R/jj_plot_volcano.R
In mathosi/jj: Just Joise
Defines functions
jj_plot_volcano
Documented in
jj_plot_volcano
#' show results from differential expression analysis
#'
#' jj_plot_volcano volcano plot of pval (which is -log10 transformed) against logFC
#'
#' @name jj_plot_volcano
#' @param logfc_column sparse matrix, vector, or data.frame
#' @param pval_column vector with group annotation, has to have length equal to ncol(sparse_mat)/nrow(data.frame)/length(vector)
#' @param symbol_column provide `symbol_column` to add text to all points that are highlighted (when use_text=TRUE)
#' @param labs_range vector specifying range of x axis (and for fc_fc plot range of y axis)
#' @param marker_thres define `marker_thres` to highlight all points with absolute value above
#' @param col_vec define larger, smaller, intermediate and highlight colours
#' @param markers_highlight vector of genes from the symbol_column which should additionally be highlighted
#' @param markers_highlight_col named vector assigning a colour to each gene to be highlighed
#' @param only_highlight if TRUE, only show markers specified in `markers_highlight`
#' @param col_by_highlight if TRUE, only colour the markers specified in `markers_highlight`
#' @param use_text plot text if there are any points to highlight
#' @param add_thres_line if TRUE, plot dashed lines at the defined `marker_thres`
#' @param alpha alpha level for points (working?)
#' @returns ggplot scatterplot of log10(pval) vs FC or FC vs FC
#' @export
#' @examples
#' #Using Seurats FindMarkers output
#' library(Seurat)
#' marker_df = FindMarkers(pbmc_small, group.by = 'groups', ident.1 = 'g1', ident.2 = 'g2')
#' marker_df$symbol = rownames(marker_df)
#' #or using a random data.frame
#' marker_df = data.frame(avg_log2FC = rnorm(100, 0, 2),
#' p_val = sample(c(runif(50, 0, 0.1), runif(50))),
#' symbol = paste0(sample(LETTERS, 100, replace = T), sample(letters, 100, replace = T), 1:100))
#' jj_plot_volcano(marker_df, logfc_column = 'avg_log2FC', pval_column = 'p_val', marker_thres = Inf) + theme(legend.position = 'none')
#' #colour highlighting above a threshold and capping very high and low values, adding lines for the threshold
#' jj_plot_volcano(marker_df, logfc_column = 'avg_log2FC', pval_column = 'p_val',
#' labs_range = c(-2,2), marker_thres = 1.5, add_thres_line=T)
#' #adding text to highlighted markers, possibility to show unbalanced x axis
#' jj_plot_volcano(marker_df, logfc_column = 'avg_log2FC', pval_column = 'p_val', symbol_column = 'symbol',
#' use_text = T, labs_range = c(-2,4), marker_thres = 2)
#' #instead of highlighting everything above/below a threshold, specific markers can be highlighted
#' jj_plot_volcano(marker_df, logfc_column = 'avg_log2FC', pval_column = 'p_val', symbol_column = 'symbol',
#' labs_range = c(-2.5, 2.5), marker_thres = 4,
#' markers_highlight = marker_df$symbol[1:4], pt.size = 1.5,
#' only_highlight = F, col_by_highlight = T)
#' #specific highlighting and general highlighting can be combined
#' jj_plot_volcano(marker_df, logfc_column = 'avg_log2FC', pval_column = 'p_val', symbol_column = 'symbol',
#' labs_range = c(-2.5, 2.5), marker_thres = 2,
#' markers_highlight = marker_df$symbol[1:4], pt.size = 1.5, highlight.pt.size = 3,
#' only_highlight = F, col_by_highlight = F)
