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sahilseth/gglegend

Last active September 16, 2022 16:51
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ggplot examples
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gglegend
override legend
# get it inside the plot, and remove alpha
theme(legend.position = c(0, 0.2),
legend.background = element_blank()) +
guides(colour = guide_legend(override.aes = list(alpha = 1)))
Raw
ggviolin
# 1
# https://github.com/kassambara/ggpubr
my_comparisons <- list( c("gb", "gc"), c("gb", "noref"))
ggplot(df_cnts_per_samp, aes(ref_type, n, color = ref_type)) +
geom_jitter() +
geom_violin(alpha = 0) +
theme_cowplot() +
scale_y_log10() +
scale_color_npg(name = "") +
xlab("Reference type") +
ylab("Number of mutations") +
stat_compare_means(comparisons = my_comparisons) + # Add pairwise comparisons p-value
stat_compare_means(label.y = 1, label.x = "gc") # Add global p-value
# to have different groups, follow this:
# https://www.datanovia.com/en/lessons/ggplot-stripchart/
ggplot(x.subset, aes(x = lbl, y = value, color = gene_id)) +
stat_summary(aes(color = gene_id), fun.data = "mean_sdl", geom="pointrange", shape=18, size=0.8, position = position_dodge(0.8)) +
geom_jitter(aes(x = lbl, y = value, color = gene_id), alpha = 0.5,
size = 1.2, position = position_jitterdodge(jitter.width = 0.2, dodge.width = 0.8)) +
# geom_violin(alpha = 0) +
scale_color_manual(values = gene_colors, name = NULL) +
theme_cowplot() +
Raw
ggviolin_jitter
# https://github.com/kassambara/ggpubr
my_comparisons <- list( c("gb", "gc"), c("gb", "noref"))
p2 = ggplot(df_cnts_per_samp, aes(ref_type, n, color = ref_type)) +
geom_jitter() +
geom_violin(alpha = 0) +
theme_cowplot() +
scale_y_log10(
breaks = scales::trans_breaks("log10", function(x) 10^x),
labels = scales::trans_format("log10", scales::math_format(10^.x))) +
# annotation_logticks() +
scale_color_npg(name = "") +
xlab("Reference type") +
ylab("Number of mutations") +
stat_compare_means(comparisons = my_comparisons) + # Add pairwise comparisons p-value
stat_compare_means(label.y = 1, label.x = "gc") # Add global p-value
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sahilseth commented Jun 15, 2021 •
edited
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facet labeller

stype.labs <- structure(c("tumor", "normal"), .Names = c("T", "N"))
facet_wrap(~ sampletype, nrow = 2,   labeller = labeller(sampletype = stype.labs)) +

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add mean comparisons (boxplot/violin)

my_comparisons &lt;- list( c("gb", "gc"), c("gb", "noref"))<br class="Apple-interchange-newline">
stat_compare_means(comparisons` = my_comparisons) + # Add pairwise comparisons p-value  
stat_compare_means(label.y = 1, label.x = "gc")       # Add global p-value

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remove color guide

theme(legend. title = element_blank()) .
theme(legend. position = "none") .
guides(color = FALSE)

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sahilseth commented Jul 16, 2021 •
edited
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change axis ticks label

labs <- c("Citrus", "Crop", "Cypress Swamp")
+ scale_x_discrete(labels= labs)

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add mean SD

  stat_summary(fun.data = "mean_sdl", geom="pointrange", shape=18, size=0.8, position = position_dodge(0.8))

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add regression line and correlation

geom_point() +
  geom_smooth(method='lm') +
  ggpubr::stat_cor() +
  theme_cowplot()

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theme cowplot font:

  theme_cowplot(font_size = 30) +

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sahilseth commented Sep 16, 2022 •
edited
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computerworld snippets:

# From Computerworld: ggplot2 code snippets

snippet myg_barplot_basic
	ggplot(${1:mydataframe}, aes(x=${2:myxcolname}, y=${3:myycolname})) + 
	  geom_bar(stat="identity")

snippet myg_barplot_basic_reorderXaxisByYvalue
	ggplot(${1:mydataframe}, aes(x=reorder(${2:myxcolname}, -${3:myycolname}), y=${3:myycolname})) + 
	  geom_bar(stat="identity")  

snippet myg_barplot_groupedByColor
	ggplot(${1:mydataframe}, aes(x=${2:myxcolname}, y=${3:myycolname}, fill=${4:mygroupcolname})) + 
	  geom_bar(stat="identity", position="dodge")

snippet myg_barplot_basic_barsSetOneColor
	ggplot(${1:mydataframe}, aes(x=${2:myxcolname}, y=${3:myycolname})) + 
	  geom_bar(fill="${4:mycolor}", stat="identity")

snippet myg_barplot_basic_bars_blue
	ggplot(${1:mydataframe}, aes(x=${2:myxcolname}, y=${3:myycolname})) + 
	  geom_bar(stat="identity", color = "black", fill="#0072B2")

snippet myg_barplot_barslabeled
	# Code from an R Graphics Cookbook recipe, by Winston Chang
	ggplot(data = ${1:mydataframe}, aes(x=${2:myxcolname}, y=${3:myycolname})) +
	  geom_bar(stat="identity", color = "black", fill="#0072B2") +
	  ggtitle("${4:My Headline}") +
	  xlab("${5:myXaxisname}") +
	  ylab("${6:myYaxisname}") +
	  theme_classic() +
	  geom_text(aes(label=${3:myycolname}), vjust=1.5, colour="white", position=position_dodge(.9), size=5)  +
	  theme(plot.title=element_text(size=24))  

snippet myg_barplot_barslabeled_reorderXaxisByYvalue
	# Code adapted from an R Graphics Cookbook recipe, by Winston Chang
	ggplot(${1:mydataframe}, aes(x=reorder(${2:myxcolname}, -${3:myycolname}), y=${3:myycolname})) + 
	  geom_bar(stat="identity", color = "black", fill="#0072B2") +
	  ggtitle("${4:myheadline}") +
	  xlab("${5:myXaxisname}") +
	  ylab("${6:myYaxisname}") +
	  theme_classic() +
	  geom_text(aes(label=${3:myycolname}), vjust=1.5, colour="white", position=position_dodge(.9), size=5)  +
	  theme(plot.title=element_text(size=24))  

snippet myg_barplot_grouped_withColorPaletteAndHeadline
	ggplot(data = ${1:mydataframe}, aes(x=${2:myXcolname}, y=${3:myYcolname}, fill=${4:mygroup/colorBycolname} )) +
	  geom_bar(stat="identity", position="dodge") +
	  scale_fill_brewer(palette="Dark2") +
	  ggtitle("${5:My Headline}") +
	  theme(plot.title=element_text(size=22))

snippet myg_scatterplot_basic
	ggplot(${1:mydataframe}, aes(x=${2:myxcolname}, y=${3:myycolname})) + 
	  geom_point()

snippet myg_scatterplot_setPointSize
	ggplot(${1:mydataframe}, aes(x=${2:myxcolname}, y=${3:myycolname})) + 
	  geom_point(size=${4:myPointSizeNumber})

snippet myg_scatterplot_setColorByDataValue
	ggplot(${1:mydataframe}, aes(x=${2:myxcolname}, y=${3:myycolname})) + 
	  geom_point(aes(color=${4:myColorBycolname})) + scale_color_gradient(low="${5:mylowcolor}", high="${6:myhighcolor}")

snippet myg_scatterplot_setColorBrewerPaletteByDataValue
	ggplot(${1:mydataframe}, aes(x=${2:myxcolname}, y=${3:myycolname})) + 
	  geom_point(aes(color=${4:myColorBycolname})) + scale_color_brewer(type="seq", palette="${5:mypalettechoice}")

snippet myg_scatterplot_groupAndAutoAnnotateByColor
	# requires package directlabels
	library("directlabels")
	myplot <- ggplot(${1:mydataframe}, aes(x=${2:myxcolname}, y=${3:myycolname}, color=${4:mygroupingcol})) + geom_point()
	direct.label(myplot, "smart.grid")

snippet myg_scatterplot_addJitter
	 + geom_point(position="jitter")

snippet myg_line_basic
	ggplot(${1:mydataframe}, aes(x=${2:myxcolname}, y=${3:myycolname})) + 
	  geom_line()
	  
