$time)) + .5),
# length(unique(z$Samples))),
# y = 110, label = rep(unique(z$features),
# each = length(unique(z$time)))) +
# annotate("text", x = seq(length(unique(z$Samples)) * .5 + .5,
# (length(unique(z$Samples)) *
# length(unique(z$features)) *
# length(unique(z$time)) + .5),
# length(unique(z$Samples))),
# y = 106.5, label = paste0(rep(unique(z$time),
# length(unique(z$features))),
# " ", lab), size = 3) +
# scale_y_continuous(limits = c(-0.5, 110),
# breaks = seq(0, 110, 20)) +
# scale_colour_manual(values = cbPalette,
# breaks = levels(factor(z$Samples,
# levels = unique(x$Samples)))) +
# annotate("text", x = 1:length(table(z$group)),
# y = -Inf, vjust = -0.5, label = d, size = dimen)
# class(a2) <- c("am_plot", class(a2))
# return(a2)
# }
###############################################################################
#' @export
am_barplot.grid <- 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 = "Gridline intersect method", ...){
Arbuscules <- Hypopodia <- Intr_Hyphae <- Total <- Vesicles <- comp <- NULL
features <- Replicates <- Samples <- values <- n <- num <- means <- se <- NULL
alpha <- alpha
annot <- match.arg(annot)
method <- match.arg(method)
legend <- match.arg(legend)
# Create summary table
y <- grid_summary(x)
num <- ncol(y)-2
# Change table shape
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("Total", "Hyphopodia",
"IntrHyphae", "Arbuscules",
"Vesicles")),
Samples = factor(Samples, levels = unique(x$Samples))) %>%
arrange(features, Samples)
# Add annotations
if (annot == "none"){
final <- final %>%
mutate(annot = rep("", nrow(final))) %>%
group_by(Samples)
dimen <- annot_size
}
if (annot == "asterisks"){
stat <- .grid_stat(x, method = method, group = FALSE, alpha = alpha)
stat_ctr <- stat[stat$group1 == y$Samples[1], ]
stat_l <- ifelse(as.numeric(as.matrix(stat_ctr[, 3:ncol(y)])) < alpha, "*", "")
ll <- split(stat_l, rep(1:num, each = length(unique(y$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 <- .grid_stat(x, method = method, group = TRUE, alpha = alpha)
d <- as.vector(as.matrix(stat[,2:ncol(stat)]))
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(),
legend.margin=margin(10,10,10,0),
legend.box.margin=margin(-10,-10,-10,-10),
panel.grid.minor.x = element_blank(),
legend.position = legend) +
labs(title = main,
fill = "",
x = "",
y = "root length colonized [%]") +
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.grid <- 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 = "Gridline intersect method", ...){
Arbuscules <- Hypopodia <- Intr_Hyphae <- Total <- Vesicles <- comp <- NULL
features <- Replicates <- Samples <- values <- n <- num <- Var1 <- NULL
alpha <- alpha
annot <- match.arg(annot)
method <- match.arg(method)
legend <- match.arg(legend)
# Create summary table
y <- grid_summary(x)
num <- ncol(y)-2
# Change table shape
z <- y %>% tidyr::gather(features, values, -Samples, -Replicates) %>%
mutate(features = factor(features, levels = c("Total", "Hyphopodia",
"IntrHyphae", "Arbuscules",
"Vesicles")),
Samples = factor(Samples, levels = unique(x$Samples))) %>%
arrange(features, Samples)
# Add annotations
if (annot == "none"){
tmp <- expand.grid(unique(z$features), unique(z$Samples)) %>%
arrange(Var1) %>%
mutate(annot = "")
an <- z %>%
left_join(tmp, by = c("features" = "Var1", "Samples" = "Var2")) %>%
group_by(Samples, features) %>%
dplyr::filter(values == max(values)) %>%
arrange(features, Samples) %>%
dplyr::top_n(1, Replicates)
dimen <- annot_size
}
if (annot == "asterisks"){
stat <- .grid_stat(x, method = method, group = FALSE, alpha = alpha)
stat_ctr <- stat[stat$group1 == y$Samples[1], ]
stat_l <- ifelse(as.numeric(as.matrix(stat_ctr[, 3:ncol(y)])) < alpha, "*", "")
ll <- split(stat_l, rep(1:num, each = length(unique(y$Samples)) - 1))
d <- NULL
for (i in seq_along(ll)){
d <- append(d, c("", ll[[i]]))
}
tmp <- expand.grid(unique(z$features), unique(z$Samples)) %>%
arrange(Var1) %>%
mutate(annot = d)
an <- z %>%
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 <- .grid_stat(x, method = method, group = TRUE, alpha = alpha)