#' #only show highlighted markers
#' jj_plot_volcano(marker_df, logfc_column = 'avg_log2FC', pval_column = 'p_val', symbol_column = 'symbol',
#' labs_range = c(-2.5, 2.5), marker_thres = 2,
#' markers_highlight = marker_df$symbol[1:4], pt.size = 1.5,
#' only_highlight = T, col_by_highlight = F)
#' #to change colour and size of highlighted markers use `highlight.pt.size` and `markers_highlight_cols`
#' jj_plot_volcano(marker_df, logfc_column = 'avg_log2FC', pval_column = 'p_val', symbol_column = 'symbol',
#' labs_range = c(-4, 4), marker_thres = Inf,
#' markers_highlight = marker_df$symbol[1:4], pt.size = 1.5, highlight.pt.size = 3,
#' only_highlight = F, col_by_highlight =T,
#' markers_highlight_col = structure(c('red','orange','red','blue'), names = marker_df$symbol[1:4])) + theme(legend.position='none')
#' @export
jj_plot_volcano = function(plot_df, logfc_column, pval_column, symbol_column=NULL,
marker_thres = c(0.5,Inf), labs_range = NULL, alpha = 1,
pt.size=2.5, highlight.pt.size = 2.5,
col_vec = c("red", "blue", "black","green"),
markers_highlight = NULL, markers_highlight_col=NULL, only_highlight=FALSE,
col_by_highlight=FALSE, use_text=TRUE, add_thres_line = FALSE, group_names=NULL,
arrow_pos=list(x=0.25, xend=1, y=40)){
#TODO: sym() throws error if it is not used from the dplyr package: Error in local_error_context(dots = dots, .index = i, mask = mask) :
# promise already under evaluation: recursive default argument reference or earlier problems?
plot_df = as.data.frame(plot_df)
stopifnot(is.data.frame(plot_df))
if(!is.null(group_names)){
stopifnot(length(group_names) == 2)
}
plot_df = plot_df[, colnames(plot_df) %in% c(logfc_column, pval_column, symbol_column)]
plot_df[, pval_column] = -log10(plot_df[, pval_column])
if(!is.null(labs_range)){
if(length(labs_range) == 2){
stopifnot(all(is.numeric(labs_range)))
labs_range = c(labs_range, 0, max(plot_df[, pval_column]))
}else if(length(labs_range) == 4){
stopifnot(all(is.numeric(labs_range)))
}else{
stop("labs_range should be of length 2 (defining x axis) or 4 (definining x and y axes) or NULL (no limits)")
}
}
symbols_use = c('outside plotting area', 'inside plotting area')
if(is.null(marker_thres)){
marker_thres = c(Inf, Inf)
}else if(length(marker_thres)==1){
marker_thres = c(marker_thres, Inf)
}else if(length(marker_thres) > 2){
stop('marker_thres should specifiy thresholds on log2FC and adjusted p value (length 2)')
}
if(!is.null(labs_range)){
#add a column that is used for different symbols (circle if inside plot, triangle if outside)
#dplyr throws error 'attempt to use zero-length variable name' if there is a colname ''
plot_df = dplyr::mutate(plot_df, localization = ifelse(!!sym(logfc_column) > labs_range[2] | !!sym(pval_column) > labs_range[4], symbols_use[1],
ifelse(!!sym(logfc_column) < labs_range[1] | !!sym(pval_column) < labs_range[3],
symbols_use[1], symbols_use[2])))
plot_df$localization = factor(plot_df$localization, levels = c('inside plotting area', 'outside plotting area'))
#cap the values outside of plot
plot_df[, logfc_column] = ifelse(plot_df[, logfc_column] > labs_range[2], labs_range[2],
ifelse(plot_df[, logfc_column] < labs_range[1],
labs_range[1], plot_df[, logfc_column]))
plot_df[, pval_column] = ifelse(plot_df[, pval_column] > labs_range[4], labs_range[4],
