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Merge pull request #421 from ncborcherding/dev
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v2.0.8
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@ncborcherding
ncborcherding authored Oct 18, 2024
2 parents 3428d08 + 18a2d41 commit ebcd027
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2 changes: 2 additions & 0 deletions NEWS.md
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## UNDERLYING CHANGES
* Fixed issue with single chain output for ```clonalLength()```
* Removed unnecessary code remnant in ```clonalLength()```
* Allow one sample to be plotted by ```percentVJ()```
* Fixed issue with ```positionalProperty()``` and exportTable

# scRepertoire VERSION 2.0.7

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101 changes: 52 additions & 49 deletions R/clonalAbundance.R
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#' Demonstrate the relative abundance of clones by group or sample
#'
#' Displays the number of clones at specific frequencies by sample
#' Displays the number of clones at specific frequencies by sample
#' or group. Visualization can either be a line graph (
#' \strong{scale} = FALSE) using calculated numbers or density
#' plot (\strong{scale} = TRUE). Multiple sequencing runs can
#' be group together using the group parameter. If a matrix
#' output for the data is preferred, set
#' \strong{scale} = FALSE) using calculated numbers or density
#' plot (\strong{scale} = TRUE). Multiple sequencing runs can
#' be group together using the group parameter. If a matrix
#' output for the data is preferred, set
#' \strong{exportTable} = TRUE.
#'
#' @examples
#' #Making combined contig data
#' combined <- combineTCR(contig_list,
#' samples = c("P17B", "P17L", "P18B", "P18L",
#' combined <- combineTCR(contig_list,
#' samples = c("P17B", "P17L", "P18B", "P18L",
#' "P19B","P19L", "P20B", "P20L"))
#' clonalAbundance(combined,
#' cloneCall = "gene",
#' clonalAbundance(combined,
#' cloneCall = "gene",
#' scale = FALSE)
#'
#' @param input.data The product of \code{\link{combineTCR}},
#' @param input.data The product of \code{\link{combineTCR}},
#' \code{\link{combineBCR}}, or \code{\link{combineExpression}}.
#' @param cloneCall How to call the clone - VDJC gene (\strong{gene}),
#' @param cloneCall How to call the clone - VDJC gene (\strong{gene}),
#' CDR3 nucleotide (\strong{nt}), CDR3 amino acid (\strong{aa}),
#' VDJC gene + CDR3 nucleotide (\strong{strict}) or a custom variable
#' in the data.
#' @param chain indicate if both or a specific chain should be used -
#' VDJC gene + CDR3 nucleotide (\strong{strict}) or a custom variable
#' in the data.
#' @param chain indicate if both or a specific chain should be used -
#' e.g. "both", "TRA", "TRG", "IGH", "IGL"
#' @param group.by The variable to use for grouping
#' @param order.by A vector of specific plotting order or "alphanumeric"
#' to plot groups in order
#' @param scale Converts the graphs into density plots in order to show
#' @param scale Converts the graphs into density plots in order to show
#' relative distributions.
#' @param exportTable Returns the data frame used for forming the graph
#' to the visualization.
#' @param palette Colors to use in visualization - input any
#' @param palette Colors to use in visualization - input any
#' \link[grDevices]{hcl.pals}.
#' @importFrom ggplot2 ggplot
#' @export
#' @concept Visualizing_Clones
#' @return ggplot of the total or relative abundance of clones
#' @return ggplot of the total or relative abundance of clones
#' across quanta
clonalAbundance <- function(input.data,
cloneCall = "strict",
chain = "both",
scale=FALSE,
group.by = NULL,
clonalAbundance <- function(input.data,
cloneCall = "strict",
chain = "both",
scale=FALSE,
group.by = NULL,
order.by = NULL,
exportTable = FALSE,
palette = "inferno") {
Con.df <- NULL
xlab <- "Abundance"
input.data <- .data.wrangle(input.data,
group.by,
.theCall(input.data, cloneCall, check.df = FALSE),
input.data <- .data.wrangle(input.data,
group.by,
.theCall(input.data, cloneCall, check.df = FALSE),
chain)
cloneCall <- .theCall(input.data, cloneCall)

names <- names(input.data)
if (!is.null(group.by)) {
for (i in seq_along(input.data)) {
data1 <- .parseContigs(input.data, i, names, cloneCall)
label <- input.data[[i]][1,group.by]
data1[,paste(group.by)] <- label
Con.df<- rbind.data.frame(Con.df, data1)
Con.df<- rbind.data.frame(Con.df, data1)
}
Con.df <- data.frame(Con.df)
if (exportTable == TRUE) {
return(Con.df)
}
col <- length(unique(Con.df[,group.by]))
fill <- group.by
if(!is.null(order.by)) {
Con.df <- .ordering.function(vector = order.by,
group.by = group.by,
group.by = group.by,
data.frame = Con.df)
}
if (scale == TRUE) {
if (scale == TRUE) {
ylab <- "Density of Clones"
plot <- ggplot(Con.df, aes(x=Abundance, fill=Con.df[,group.by])) +
geom_density(aes(y=after_stat(scaled)),
alpha=0.5,
lwd=0.25,
color="black",
geom_density(aes(y=after_stat(scaled)),
alpha=0.5,
lwd=0.25,
color="black",
bw=0.5) +
scale_fill_manual(values = .colorizer(palette,col)) +
labs(fill = fill)
} else {
} else {
ylab <- "Number of Clones"
plot <- ggplot(Con.df, aes(x=Abundance, group.by = values,
plot <- ggplot(Con.df, aes(x=Abundance, group.by = values,
color = Con.df[,group.by])) +
geom_line(stat="count") +
scale_color_manual(values = .colorizer(palette,col)) +
Expand All @@ -92,39 +95,39 @@ clonalAbundance <- function(input.data,
} else {
for (i in seq_along(input.data)) {
data1 <- .parseContigs(input.data, i, names, cloneCall)
Con.df<- rbind.data.frame(Con.df, data1)
Con.df<- rbind.data.frame(Con.df, data1)
}
Con.df <- data.frame(Con.df)
if (exportTable == TRUE) {
return(Con.df)
}
if(!is.null(order.by)) {
Con.df <- .ordering.function(vector = order.by,
group.by = "values",
group.by = "values",
data.frame = Con.df)
}

col <- length(unique(Con.df$values))
fill <- "Samples"
if (scale == TRUE) {
if (scale == TRUE) {
ylab <- "Density of Clones"
plot <- ggplot(Con.df, aes(Abundance, fill=values)) +
geom_density(aes(y=after_stat(scaled)),
alpha=0.5,
lwd=0.25,
color="black",
geom_density(aes(y=after_stat(scaled)),
alpha=0.5,
lwd=0.25,
color="black",
bw=0.5) +
scale_fill_manual(values = .colorizer(palette,col)) +
labs(fill = fill)
} else {
} else {
ylab <- "Number of Clones"
plot <- ggplot(Con.df, aes(x=Abundance, group = values,
plot <- ggplot(Con.df, aes(x=Abundance, group = values,
color = values)) +
geom_line(stat="count") +
scale_color_manual(values = .colorizer(palette,col)) +
labs(color = fill)
} }
if (exportTable == TRUE) {
return(Con.df)
}
plot <- plot + scale_x_log10() + ylab(ylab) + xlab(xlab) +
theme_classic()
return(plot)
return(plot)
}
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