{"id":439,"date":"2023-04-20T07:48:06","date_gmt":"2023-04-20T07:48:06","guid":{"rendered":"https:\/\/yunshangtulv.com.cn\/?p=439"},"modified":"2023-04-20T07:51:11","modified_gmt":"2023-04-20T07:51:11","slug":"r%e8%af%ad%e8%a8%80%e8%bf%9b%e9%98%b6%e7%bb%98%e5%9b%be%ef%bc%9a%e7%81%ab%e5%b1%b1%e5%9b%be","status":"publish","type":"post","link":"https:\/\/yunshangtulv.com.cn\/?p=439","title":{"rendered":"R\u8bed\u8a00\u8fdb\u9636\u7ed8\u56fe\uff1a\u706b\u5c71\u56fe"},"content":{"rendered":"<h2>\u5e38\u89c4\u706b\u5c71\u56fe<\/h2>\n<div class=\"group w-full text-gray-800 dark:text-gray-100 border-b border-black\/10 dark:border-gray-900\/50 bg-gray-50 dark:bg-[#444654]\">\n<div class=\"text-base gap-4 md:gap-6 md:max-w-2xl lg:max-w-xl xl:max-w-3xl p-4 md:py-6 flex lg:px-0 m-auto\">\n<div class=\"relative flex w-[calc(100%-50px)] flex-col gap-1 md:gap-3 lg:w-[calc(100%-115px)]\">\n<div class=\"flex flex-grow flex-col gap-3\">\n<div class=\"min-h-[20px] flex flex-col items-start gap-4 whitespace-pre-wrap\">\n<div class=\"markdown prose w-full break-words dark:prose-invert light\">\n<p>\u4e0b\u9762\u7684\u793a\u4f8b\u4e2d\uff0c\u6211\u5c06\u521b\u5efa\u4e00\u4e2a\u865a\u6784\u7684\u6570\u636e\u96c6\uff0c\u5c55\u793a\u524d\u51e0\u884c\uff0c\u5e76\u7ed8\u5236\u4e00\u5f20\u7f8e\u89c2\u3001\u8be6\u5c3d\u7684\u706b\u5c71\u56fe\u3002\u6211\u4eec\u5c06\u4f7f\u7528<code>ggplot2<\/code>\u5305\u521b\u5efa\u706b\u5c71\u56fe\u3002\u8bf7\u6ce8\u610f\uff0c\u8fd9\u4e2a\u793a\u4f8b\u4f7f\u7528\u4e86\u968f\u673a\u751f\u6210\u7684\u6570\u636e\uff0c\u5b9e\u9645\u7814\u7a76\u4e2d\u5e94\u4f7f\u7528\u771f\u5b9e\u6570\u636e\u3002<\/p>\n<div class=\"bg-black rounded-md mb-4\">\n<div class=\"p-4 overflow-y-auto\">\n<pre class=\"corepress-code-pre\"><code>\r\n\r\n# \u5b89\u88c5\u5e76\u52a0\u8f7d\u6240\u9700\u7684\u5305\r\nif (!requireNamespace(\"ggplot2\", quietly = TRUE))\r\ninstall.packages(\"ggplot2\")\r\nlibrary(ggplot2)# \u793a\u4f8b\u6570\u636e\r\nset.seed(123) # \u8bbe\u7f6e\u968f\u673a\u6570\u79cd\u5b50\uff0c\u4ee5\u4fbf\u751f\u6210\u53ef\u91cd\u73b0\u7684\u6570\u636e\r\ngene_ids &lt;- paste0(\"Gene\", 1:1000)\r\nlog2_fold_changes &lt;- rnorm(1000, mean = 0, sd = 1)\r\np_values &lt;- runif(1000, min = 0, max = 1)\r\n\r\n# \u521b\u5efa\u6570\u636e\u6846\r\nvolcano_data &lt;- data.frame(GeneID = gene_ids,\r\nLog2FoldChange = log2_fold_changes,\r\nPValue = p_values)\r\n\r\n# \u5c55\u793a\u524d\u51e0\u884c\u6570\u636e\r\nhead(volcano_data)\r\n\r\n# \u8ba1\u7b97-log10(PValue)\r\nvolcano_data$NegLog10PValue &lt;- -log10(volcano_data$PValue)\r\n\r\n# \u6839\u636e\u663e\u8457\u6027\u548c\u5dee\u5f02\u8868\u8fbe\u9608\u503c\u5bf9\u57fa\u56e0\u8fdb\u884c\u5206\u7ec4\r\nthreshold_p_value &lt;- 0.05\r\nthreshold_log2_fold_change &lt;- 1\r\n\r\nvolcano_data$Group &lt;- \"Not significant\"\r\nvolcano_data$Group[volcano_data$PValue &lt; threshold_p_value &amp;\r\nabs(volcano_data$Log2FoldChange) &gt; threshold_log2_fold_change] &lt;- \"Significant\"\r\n\r\n# \u7ed8\u5236\u706b\u5c71\u56fe\r\np &lt;- ggplot(volcano_data, aes(x = Log2FoldChange, y = NegLog10PValue, color = Group)) +\r\ngeom_point(alpha = 0.8, size = 1.5) +\r\nscale_color_manual(values = c(\"Not significant\" = \"gray\", \"Significant\" = \"red\")) +\r\ngeom_hline(yintercept = -log10(threshold_p_value), linetype = \"dashed\", color = \"blue\") +\r\ngeom_vline(xintercept = c(-threshold_log2_fold_change, threshold_log2_fold_change), linetype = \"dashed\", color = \"blue\") +\r\nxlab(\"log2(Fold Change)\") +\r\nylab(\"-log10(P-Value)\") +\r\nggtitle(\"\u706b\u5c71\u56fe\") +\r\ntheme_minimal() +\r\ntheme(legend.position = \"bottom\")\r\n\r\n# \u663e\u793a\u56fe\u5f62\r\nprint(p)\r\n\r\n# \u4fdd\u5b58\u4e3aPDF\u6587\u4ef6\r\nggsave(\"volcano_plot.pdf\", plot = p, width = 10, height = 7, units = \"in\")<\/code><\/pre>\n<p>&nbsp;<\/p>\n<\/div>\n<\/div>\n<p>\u89e3\u91ca\uff1a<\/p>\n<ol>\n<li>\u9996\u5148\uff0c\u6211\u4eec\u751f\u6210\u4e86\u4e00\u4e2a\u5305\u542b1000\u4e2a\u57fa\u56e0\u7684\u865a\u6784\u6570\u636e\u96c6\uff0c\u6bcf\u4e2a\u57fa\u56e0\u5177\u6709log2(\u500d\u6570\u53d8\u5316)\u548cP\u503c\u3002\u5b9e\u9645\u7814\u7a76\u4e2d\uff0c\u8fd9\u4e9b\u503c\u901a\u5e38\u6765\u81ea\u5dee\u5f02\u8868\u8fbe\u57fa\u56e0\u5206\u6790\u3002<\/li>\n<li>\u6211\u4eec\u4e3a\u6570\u636e\u96c6\u6dfb\u52a0\u4e86\u4e00\u4e2a\u65b0\u5217\uff0c\u8868\u793aP\u503c\u7684\u8d1f\u5bf9\u6570\u503c\uff08-log10(PValue)\uff09\u3002<\/li>\n<li>\u6211\u4eec\u5b9a\u4e49\u4e86\u663e\u8457\u6027\u548c\u5dee\u5f02\u8868\u8fbe\u9608\u503c\uff0c\u5e76\u6839\u636e\u8fd9\u4e9b\u9608\u503c\u5bf9\u57fa\u56e0\u8fdb\u884c\u4e86\