ifelse(plot_df[, pval_column] < labs_range[3],
labs_range[3], plot_df[, pval_column]))
}
#give label for all genes > marker_thres
mthres = as.character(marker_thres[1])
small_val = paste0(">= ", mthres)
middle_val = sprintf(">-%s & <%s", mthres, mthres)
big_val = paste0("<= -", mthres)
plot_df$logFC = ifelse(plot_df[, logfc_column] >= marker_thres[1], small_val,
ifelse(plot_df[, logfc_column]<=-marker_thres[1] , big_val,
middle_val))
mthres2 = as.character(marker_thres[2])
small_val2 = paste0(">= ", mthres2)
big_val2 = paste0("<= -", mthres2)
plot_df$pval_thres = ifelse(plot_df[, pval_column] >= marker_thres[2], small_val2, big_val2)
if(!is.null(symbol_column)){
plot_df$label_use <- ''
plot_df$label_use[plot_df$logFC != middle_val] <- plot_df[, symbol_column][plot_df$logFC != middle_val]
plot_df$label_use[plot_df$pval_thres != big_val2] <- plot_df[, symbol_column][plot_df$pval_thres != big_val2]
if(!is.null(markers_highlight) & any(plot_df[, symbol_column] %in% markers_highlight)){
if(only_highlight){
plot_df = plot_df[plot_df[, symbol_column] %in% markers_highlight, ]
}
#markers_highlight = unique(plot_df[, symbol_column])
plot_df$label_use[plot_df[, symbol_column] %in% markers_highlight] <- plot_df[, symbol_column][plot_df[, symbol_column] %in% markers_highlight]
plot_df$logFC[plot_df[, symbol_column] %in% markers_highlight] = 'highlight'
plot_df = plot_df[order(plot_df[, symbol_column] %in% markers_highlight, decreasing = F), ]
}
}
cols_use = structure(col_vec, names = c(big_val, small_val, middle_val, "highlight"))
cols_use = cols_use[names(cols_use) %in% plot_df$logFC]
if(col_by_highlight){
if(is.null(markers_highlight_col)){
cols_use = jj_get_jj_colours(markers_highlight)
}else{
cols_use = markers_highlight_col
}
if(!is.null(labs_range)){
g1 = ggplot() +
geom_point(data=plot_df,
aes_string(x=logfc_column, y=pval_column, shape='localization'),
alpha=alpha, size=pt.size) +
geom_point(data=plot_df[plot_df[, symbol_column] %in% markers_highlight, ],
aes_string(x=logfc_column, y=pval_column, shape='localization',
colour='label_use'),
size=highlight.pt.size)
}else{
g1 = ggplot() +
geom_point(data=plot_df,
aes_string(x=logfc_column, y=pval_column),
alpha=alpha, size=pt.size) +
geom_point(data=plot_df[plot_df[, symbol_column] %in% markers_highlight, ],
aes_string(x=logfc_column, y=pval_column, #label='label_use',
colour='label_use'), size=highlight.pt.size)
}
}else{
if(!is.null(labs_range)){
g1 = ggplot(plot_df, aes_string(x=logfc_column, y=pval_column)) +
geom_point(aes(colour = logFC, shape=localization), size=pt.size, alpha=alpha)
# if(!is.null(markers_highlight[1])){
# g1 = g1 + geom_point(data=plot_df[plot_df[, symbol_column] %in% markers_highlight, ],
# aes_string(x=logfc_column, y=pval_column, shape='localization'),
# size=highlight.pt.size, colour = 'green')
# }
}else{
g1 = ggplot(plot_df, aes_string(x=logfc_column, y=pval_column), alpha=alpha) +
geom_point(aes(colour = logFC), size=pt.size)
# if(!is.null(markers_highlight[1])){
# g1 = g1 + geom_point(data=plot_df[plot_df[, symbol_column] %in% markers_highlight, ],
# aes_string(x=logfc_column, y=pval_column), size=highlight.pt.size)
# }
}
}
if(!is.null(symbol_column) & use_text){
g1 = g1 +
ggrepel::geom_text_repel(data=plot_df,
aes_string(x=logfc_column,
