#install.packages("ggsci")
library('ggplot2')
library('gridExtra')
library('ggsci')
## Warning: package 'ggsci' was built under R version 4.0.5
#scale_colour_palname()
p1 <- ggplot(
subset(diamonds, carat >= 2.2),
aes(x = table, y = price, colour = cut)) +
geom_point(alpha = 0.7) +
geom_smooth(method = "loess", alpha = 0.05, size = 1, span = 1) +
theme_bw()
p2 <- ggplot(
subset(diamonds, carat > 2.2 & depth > 55 & depth < 70),
aes(x = depth, fill = cut)) +
geom_histogram(colour = "black", binwidth = 1, position = "dodge") +
theme_bw()
grid.arrange(p1, p2, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'
p1_npg <- p1 + scale_color_npg()
p2_npg <- p2 + scale_fill_npg()
grid.arrange(p1_npg, p2_npg, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'
p1_aaas <- p1 + scale_color_aaas()
p2_aaas <- p2 + scale_fill_aaas()
grid.arrange(p1_aaas, p2_aaas, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'
p1_nejm <- p1 + scale_color_nejm()
p2_nejm <- p2 + scale_fill_nejm()
grid.arrange(p1_nejm, p2_nejm, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'
p1_lancet <- p1 + scale_color_lancet()
p2_lancet <- p2 + scale_fill_lancet()
grid.arrange(p1_lancet, p2_lancet, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'
p1_jama <- p1 + scale_color_jama()
p2_jama <- p2 + scale_fill_jama()
grid.arrange(p1_jama, p2_jama, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'
p1_jco <- p1 + scale_color_jco()
p2_jco <- p2 + scale_fill_jco()
grid.arrange(p1_jco, p2_jco, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'
p1_ucscgb <- p1 + scale_color_ucscgb()
p2_ucscgb <- p2 + scale_fill_ucscgb()
grid.arrange(p1_ucscgb, p2_ucscgb, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'
p1_d3 <- p1 + scale_color_d3()
p2_d3 <- p2 + scale_fill_d3()
grid.arrange(p1_d3, p2_d3, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'
p1_locuszoom <- p1 + scale_color_locuszoom()
p2_locuszoom <- p2 + scale_fill_locuszoom()
grid.arrange(p1_locuszoom, p2_locuszoom, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'
p1_igv_default <- p1 + scale_color_igv()
p2_igv_default <- p2 + scale_fill_igv()
grid.arrange(p1_igv_default, p2_igv_default, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'
#p1_cosmic_hallmarks_light <- p1 + scale_color_cosmic("hallmarks_light")
#p2_cosmic_hallmarks_light <- p2 + scale_fill_cosmic("hallmarks_light")
#grid.arrange(p1_cosmic_hallmarks_light, p2_cosmic_hallmarks_light, ncol = 2)
##
#p1_cosmic_hallmarks_dark <- p1 + scale_color_cosmic("hallmarks_dark")
#p2_cosmic_hallmarks_dark <- p2 + scale_fill_cosmic("hallmarks_dark")
#grid.arrange(p1_cosmic_hallmarks_dark, p2_cosmic_hallmarks_dark, ncol = 2)
##
#p1_cosmic_signature <- p1 + scale_color_cosmic("signature_substitutions")
#p2_cosmic_signature <- p2 + scale_fill_cosmic("signature_substitutions")
#grid.arrange(p1_cosmic_signature, p2_cosmic_signature, ncol = 2)
p1_uchicago <- p1 + scale_color_uchicago()
p2_uchicago <- p2 + scale_fill_uchicago()
grid.arrange(p1_uchicago, p2_uchicago, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'
p1_startrek <- p1 + scale_color_startrek()
p2_startrek <- p2 + scale_fill_startrek()
grid.arrange(p1_startrek, p2_startrek, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'
p1_tron <- p1 + theme_dark() + theme(
