{"id":23715,"date":"2024-01-08T17:37:49","date_gmt":"2024-01-08T09:37:49","guid":{"rendered":"http:\/\/www.biocloudservice.com\/wordpress\/?p=23715"},"modified":"2024-01-08T17:37:51","modified_gmt":"2024-01-08T09:37:51","slug":"%e5%a4%9a%e6%b8%a0%e9%81%93%e7%bb%98%e5%88%b6%e5%b0%8f%e6%8f%90%e7%90%b4%e5%9b%be%ef%bc%8c%e5%ae%9e%e7%8e%b0%e4%bd%9c%e5%9b%be%e8%87%aa%e7%94%b1","status":"publish","type":"post","link":"http:\/\/www.biocloudservice.com\/wordpress\/?p=23715","title":{"rendered":"\u591a\u6e20\u9053\u7ed8\u5236\u5c0f\u63d0\u7434\u56fe\uff0c\u5b9e\u73b0\u4f5c\u56fe\u81ea\u7531"},"content":{"rendered":"

\u6587\u7ae0\u4e2d\u51fa\u73b0\u5f88\u591a\u5c0f\u63d0\u7434\u56fe\u548c\u76d2\u6027\u56fe\uff0c\u5373\u4f53\u73b0\u4e86\u7f8e\u89c2\u6027\u53c8\u5177\u6709\u5f88\u5f3a\u7684\u53ef\u8bfb\u6027\u3002<\/p>\n

\u672c\u6587\u6c47\u603b\u4e86\u5f88\u591a\u5236\u4f5c\u5c0f\u63d0\u7434\u56fe\u7684\u65b9\u6cd5\u53ef\u4ee5\u4f9b\u9009\u62e9\uff0c\u603b\u6709\u4e00\u4e2a\u9002\u5408\u4f60\u7684\u65b9\u6cd5\u3002<\/p>\n

\u4ec0\u4e48\u662f\u5c0f\u63d0\u7434\u56fe\uff0c\u751f\u7269\u5b66\u610f\u4e49\u662f\u4ec0\u4e48\uff1f<\/h2>\n

\u4e00\u822c\u6765\u8bf4\u5c0f\u63d0\u7434\u56fe\u662f\u4e00\u79cd\u7ed8\u5236\u8fde\u7eed\u578b\u6570\u636e\u7684\u65b9\u6cd5\uff0c\u5728\u5c0f\u63d0\u7434\u56fe\u4e2d\u65e2\u53ef\u4ee5\u770b\u5230\u4e0e\u7bb1\u7ebf\u56fe\u4e2d\u4e00\u6837\u7684\u76f8\u540c\u7684\u4fe1\u606f\uff0c\u5305\u62ec\u4e2d\u4f4d\u6570\uff08\u4e2d\u95f4\u7684\u4e00\u4e2a\u5c0f\u767d\u70b9\uff09\uff0c\u56db\u5206\u4f4d\u6570\u8303\u56f4\uff08\u4e2d\u95f4\u7684\u9ed1\u8272\u7684\u6761\uff09\uff0c\u7b2c\u4e00\u56db\u5206\u4f4d\u6570\u548c\u7b2c\u4e09\u56db\u5206\u4f4d\u6570\uff0c\u8fd8\u53ef\u4ee5\u89c2\u5bdf\u5230\u6570\u6570\u636e\u7684\u6574\u4f53\u7684\u6570\u636e\u5206\u5e03\u72b6\u6001\u3002<\/p>\n

\"IMG_256\"<\/p>\n

\u6709\u4e86\u8fdb\u4e00\u6b65\u7684\u4e86\u89e3\u4e4b\u540e\uff0c\u53ef\u4ee5\u5c1d\u8bd5\u7ed8\u5236\u5c0f\u63d0\u7434\u56fe\u5566\uff5e<\/p>\n