y=pval_column,
label='label_use'),
max.overlaps = 500)
}
g1 = g1 +
scale_colour_manual(values = cols_use) +
geom_hline(yintercept = 0) + geom_vline(xintercept = 0) + theme_minimal()
if(!is.null(labs_range)){
g1 = g1 + coord_cartesian(xlim=labs_range[1:2], ylim = labs_range[3:4], expand = F, clip = 'off')
}
if(add_thres_line){
if(!is.infinite(marker_thres[1])){
g1 = g1 +
geom_vline(xintercept = -marker_thres[1], linetype="dashed", color ='black', size = 0.5) +
geom_vline(xintercept = marker_thres[1], linetype="dashed", color ='black', size = 0.5)
}
if(! is.infinite(marker_thres[2])){
g1 = g1 +
geom_hline(yintercept = marker_thres[2], linetype="dashed", color ='black', size = 0.5)
}
}
label_df = data.frame(name = c('logfc_gr0', 'logfc_sm0'),
n = c(sum(plot_df[, logfc_column] > 0), sum(plot_df[, logfc_column] < 0)))
# if(add_numbers){
# g1 = g1 + geom_text(data = label_df[1, ],hjust = 1, vjust=0, mapping = aes(x = x_pos, y = y_pos, label = n)) +
# geom_text(data = label_df[2, ],hjust = 0, vjust=0, mapping = aes(x = x_pos, y = y_pos, label = n))
# }
if(!is.null(group_names[1])){
g1 = g1 + annotate('segment', x = arrow_pos$x, xend = arrow_pos$xend, y = arrow_pos$y, yend = arrow_pos$y, arrow = arrow(type = "closed", length = unit(0.02, "npc"))) +
annotate('segment', x = -arrow_pos$x, xend = -arrow_pos$xend, y = arrow_pos$y, yend = arrow_pos$y, arrow = arrow(type = "closed", length = unit(0.02, "npc"))) +
annotate('text', x = arrow_pos$xend+0.01, y = arrow_pos$y, label = sprintf('%s (%i genes)', group_names[1], label_df$n[1]), hjust = 0, size=3) +
annotate('text', x = -arrow_pos$xend-0.01, y = arrow_pos$y, label = sprintf('%s (%i genes)', group_names[2], label_df$n[2]), hjust = 1, size = 3)
}
g1 = g1 + labs(y = paste(pval_column, '(-log10)'))
return(g1)
}
mathosi/jj documentation built on Feb. 25, 2024, 2:29 p.m.
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Defines functions jj_plot_volcano
Documented in jj_plot_volcano
#' show results from differential expression analysis
#'
#' jj_plot_volcano volcano plot of pval (which is -log10 transformed) against logFC
#'
#' @name jj_plot_volcano
#' @param logfc_column sparse matrix, vector, or data.frame
#' @param pval_column vector with group annotation, has to have length equal to ncol(sparse_mat)/nrow(data.frame)/length(vector)
#' @param symbol_column provide `symbol_column` to add text to all points that are highlighted (when use_text=TRUE)
#' @param labs_range vector specifying range of x axis (and for fc_fc plot range of y axis)
#' @param marker_thres define `marker_thres` to highlight all points with absolute value above
#' @param col_vec define larger, smaller, intermediate and highlight colours
#' @param markers_highlight vector of genes from the symbol_column which should additionally be highlighted
#' @param markers_highlight_col named vector assigning a colour to each gene to be highlighed
#' @param only_highlight if TRUE, only show markers specified in `markers_highlight`
#' @param col_by_highlight if TRUE, only colour the markers specified in `markers_highlight`
#' @param use_text plot text if there are any points to highlight
#' @param add_thres_line if TRUE, plot dashed lines at the defined `marker_thres`
#' @param alpha alpha level for points (working?)