snippet myg_line_linesByCategory
	ggplot(${1:mydataframe}, aes(x=${2:myxcolname}, y=${3:myycolname})) + 
	  geom_line(aes(color=${4:mycolnameForEachLine}))	  

snippet myg_line_goupAndAutoAnnotateByColor
	# requires package directlabels; code via https://goo.gl/jpSDtw 
	library("directlabels")
	myplot <- ggplot(${1:mydataframe}, aes(x=${2:myxcolname}, y=${3:myycolname})) + geom_line(aes(color=${4:mycolnameForEachLine}))
	direct.label(myplot, list(last.points, hjust = 0.7, vjust = 1))

snippet myg_add_horizontalLine
	 + geom_hline(yintercept=${1:theYintercept})

snippet myg_add_vertictalLine
	 + geom_vline(xintercept=${1:theXintercept})

snippet myg_headline_setTextAndSize
	 + ggtitle("${1:myheadlinetext}") + 
	  theme(plot.title = element_text(size = ${2:myintegerPointSize}))

snippet myg_headline_makeBold
	 + theme(plot.title = element_text(face="bold"))

snippet myg_Xaxis_setTitle
	 + xlab("${1:My x-axis title text}")

snippet myg_Yaxis_setTitle
	 + ylab("${1:My y-axis title text}")

snippet myg_Xaxis_setCatVariableLabels
	 + scale_x_discrete(labels=${1:myvectoroflabels})

snippet myg_Yaxis_setContVariableLabels
	 + scale_y_continuous(breaks=${1:myvectorofbreaks})

snippet myg_Yaxis_setLimits
	 + ylim(${1:myYmin}, ${2:myYmax})

snippet myg_Xaxis_rotateLabels45degrees
	 + theme(axis.text.x= element_text(angle=45, hjust = 1.3, vjust = 1.2))

snippet myg_Yaxis_rotateTitle
	 + theme(axis.title.y = element_text(angle = 0))

snippet myg_legend_off
	 + theme(legend.position = "none")

snippet myg_multiplots_1factor_2columns
	 + facet_wrap(~ ${1:mycolname}, ncol=2)

snippet myg_multiplots_2factors_2columns
	 + facet_wrap(${1:mycolname1} ~ ${2:mycolname2}, ncol=2)

snippet myg_multiplots_1factor_2rows
	 + facet_wrap(~ ${1:mycolname}, nrow=2)

snippet myg_multiplots_2factors_2rows
	 + facet_wrap(${1:mycolname1} ~ ${2:mycolname2}, nrow=2)

snippet myg_multiplots_2factors
	  +  facet_grid(${1:mycolname1} ~ ${2:mycolname2})
	  
snippet myg_multiplots_unrelatedPlots_1column
	# gridExtra package required; enter any number of existing plots, each separated by a comma
	gridExtra::grid.arrange(${1:plot1}, ${2:plot2}, ${3:plot3})	
	
snippet myg_multiplots_unrelatedPlots_SetNumColumns
	# gridExtra package required; enter any number of existing plots, each separated by a comma
	gridExtra::grid.arrange(${1:plot1}, ${2:plot2}, ${3:plot3}, ncol=${4:numcolumns})		  

snippet myg_annotate_addByXYposition
	 + annotate("text", x=${1:myxposition}, y=${2:myyposition}, label="${3:My text}")

snippet myg_corrplot
	# requires package corrplot
	mycorrelationmatrix <- cor(${1:mymatrix})
	col <- colorRampPalette(c("#BB4444", "#EE9988", "#FFFFFF", "#77AADD", "#4477AA"))
	corrplot::corrplot(mycorrelationmatrix, method="shade", shade.col=NA, tl.col="black", tl.srt=45, col=col(200), addCoef.col="black")  

snippet myg_interactive_histogram
	# requires package ggvis
	library(ggvis)
	${1:mydataframe} %>% 
	  ggvis(x = ~${2:mydatacolumn}, fill := "gray") %>% 
	  layer_histograms(width =  input_slider(min=${3:mysliderMinValue}, max=${4:mysliderMax}, value= ${5:mysliderStartingValue}, label = "Bin Width")) 
	  
# end Computerworld ggplot2 code snippets

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