GSEA dot plot

library(ggplot2)
library(dplyr)
library(stringr)
library(forcats) ## for reordering the factor

df = read.csv("gsea.tsv",sep="\t")
head(df)

A data.frame: 6 × 7

	Term	es	nes	pval	fdr	geneset_size	matched_size
	<chr>	<dbl>	<dbl>	<int>	<int>	<int>	<int>
1	HALLMARK_UV_RESPONSE_DN	-0.4888729	-2.175577	0	0	144	40
2	HALLMARK_MITOTIC_SPINDLE	-0.3717000	-2.100263	0	0	199	87
3	translational termination	0.7299984	3.668103	0	0	96	47
4	translational elongation	0.6999150	3.711168	0	0	104	55
5	mitochondrial respiratory chain complex I assembly	0.7694024	3.758074	0	0	58	37
6	mitochondrial ATP synthesis coupled electron transport	0.8161274	4.028207	0	0	71	50

df$gene_ratio = df$matched_size/df$geneset_size
head(df)

A data.frame: 6 × 8

	Term	es	nes	pval	fdr	geneset_size	matched_size	gene_ratio
	<chr>	<dbl>	<dbl>	<int>	<int>	<int>	<int>	<dbl>
1	HALLMARK_UV_RESPONSE_DN	-0.4888729	-2.175577	0	0	144	40	0.2777778
2	HALLMARK_MITOTIC_SPINDLE	-0.3717000	-2.100263	0	0	199	87	0.4371859
3	translational termination	0.7299984	3.668103	0	0	96	47	0.4895833
4	translational elongation	0.6999150	3.711168	0	0	104	55	0.5288462
5	mitochondrial respiratory chain complex I assembly	0.7694024	3.758074	0	0	58	37	0.6379310
6	mitochondrial ATP synthesis coupled electron transport	0.8161274	4.028207	0	0	71	50	0.7042254

# pvalue is all zero, no point to use pvalue for color or size

options(repr.plot.width = 10, repr.plot.height = 8)

ggplot(df, aes(x = gene_ratio, y = fct_reorder(Term, gene_ratio))) +
               geom_point(aes(size = matched_size, color = nes)) +
               theme_bw(base_size = 16) +
        scale_color_gradient2(low="blue", high="red",midpoint=1)+
        ylab(NULL) +
        ggtitle("Gene Set Enrichment Analysis")
ggsave("GSEA.pdf",height=8,width=10)