\u7528vioplot\u5305\u7ed8\u5236\u5c0f\u63d0\u7434\u56fe<\/h2>\n

#\u5b89\u88c5\u52a0\u8f7d\u5b89\u88c5\u5305<\/p>\n

install.packages(“vioplot”)<\/p>\n

library(vioplot)<\/p>\n

#\u5229\u7528R\u4e2d\u81ea\u5e26\u7684iris\u6765\u5b66\u4e60\u5c0f\u63d0\u7434\u7684\u7ed8\u5236<\/p>\n

df <- data.frame(iris)<\/p>\n

#\u8fd9\u6837\u7ed8\u5236\u51fa\u57fa\u7840\u7684\u5c0f\u63d0\u7434\u56fe\u5f62<\/p>\n

vioplot(Sepal.Length~Species,data = df,main =”Speal Length”,col = c(“lightgreen”,”lightblue”,”pink”))<\/p>\n

#\u6dfb\u52a0\u56fe\u4f8b<\/p>\n

legend(“topleft”,legend=c(“setosa”,”versicolor”,”virginica”),fill = c(“lightgreen”,”lightblue”,”pink”),cex = 0.7)<\/p>\n

\"\u622a\u5c4f2023-06-12<\/p>\n

\u5728\u5c1d\u8bd5\u4e00\u4e2a\u5173\u4e8eR\u4e2d\u94bb\u77f3\u7684\u6570\u636e\uff5e<\/p>\n

#\u94bb\u77f3<\/p>\n

df1 <- data.frame(diamonds)<\/p>\n

head(df1)<\/p>\n

#\u7ed8\u5236\u94bb\u77f3\u7684\u4ef7\u683c\u662f\u4e0ecut\u3001color\u548cclarity\u4e09\u4e2a\u4e0d\u540c\u7ef4\u5ea6\u4e2d\u7684\u6570\u636e\u72b6\u6001<\/p>\n

a <- length(levels(df1$cut))<\/p>\n

b <- length(levels(df1$color))<\/p>\n

c <- length(levels(df1$clarity))<\/p>\n

num = max(a,b,c)<\/p>\n

#\u6700\u591a\u67098\u4e2a\u753b\u677f\uff0c\u9009\u62e9\u753b\u677f<\/p>\n

install.packages(“RColorBrewer”)<\/p>\n

library(RColorBrewer)<\/p>\n

col <- RColorBrewer::brewer.pal(8,”Accent”)<\/p>\n

col<\/p>\n

vioplot(price~cut,data = diamonds,col = col)<\/p>\n

\"Rplot03\"<\/p>\n

\u7528ggpubr\u6765\u7ed8\u5236\u5c0f\u63d0\u7434\u56fe<\/h2>\n

\u5728\u4ee5\u524d\u6211\u4eec\u7528ggpubr\u7ed8\u5236\u8fc7\u76f8\u5173\u6027\u5206\u6790\u56fe\uff0c\u8fd9\u4e2a\u4e07\u80fd\u7684\u7ed8\u56fe\u5305\u4e5f\u53ef\u4ee5\u7528\u6765\u7ed8\u5236\u76f8\u5e94\u7684\u5c0f\u63d0\u7434\u56fe\u3002<\/p>\n

comparisons <- list(c(“setosa”, “versicolor”), c(“versicolor”, “virginica”), c(“setosa”,”virginica”))<\/p>\n

library(ggpubr)<\/p>\n

ggviolin(iris, x = “Species”, y = “Sepal.Length”,<\/p>\n

fill = “Species”, #xy\u8f74\u5b9a\u4e49\uff0c\u586b\u5145\u6620\u5c04\u5230\u7269\u79cd\u4e0a<\/p>\n

palette = c(“lancet”),#\u8272\u5757\u7684\u9009\u62e9\uff0c\u8fd9\u91cc\u63d0\u4f9b\u4e86”npg”, “aaas”, “lancet”, “jco”, “ucscgb”, “uchicago”, “simpsons” and “rickandmorty”\u7b49<\/p>\n

