いくつかのトピックを検索し、ヴァイオリン プロットをプロットするという主なアイデアを見つけましたが、それらのスクリプトを私の中で組み合わせると (以下に示します)、結果は受け入れられません。バー プロットをバイオリン プロットに変換するよりも、最初からバイオリン プロットを作成する方が簡単なようです。
Q:バー プロット スクリプトがあり、バイオリン プロット (これと同じ)に変換しようとしています。
この点で私を助けてくれませんか？(よろしくお願いします)
dat <- data.frame(
FunctionClass = factor(c("A", "B", "C", "D", "E", "F", "G", "H", "I", "J", "K", "L", "M", "N", "O", "P", "Q", "R", "S", "T", "U", "V", "W", "Y", "Z"), levels=c("A", "B", "C", "D", "E", "F", "G", "H", "I", "J", "K", "L", "M", "N", "O", "P", "Q", "R", "S", "T", "U", "V", "W", "Y", "Z")),
legend = c("A: RNA processing and modification", "B: Chromatin structure and dynamics", "C: Energy production and conversion", "D: Cell cycle control, cell division, chromosome partitioning", "E: Amino acid transport and metabolism", "F: Nucleotide transport and metabolism", "G: Carbohydrate transport and metabolism", "H: Coenzyme transport and metabolism", "I: Lipid transport and metabolism", "J: Translation, ribosomal structure and biogenesis", "K: Transcription", "L: Replication, recombination and repair", "M: Cell wall/membrane/envelope biogenesis", "N: Cell motility", "O: Posttranslational modification, protein turnover, chaperones", "P: Inorganic ion transport and metabolism", "Q: Secondary metabolites biosynthesis, transport and catabolism", "R: General function prediction only", "S: Function unknown", "T: Signal transduction mechanisms", "U: Intracellular trafficking, secretion, and vesicular transport", "V: Defense mechanisms", "W: Extracellular structures", "Y: Nuclear structure", "Z: Cytoskeleton"),
Frequency = c(360,391,897,1558,1168,448,1030,536,732,1292,2221,2098,789,117,1744,732,437,5162,1251,2191,603,216,2,14,739)
)
library(ggplot2)
ggplot(data=dat, aes(x=FunctionClass, y=Frequency, fill=legend)) +
geom_bar(stat="identity", position=position_dodge(), colour="black")
scale_colour_gradientn(colours=rainbow(36))