u5206\u7ec4\u3002\u5728\u6b64\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528P\u503c\u5c0f\u4e8e0.05\u548clog2(\u500d\u6570\u53d8\u5316)\u7684\u7edd\u5bf9\u503c\u5927\u4e8e1\u4f5c\u4e3a\u663e\u8457\u6027\u548c\u5dee\u5f02\u8868\u8fbe\u9608\u503c\u3002<\/li>\n<li>\u4f7f\u7528<code>ggplot2<\/code>\u5305\u7ed8\u5236\u706b\u5c71\u56fe\u3002\u6211\u4eec\u6839\u636e\u57fa\u56e0\u6240\u5c5e\u7684\u5206\u7ec4\uff08\u663e\u8457\u6216\u975e\u663e\u8457\uff09\u7ed9\u6563\u70b9\u4e0a\u8272\u3002\u975e\u663e\u8457\u57fa\u56e0\u4e3a\u7070\u8272\uff0c\u663e\u8457\u57fa\u56e0\u4e3a\u7ea2\u8272\u3002<\/li>\n<li>\u6dfb\u52a0\u6c34\u5e73\u548c\u5782\u76f4\u865a\u7ebf\uff0c\u8868\u793a\u663e\u8457\u6027\u548c\u5dee\u5f02\u8868\u8fbe\u9608\u503c\u3002\u84dd\u8272\u6c34\u5e73\u865a\u7ebf\u8868\u793a-log10(P\u503c)\u7684\u9608\u503c\uff0c\u84dd\u8272\u5782\u76f4\u865a\u7ebf\u8868\u793alog2(\u500d\u6570\u53d8\u5316)\u7684\u9608\u503c\u3002<\/li>\n<li>\u4f7f\u7528<code>theme_minimal()<\/code>\u8bbe\u7f6e\u56fe\u5f62\u4e3b\u9898\u4e3a\u7b80\u7ea6\u98ce\u683c\uff0c\u5e76\u5c06\u56fe\u4f8b\u4f4d\u7f6e\u8bbe\u7f6e\u5728\u5e95\u90e8\u3002<\/li>\n<li>\u4f7f\u7528<code>ggsave()<\/code>\u51fd\u6570\u5c06\u706b\u5c71\u56fe\u4fdd\u5b58\u4e3aPDF\u6587\u4ef6\uff0c\u6307\u5b9a\u5bbd\u5ea6\u4e3a10\u82f1\u5bf8\uff0c\u9ad8\u5ea6\u4e3a7\u82f1\u5bf8\u3002<\/li>\n<\/ol>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"group w-full text-gray-800 dark:text-gray-100 border-b border-black\/10 dark:border-gray-900\/50 bg-gray-50 dark:bg-[#444654]\">\n<div class=\"text-base gap-4 md:gap-6 md:max-w-2xl lg:max-w-xl xl:max-w-3xl p-4 md:py-6 flex lg:px-0 m-auto\">\n<div class=\"relative flex w-[calc(100%-50px)] flex-col gap-1 md:gap-3 lg:w-[calc(100%-115px)]\">\n<div class=\"flex flex-grow flex-col gap-3\">\n<div class=\"min-h-[20px] flex flex-col items-start gap-4 whitespace-pre-wrap\">\n<div class=\"markdown prose w-full break-words dark:prose-invert light\">\n<ol