add = “boxplot”,#\u6dfb\u52a0\u7bb1\u7ebf\u56fe\u5728\u56fe\u4e2d\uff0c\u8fd8\u53ef\u4ee5\u9009\u62e9”none”, “dotplot”, “jitter”, “boxplot”, “point”, “mean”, “mean_se”, “mean_sd”, “mean_ci”, “mean_range”, “median”, “median_iqr”, “median_hilow”, “median_q1q3”, “median_mad”, “median_range”\u7b49\u6765\u67e5\u770b\u56fe\u4e2d\u7684\u4e00\u4e9b\u7ec6\u8282\u90e8\u5206<\/p>\n

add.params = list(fill = “white”),#\u586b\u5145\u4e3a\u767d\u8272<\/p>\n

order = c(“virginica”,”versicolor”,”setosa”), error.plot = “errorbar”) + stat_compare_means(comparisons = comparisons)<\/p>\n

#\u6700\u540e\u7528stat_compare_means\u51fd\u6570\u5b9e\u73b0\u4e24\u4e24\u6bd4\u8f83\u7684\u7530\u95f4p\u503c\u7684\u64cd\u4f5c\u3002<\/p>\n

\"\u622a\u5c4f2023-06-12<\/p>\n

\u7528ggplot\u7ed8\u5236\u5c0f\u63d0\u7434\u56fe<\/h4>\n

\u76f8\u6bd4\u4e8e\u524d\u9762\u7684\u4e24\u79cdggplot\u7ed8\u5236\u5c0f\u63d0\u7434\u56fe\u8f83\u4e3a\u9ebb\u70e6\u4e00\u4e0b\uff0c\u4f46\u662f\u786e\u53ef\u4ee5\u6ee1\u8db3\u5f88\u591a\u7cbe\u7ec6\u7684\u9700\u6c42\u3002ggplot\u7ed8\u56fe\u5c31\u50cf\u662f\u6211\u4eec\u7ed8\u753b\u4e00\u6837\uff0c\u4e00\u6b65\u4e00\u6b65\u7684\u6dfb\u52a0\u5373\u53ef\uff0c\u90a3\u8ddf\u968f\u5c0f\u679c\u7684\u6b65\u4f10\u4e00\u8d77\u6765\u64cd\u4f5c\u4e00\u4e0b\u5427\uff5e<\/p>\n

#\u7ed8\u5236\u4e00\u4e2a\u57fa\u672c\u7684\u56fe\u5c42<\/p>\n

p <- ggplot(ToothGrowth, aes(x = dose, y = len))<\/p>\n

#\u57fa\u7840<\/p>\n

p + geom_violin()<\/p>\n

#\u4e0d\u4fee\u526a\u5c0f\u63d0\u7434\u7684\u5c3e\u90e8<\/p>\n

p + geom_violin(trim = FALSE, fill = “steelblue”)<\/p>\n

#\u6dfb\u52a0\u7edf\u8ba1\u503c\uff0cfun=mean\u662f\u5747\u503c\uff0c\u8fd8\u53ef\u4ee5\u662fmedian<\/p>\n

p + geom_violin(trim = FALSE) +stat_summary(fun= mean, geom = “point”,<\/p>\n

shape = 23, size = 2, color = “blue”)<\/p>\n

#\u6dfb\u52a0\u7bb1\u7ebf\u56fe<\/p>\n

p + geom_violin(trim = FALSE) +<\/p>\n

geom_boxplot(width = 0.2)<\/p>\n

#\u586b\u5145\u989c\u8272<\/p>\n

p + geom_violin(aes(fill = dose), trim = FALSE)+geom_boxplot(width = 0.2)<\/p>\n

\"\u622a\u5c4f2023-06-12<\/p>\n

\u9664\u4e86\u4ee5\u4e0a\u7ed8\u5236\u7684\u65b9\u6cd5\u610f\u5916\u8fd8\u6709\u5f88\u591a\u5c0f\u5de5\u5177\u5df2\u7ecf\u5b9e\u73b0\u4e86\u5c0f\u63d0\u7434\u7684\u7ed8\u5236\uff0c\u4f8b\u5982\uff1ahttps:\/\/www.bioinformatics.com.cn\/plot_basic_vertical_horizontal_violin_plot_068<\/a><\/p>\n