#' @returns ggplot scatterplot of log10(pval) vs FC or FC vs FC
#' @export
#' @examples
#' #Using Seurats FindMarkers output
#' library(Seurat)
#' marker_df = FindMarkers(pbmc_small, group.by = 'groups', ident.1 = 'g1', ident.2 = 'g2')
#' marker_df$symbol = rownames(marker_df)
#' #or using a random data.frame
#' marker_df = data.frame(avg_log2FC = rnorm(100, 0, 2),
#' p_val = sample(c(runif(50, 0, 0.1), runif(50))),
#' symbol = paste0(sample(LETTERS, 100, replace = T), sample(letters, 100, replace = T), 1:100))
#' jj_plot_volcano(marker_df, logfc_column = 'avg_log2FC', pval_column = 'p_val', marker_thres = Inf) + theme(legend.position = 'none')
#' #colour highlighting above a threshold and capping very high and low values, adding lines for the threshold
#' jj_plot_volcano(marker_df, logfc_column = 'avg_log2FC', pval_column = 'p_val',
#' labs_range = c(-2,2), marker_thres = 1.5, add_thres_line=T)
#' #adding text to highlighted markers, possibility to show unbalanced x axis
#' jj_plot_volcano(marker_df, logfc_column = 'avg_log2FC', pval_column = 'p_val', symbol_column = 'symbol',
#' use_text = T, labs_range = c(-2,4), marker_thres = 2)
#' #instead of highlighting everything above/below a threshold, specific markers can be highlighted
#' jj_plot_volcano(marker_df, logfc_column = 'avg_log2FC', pval_column = 'p_val', symbol_column = 'symbol',
#' labs_range = c(-2.5, 2.5), marker_thres = 4,
#' markers_highlight = marker_df$symbol[1:4], pt.size = 1.5,
#' only_highlight = F, col_by_highlight = T)
#' #specific highlighting and general highlighting can be combined
#' jj_plot_volcano(marker_df, logfc_column = 'avg_log2FC', pval_column = 'p_val', symbol_column = 'symbol',
#' labs_range = c(-2.5, 2.5), marker_thres = 2,
#' markers_highlight = marker_df$symbol[1:4], pt.size = 1.5, highlight.pt.size = 3,
#' only_highlight = F, col_by_highlight = F)
#' #only show highlighted markers
#' jj_plot_volcano(marker_df, logfc_column = 'avg_log2FC', pval_column = 'p_val', symbol_column = 'symbol',
#' labs_range = c(-2.5, 2.5), marker_thres = 2,
#' markers_highlight = marker_df$symbol[1:4], pt.size = 1.5,
#' only_highlight = T, col_by_highlight = F)
#' #to change colour and size of highlighted markers use `highlight.pt.size` and `markers_highlight_cols`
#' jj_plot_volcano(marker_df, logfc_column = 'avg_log2FC', pval_column = 'p_val', symbol_column = 'symbol',
#' labs_range = c(-4, 4), marker_thres = Inf,
#' markers_highlight = marker_df$symbol[1:4], pt.size = 1.5, highlight.pt.size = 3,
#' only_highlight = F, col_by_highlight =T,
#' markers_highlight_col = structure(c('red','orange','red','blue'), names = marker_df$symbol[1:4])) + theme(legend.position='none')
#' @export
jj_plot_volcano = function(plot_df, logfc_column, pval_column, symbol_column=NULL,
marker_thres = c(0.5,Inf), labs_range = NULL, alpha = 1,
pt.size=2.5, highlight.pt.size = 2.5,
col_vec = c("red", "blue", "black","green"),
markers_highlight = NULL, markers_highlight_col=NULL, only_highlight=FALSE,
col_by_highlight=FALSE, use_text=TRUE, add_thres_line = FALSE, group_names=NULL,
arrow_pos=list(x=0.25, xend=1, y=40)){
#TODO: sym() throws error if it is not used from the dplyr package: Error in local_error_context(dots = dots, .index = i, mask = mask) :
