library(ggplot2) theme_set( theme_classic() + theme(legend.position ="top") ) Basic scatter plots sp <- ggplot(cars, aes(x = speed, y = dist)) + geom_point() sp Change axis ticks break interval # Break y axis by a specified value# a tick mark is shown on every 50sp + scale...
#' @param x a mschart object #' @param base_size base font size #' @param base_family font family #' #' @return a mschart object #' #' @export #' #' @section theme_ggplot2(): #' #' \if{html}{\figure{fig_theme_ggplot2.png}{options: width="500"}} #' #' @examples #...
(x2, y2, label="波谷点")7.添加一些网格和图注释 theme(:ggplot2) #用一下ggplot2主题 #设...
使用ggplot在热图中剖切 添加镶嵌面包裹并指示四列。 ggplot(df[1:500,], aes(x = variable, y = Row.names, fill = value)) + geom_tile() + theme(axis.title.x=element_blank(), axis.text.x=element_blank(), axis.ticks.x=element_blank(), axis.title.y=element_blank(), axis.text.y=...
axis.ticks.y=element_blank()) if (logy) plot <- plot + scale_y_log10() plot } choose100_df <- choose_df(0:100, 0.8) cp <- choose_plot(choose100_df, FALSE) lcp <- choose_plot(choose100_df, TRUE) grid.newpage() grid.arrange(ggplotGrob(cp), ggplotGrob(lcp), ncol = 2) ...
library(ggplot2)pp = ggplot(diff_result, aes(reorder(geneset, t), t)) + geom_col(aes(fill=up_down)) + scale_fill_manual(values=c("#6CC570","#2A5078")) + coord_flip() +labs(x="Gene set", y="t value of GSVA Score") +theme_minimal() +geom_text(data = diff_result[diff...
(x2, y2, label="波谷点")7.添加一些网格和图注释theme(:ggplot2) #用一下ggplot2主题 #设置...
library(ggplot2)pp = ggplot(diff_result, aes(reorder(geneset, t), t)) + geom_col(aes(fill=up_down)) + scale_fill_manual(values=c("#6CC570","#2A5078")) + coord_flip() +labs(x="Gene set", y="t value of GSVA Score") +theme_minimal() +geom_text(data = diff_result[diff...
This repository contains the scripts used for validating and analyzing the Taenia solium transcriptome. The workflow serves as a starting point for data exploration and hypothesis generation. - ts-seq/gene_set_enrichment.R at main · dcastanedac/ts-seq
vis_ligand_receptor_network = lr_network_top_matrix[order_receptors, order_ligands_receptor] p_ligand_receptor_network = vis_ligand_receptor_network %>% t() %>% make_heatmap_ggplot("Prioritized CAF-ligands","Receptors expressed by malignant cells", color = "mediumvioletred", x_axis_position...