\u6211\u4eec\u5728\u505a\u79d1\u7814\u7684\u65f6\u5019\u9700\u8981\u7528\u5404\u79cd\u4e0d\u540c\u7684\u56fe\u5f62\u6765\u5c55\u793a\u6211\u4eec\u7684\u6570\u636e\uff0c\u5408\u7406\u7684\u9009\u62e9\u56fe\u5f62\uff0c\u5408\u7406\u9009\u62e9\u7b80\u4fbf\u6709\u6548\u7684\u7ed8\u56fe\u65b9\u6cd5\u90fd\u662f\u6211\u4eec\u503c\u5f97\u8003\u8651\u7684\u3002\u901a\u8fc7\u603b\u7ed3\u4e0d\u540c\u7684\u7ed8\u56fe\u65b9\u6cd5\u4e5f\u662f\u6211\u4eec\u5b66\u4e60\u597d\u751f\u4fe1\u7684\u5fc5\u8981\u4e00\u6b65\uff0c\u5c0f\u679c\u548c\u4f60\u4eec\u4e00\u8d77\u52a0\u6cb9\uff5e<\/p>\n

\u901a\u8fc7\u4ee5\u4e0a\u7684\u64cd\u4f5c\uff0c\u76f8\u4fe1\u4f60\u5bf9\u4e8e\u5c0f\u63d0\u7434\u56fe\u7684\u7ed8\u5236\u4ee5\u53ca\u4e00\u4e9b\u57fa\u7840\u7684\u539f\u7406\u6709\u4e86\u4e00\u5b9a\u7684\u4e86\u89e3\uff0c\u4e5f\u4e00\u5b9a\u9009\u62e9\u4e86\u4e00\u4e2a\u9002\u5408\u4f60\u7684\u65b9\u6cd5\u3002\u5f53\u7136\u8fd9\u91cc\u53ea\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u5f15\u5bfc\u4f5c\u7528\uff0c\u6bcf\u79cd\u5305\u6216\u662f\u65b9\u6cd5\u4e2d\u90fd\u6709\u5f88\u591a\u53c2\u6570\uff0c\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u7ed8\u5236\u51fa\u66f4\u52a0\u7f8e\u89c2\u7684\u56fe\u5f62\uff0c\u503c\u5f97\u5927\u5bb6\u7ec6\u7ec6\u63a2\u7d22\u3002<\/p>\n

\u597d\u4e86\uff0c\u8fd9\u6837\u6211\u4eec\u5c0f\u63d0\u7434\u56fe\u5c31\u4ecb\u7ecd\u5230\u8fd9\u91cc\u4e86\u3002\u5c0f\u4f19\u4f34\u4eec\u5982\u679c\u6709\u4ec0\u4e48\u95ee\u9898\u5c31\u548c\u5c0f\u679c\u8ba8\u8bba\u5427\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"

\u6587\u7ae0\u4e2d\u51fa\u73b0\u5f88\u591a\u5c0f\u63d0\u7434\u56fe\u548c\u76d2\u6027\u56fe\uff0c\u5373\u4f53\u73b0\u4e86\u7f8e\u89c2\u6027\u53c8\u5177\u6709\u5f88\u5f3a\u7684\u53ef\u8bfb\u6027\u3002 \u672c\u6587\u6c47\u603b\u4e86\u5f88\u591a\u5236\u4f5c\u5c0f\u63d0\u7434\u56fe\u7684\u65b9\u6cd5\u53ef\u4ee5\u4f9b\u9009\u62e9 […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":""},"categories":[1],"tags":[],"jetpack_featured_media_url":"","_links":{"self":[{"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/23715"}],"collection":[{"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=23715"}],"version-history":[{"count":1,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/23715\/revisions"}],"predecessor-version":[{"id":23721,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/23715\/revisions\/23721"}],"wp:attachment":[{"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=23715"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=23715"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=23715"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}