# promise already under evaluation: recursive default argument reference or earlier problems?
plot_df = as.data.frame(plot_df)
stopifnot(is.data.frame(plot_df))
if(!is.null(group_names)){
stopifnot(length(group_names) == 2)
}
plot_df = plot_df[, colnames(plot_df) %in% c(logfc_column, pval_column, symbol_column)]
plot_df[, pval_column] = -log10(plot_df[, pval_column])
if(!is.null(labs_range)){
if(length(labs_range) == 2){
stopifnot(all(is.numeric(labs_range)))
labs_range = c(labs_range, 0, max(plot_df[, pval_column]))
}else if(length(labs_range) == 4){
stopifnot(all(is.numeric(labs_range)))
}else{
stop("labs_range should be of length 2 (defining x axis) or 4 (definining x and y axes) or NULL (no limits)")
}
}
symbols_use = c('outside plotting area', 'inside plotting area')
if(is.null(marker_thres)){
marker_thres = c(Inf, Inf)
}else if(length(marker_thres)==1){
marker_thres = c(marker_thres, Inf)
}else if(length(marker_thres) > 2){
stop('marker_thres should specifiy thresholds on log2FC and adjusted p value (length 2)')
}
if(!is.null(labs_range)){
#add a column that is used for different symbols (circle if inside plot, triangle if outside)
#dplyr throws error 'attempt to use zero-length variable name' if there is a colname ''
plot_df = dplyr::mutate(plot_df, localization = ifelse(!!sym(logfc_column) > labs_range[2] | !!sym(pval_column) > labs_range[4], symbols_use[1],
ifelse(!!sym(logfc_column) < labs_range[1] | !!sym(pval_column) < labs_range[3],
symbols_use[1], symbols_use[2])))
plot_df$localization = factor(plot_df$localization, levels = c('inside plotting area', 'outside plotting area'))
#cap the values outside of plot
plot_df[, logfc_column] = ifelse(plot_df[, logfc_column] > labs_range[2], labs_range[2],
ifelse(plot_df[, logfc_column] < labs_range[1],
labs_range[1], plot_df[, logfc_column]))
plot_df[, pval_column] = ifelse(plot_df[, pval_column] > labs_range[4], labs_range[4],
ifelse(plot_df[, pval_column] < labs_range[3],
labs_range[3], plot_df[, pval_column]))
}
#give label for all genes > marker_thres
mthres = as.character(marker_thres[1])
small_val = paste0(">= ", mthres)
middle_val = sprintf(">-%s & <%s", mthres, mthres)
big_val = paste0("<= -", mthres)
plot_df$logFC = ifelse(plot_df[, logfc_column] >= marker_thres[1], small_val,
ifelse(plot_df[, logfc_column]<=-marker_thres[1] , big_val,
middle_val))
mthres2 = as.character(marker_thres[2])
small_val2 = paste0(">= ", mthres2)
big_val2 = paste0("<= -", mthres2)
plot_df$pval_thres = ifelse(plot_df[, pval_column] >= marker_thres[2], small_val2, big_val2)
if(!is.null(symbol_column)){
plot_df$label_use <- ''
plot_df$label_use[plot_df$logFC != middle_val] <- plot_df[, symbol_column][plot_df$logFC != middle_val]
plot_df$label_use[plot_df$pval_thres != big_val2] <- plot_df[, symbol_column][plot_df$pval_thres != big_val2]
if(!is.null(markers_highlight) & any(plot_df[, symbol_column] %in% markers_highlight)){
if(only_highlight){
plot_df = plot_df[plot_df[, symbol_column] %in% markers_highlight, ]
}
#markers_highlight = unique(plot_df[, symbol_column])
plot_df$label_use[plot_df[, symbol_column] %in% markers_highlight] <- plot_df[, symbol_column][plot_df[, symbol_column] %in% markers_highlight]
plot_df$logFC[plot_df[, symbol_column] %in% markers_highlight] = 'highlight'
plot_df = plot_df[order(plot_df[, symbol_column] %in% markers_highlight, decreasing = F), ]
}
}
cols_use = structure(col_vec, names = c(big_val, small_val, middle_val, "highlight"))
cols_use = cols_use[names(cols_use) %in% plot_df$logFC]