panel.background = element_rect(fill = "#2D2D2D"),
legend.key = element_rect(fill = "#2D2D2D")) +
scale_color_tron()
p2_tron <- p2 + theme_dark() + theme(
panel.background = element_rect(fill = "#2D2D2D")) +
scale_fill_tron()
grid.arrange(p1_tron, p2_tron, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'
p1_futurama <- p1 + scale_color_futurama()
p2_futurama <- p2 + scale_fill_futurama()
grid.arrange(p1_futurama, p2_futurama, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'
p1_rickandmorty <- p1 + scale_color_rickandmorty()
p2_rickandmorty <- p2 + scale_fill_rickandmorty()
grid.arrange(p1_rickandmorty, p2_rickandmorty, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'
p1_simpsons <- p1 + scale_color_simpsons()
p2_simpsons <- p2 + scale_fill_simpsons()
grid.arrange(p1_simpsons, p2_simpsons, ncol = 2)
## `geom_smooth()` using formula 'y ~ x'
library("reshape2")
data("mtcars")
cor <- cor(unname(cbind(mtcars, mtcars, mtcars, mtcars)))
cor_melt <- melt(cor)
head(cor_melt)
## Var1 Var2 value
## 1 1 1 1.0000000
## 2 2 1 -0.8521620
## 3 3 1 -0.8475514
## 4 4 1 -0.7761684
## 5 5 1 0.6811719
## 6 6 1 -0.8676594
p3 <- ggplot(
cor_melt,
aes(x = Var1, y = Var2, fill = value)) +
geom_tile(colour = "black", size = 0.3) +
theme_bw() +
theme(
axis.title.x = element_blank(),
axis.title.y = element_blank())
p3
############22---GSEA
p3_gsea <- p3 + scale_fill_gsea()
p3_gsea_inv <- p3 + scale_fill_gsea(reverse = TRUE)
grid.arrange(p3_gsea, p3_gsea_inv, ncol = 2)
############22---Material Design
library("reshape2")
set.seed(121)
k <- 9
x <- diag(k)
x[upper.tri(x)] <- runif(sum(1:(k - 1)), 0, 1)
x_melt <- melt(x)
p4 <- ggplot(x_melt, aes(x = Var1, y = Var2, fill = value)) +
geom_tile(colour = "black", size = 0.3) +
scale_x_continuous(expand = c(0, 0)) +
scale_y_continuous(expand = c(0, 0)) +
theme_bw() + theme(
legend.position = "none", plot.background = element_blank(),
axis.line = element_blank(), axis.ticks = element_blank(),
axis.text.x = element_blank(), axis.text.y = element_blank(),
axis.title.x = element_blank(), axis.title.y = element_blank(),
panel.background = element_blank(), panel.border = element_blank(),
panel.grid.major = element_blank(), panel.grid.minor = element_blank()
)
p4
grid.arrange(
p4 + scale_fill_material("red"), p4 + scale_fill_material("pink"),
p4 + scale_fill_material("purple"), p4 + scale_fill_material("deep-purple"),
p4 + scale_fill_material("indigo"), p4 + scale_fill_material("blue"),
p4 + scale_fill_material("light-blue"), p4 + scale_fill_material("cyan"),
p4 + scale_fill_material("teal"), p4 + scale_fill_material("green"),
p4 + scale_fill_material("light-green"), p4 + scale_fill_material("lime"),
p4 + scale_fill_material("yellow"), p4 + scale_fill_material("amber"),
p4 + scale_fill_material("orange"), p4 + scale_fill_material("deep-orange"),
p4 + scale_fill_material("brown"), p4 + scale_fill_material("grey"),
p4 + scale_fill_material("blue-grey"),
ncol = 6
)
mypal <- pal_npg("nrc", alpha = 0.7)(9)
mypal
## [1] "#E64B35B2" "#4DBBD5B2" "#00A087B2" "#3C5488B2" "#F39B7FB2" "#8491B4B2"
## [7] "#91D1C2B2" "#DC0000B2" "#7E6148B2"
library("scales")
show_col(mypal)
##reff:https://cran.r-project.org/web/packages/ggsci/vignettes/ggsci.html
vignette("ggsci")
## starting httpd help server ... done