d <- as.vector(as.matrix(stat[,2:ncol(stat)]))
tmp <- expand.grid(unique(z$features), unique(z$Samples)) %>%
arrange(Var1) %>%
mutate(annot = d)
an <- z %>%
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 = z,
aes(x = features,
y = values,
colour = 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(),
legend.margin=margin(10,10,10,0),
legend.box.margin=margin(-10,-10,-10,-10),
panel.grid.minor.x = element_blank(),
legend.position = legend) +
geom_vline(xintercept = seq(1.5, length(unique(an$features))-0.5, 1),
colour = "lightgrey") +
labs(title = main,
color = "",
x = "",
y = "root length colonized [%]") +
scale_y_continuous(limits = c(-0.5, 105),
breaks = seq(0, 105, 20))+
scale_colour_manual(values = cbPalette,
breaks = levels(factor(z$Samples,
levels = unique(x$Samples))),
name = "") +
geom_text(data = an, aes(x = features, label = annot, y = values), vjust = -0.8,
position = dodge, show.legend = FALSE, size = dimen)
class(a2) <- c("am_plot", class(a2))
return(a2)
}
#' @export
am_dotplot.grid <- function(x, cbPalette = c("#999999", "#E69F00", "#56B4E9",
"#009E73", "#F0E442", "#0072B2",
"#D55E00", "#CC79A7"),
alpha = 0.05,
annot = c("none", "asterisks", "letters"),
annot_size = 5,
method = c("none","holm","hommel", "hochberg",
"bonferroni", "BH", "BY", "fdr"),
legend = c("right", "left", "top", "bottom"),
main = "Gridline intersect method", ...){
Arbuscules <- Hypopodia <- Intr_Hyphae <- Total <- Vesicles <- comp <- NULL
features <- Replicates <- Samples <- values <- Var1 <- NULL
alpha <- alpha
annot <- match.arg(annot)
method <- match.arg(method)
legend <- match.arg(legend)
# Create summary table
y <- grid_summary(x)
num <- ncol(y)-2
# Change table shape
z <- y %>% tidyr::gather(features, values, -Samples, -Replicates) %>%
mutate(features = factor(features, levels = c("Total", "Hyphopodia",
"IntrHyphae", "Arbuscules",
"Vesicles")),
Samples = factor(Samples, levels = unique(x$Samples))) %>%
arrange(features, Samples)
# Add annotations
if (annot == "none"){
tmp <- expand.grid(unique(z$features), unique(z$Samples)) %>%
arrange(Var1) %>%
mutate(annot = "")
an <- z %>%
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 <- .grid_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:ncol(y)])) < alpha, "*", "")
ll <- split(stat_l, rep(1:num, each = length(unique(y$Samples)) - 1))
d <- NULL
for (i in seq_along(ll)){
d <- append(d, c("", ll[[i]]))
}
tmp <- expand.grid(unique(z$features), unique(z$Samples)) %>%
arrange(Var1) %>%
mutate(annot = d)
an <- z %>%
left_join(tmp, by = c("features" = "Var1", "Samples" = "Var2")) %>%
group_by(Samples, features) %>%
dplyr::filter(values == max(values)) %>%
arrange(features, Samples) %>%
dplyr::top_n(1, Replicates)
dimen <- annot_size
}
if (annot == "letters"){
stat <- .grid_stat(x, method = method, group = TRUE, alpha = alpha)
d <- as.vector(as.matrix(stat[,2:ncol(stat)]))
tmp <- expand.grid(unique(z$features), unique(z$Samples)) %>%
arrange(Var1) %>%
mutate(annot = d)
an <- z %>%
left_join(tmp, by = c("features" = "Var1", "Samples" = "Var2")) %>%
group_by(Samples, features) %>%
dplyr::filter(values == max(values)) %>%
arrange(features, Samples) %>%
dplyr::top_n(1, Replicates)
dimen <- annot_size
}
g <- ggplot(data = z,
aes(x = features,
y = values, color = Samples))
dodge <- position_dodge(width=0.9)
a2 <- g +
geom_point(position = position_jitterdodge(dodge.width = 0.9,
jitter.width = 0.1)) +
theme_bw() +
theme(plot.title = element_text(size = 19),
panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
panel.grid.major.x = element_blank(),
legend.margin=margin(10,10,10,0),
legend.box.margin=margin(-10,-10,-10,-10),
panel.grid.minor.x = element_blank(),
legend.position = legend) +
geom_vline(xintercept = seq(1.5, length(unique(an$features))-0.5, 1),
colour = "lightgrey") +
labs(title = main,
color = "",
x = "",
y = "root length colonized [%]") +
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(z$Samples,
levels = unique(x$Samples))),
name = "")
class(a2) <- c("am_plot", class(a2))
return(a2)
}
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