if(col_by_highlight){
if(is.null(markers_highlight_col)){
cols_use = jj_get_jj_colours(markers_highlight)
}else{
cols_use = markers_highlight_col
}
if(!is.null(labs_range)){
g1 = ggplot() +
geom_point(data=plot_df,
aes_string(x=logfc_column, y=pval_column, shape='localization'),
alpha=alpha, size=pt.size) +
geom_point(data=plot_df[plot_df[, symbol_column] %in% markers_highlight, ],
aes_string(x=logfc_column, y=pval_column, shape='localization',
colour='label_use'),
size=highlight.pt.size)
}else{
g1 = ggplot() +
geom_point(data=plot_df,
aes_string(x=logfc_column, y=pval_column),
alpha=alpha, size=pt.size) +
geom_point(data=plot_df[plot_df[, symbol_column] %in% markers_highlight, ],
aes_string(x=logfc_column, y=pval_column, #label='label_use',
colour='label_use'), size=highlight.pt.size)
}
}else{
if(!is.null(labs_range)){
g1 = ggplot(plot_df, aes_string(x=logfc_column, y=pval_column)) +
geom_point(aes(colour = logFC, shape=localization), size=pt.size, alpha=alpha)
# if(!is.null(markers_highlight[1])){
# g1 = g1 + geom_point(data=plot_df[plot_df[, symbol_column] %in% markers_highlight, ],
# aes_string(x=logfc_column, y=pval_column, shape='localization'),
# size=highlight.pt.size, colour = 'green')
# }
}else{
g1 = ggplot(plot_df, aes_string(x=logfc_column, y=pval_column), alpha=alpha) +
geom_point(aes(colour = logFC), size=pt.size)
# if(!is.null(markers_highlight[1])){
# g1 = g1 + geom_point(data=plot_df[plot_df[, symbol_column] %in% markers_highlight, ],
# aes_string(x=logfc_column, y=pval_column), size=highlight.pt.size)
# }
}
}
if(!is.null(symbol_column) & use_text){
g1 = g1 +
ggrepel::geom_text_repel(data=plot_df,
aes_string(x=logfc_column,
y=pval_column,
label='label_use'),
max.overlaps = 500)
}
g1 = g1 +
scale_colour_manual(values = cols_use) +
geom_hline(yintercept = 0) + geom_vline(xintercept = 0) + theme_minimal()
if(!is.null(labs_range)){
g1 = g1 + coord_cartesian(xlim=labs_range[1:2], ylim = labs_range[3:4], expand = F, clip = 'off')
}
if(add_thres_line){
if(!is.infinite(marker_thres[1])){
g1 = g1 +
geom_vline(xintercept = -marker_thres[1], linetype="dashed", color ='black', size = 0.5) +
geom_vline(xintercept = marker_thres[1], linetype="dashed", color ='black', size = 0.5)
}
if(! is.infinite(marker_thres[2])){
g1 = g1 +
geom_hline(yintercept = marker_thres[2], linetype="dashed", color ='black', size = 0.5)
}
}
label_df = data.frame(name = c('logfc_gr0', 'logfc_sm0'),
n = c(sum(plot_df[, logfc_column] > 0), sum(plot_df[, logfc_column] < 0)))
# if(add_numbers){
# g1 = g1 + geom_text(data = label_df[1, ],hjust = 1, vjust=0, mapping = aes(x = x_pos, y = y_pos, label = n)) +
# geom_text(data = label_df[2, ],hjust = 0, vjust=0, mapping = aes(x = x_pos, y = y_pos, label = n))
# }
if(!is.null(group_names[1])){
g1 = g1 + annotate('segment', x = arrow_pos$x, xend = arrow_pos$xend, y = arrow_pos$y, yend = arrow_pos$y, arrow = arrow(type = "closed", length = unit(0.02, "npc"))) +
annotate('segment', x = -arrow_pos$x, xend = -arrow_pos$xend, y = arrow_pos$y, yend = arrow_pos$y, arrow = arrow(type = "closed", length = unit(0.02, "npc"))) +
annotate('text', x = arrow_pos$xend+0.01, y = arrow_pos$y, label = sprintf('%s (%i genes)', group_names[1], label_df$n[1]), hjust = 0, size=3) +
annotate('text', x = -arrow_pos$xend-0.01, y = arrow_pos$y, label = sprintf('%s (%i genes)', group_names[2], label_df$n[2]), hjust = 1, size = 3)
}
g1 = g1 + labs(y = paste(pval_column, '(-log10)'))
return(g1)
}
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