start=\"3\"><\/ol>\n<p>\u8fd9\u4e2a\u793a\u4f8b\u5c55\u793a\u4e86\u5982\u4f55\u4f7f\u7528\u865a\u6784\u6570\u636e\u521b\u5efa\u706b\u5c71\u56fe\u3002\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u4f60\u9700\u8981\u4f7f\u7528\u5b9e\u9645\u7684\u5dee\u5f02\u8868\u8fbe\u57fa\u56e0\u6570\u636e\u6765\u751f\u6210\u706b\u5c71\u56fe\u3002\u706b\u5c71\u56fe\u53ef\u7528\u4e8e\u4e00\u76ee\u4e86\u7136\u5730\u5c55\u793a\u5927\u91cf\u57fa\u56e0\u7684\u8868\u8fbe\u53d8\u5316\u548c\u663e\u8457\u6027\u6c34\u5e73\uff0c\u5e2e\u52a9\u7814\u7a76\u4eba\u5458\u8bc6\u522b\u6f5c\u5728\u7684\u751f\u7269\u5b66\u4e0a\u91cd\u8981\u7684\u57fa\u56e0\u3002\u4e3a\u4e86\u4f7f\u706b\u5c71\u56fe\u770b\u8d77\u6765\u66f4\u7f8e\u89c2\uff0c\u6211\u4eec\u53ef\u4ee5\u8c03\u6574\u70b9\u7684\u6837\u5f0f\u3001\u5927\u5c0f\u548c\u989c\u8272\u3002\u6b64\u5916\uff0c\u6211\u4eec\u8fd8\u53ef\u4ee5\u8c03\u6574\u8f74\u7684\u6807\u9898\u548c\u56fe\u5f62\u6807\u9898\u7684\u5b57\u4f53\u5927\u5c0f\uff0c\u4ee5\u53ca\u4f18\u5316\u5750\u6807\u8f74\u523b\u5ea6\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"group w-full text-gray-800 dark:text-gray-100 border-b border-black\/10 dark:border-gray-900\/50 bg-gray-50 dark:bg-[#444654]\">\n<div class=\"text-base gap-4 md:gap-6 md:max-w-2xl lg:max-w-xl xl:max-w-3xl p-4 md:py-6 flex lg:px-0 m-auto\">\n<div class=\"relative flex w-[calc(100%-50px)] flex-col gap-1 md:gap-3 lg:w-[calc(100%-115px)]\">\n<div class=\"flex flex-grow flex-col gap-3\">\n<div class=\"min-h-[20px] flex flex-col items-start gap-4 whitespace-pre-wrap\">\n<div class=\"markdown prose w-full break-words dark:prose-invert light\">\n<p>\u4e0b\u9762\u662f\u4e00\u4e2a\u4fee\u6539\u540e\u7684\u706b\u5c71\u56fe\u793a\u4f8b\uff1a<\/p>\n<div class=\"bg-black rounded-md mb-4\"><\/div>\n<pre class=\"corepress-code-pre\"><code>\r\n\r\n# \u52a0\u8f7d\u6240\u9700\u7684\u5305\r\nlibrary(ggplot2)# \u793a\u4f8b\u6570\u636e\r\nset.seed(123) # \u8bbe\u7f6e\u968f\u673a\u6570\u79cd\u5b50\uff0c\u4ee5\u4fbf\u751f\u6210\u53ef\u91cd\u73b0\u7684\u6570\u636e\r\ngene_ids &lt;- paste0(\"Gene\", 1:1000)\r\nlog2_fold_changes &lt;- rnorm(1000, mean = 0, sd = 1.5)\r\np_values &lt;- runif(1000, min = 0, max = 1)\r\n\r\n# \u521b\u5efa\u6570\u636e\u6846\r\nvolcano_data &lt;- data.frame(GeneID = gene_ids,\r\nLog2FoldChange = log2_fold_changes,\r\nPValue = p_values)\r\n\r\n# \u8ba1\u7b97-log10(PValue)\r\nvolcano_data$NegLog10PValue &lt;- -log10(volcano_data$PValue)\r\n\r\n# \u6839\u636e\u663e\u8457\u6027\u548c\u5dee\u5f02\u8868\u8fbe\u9608\u503c\u5bf9\u57fa\u56e0\u8fdb\u884c\u5206\u7ec4\r\nthreshold_p_value &lt;- 0.05\r\nthreshold_log2_fold_change &lt;- 1\r\n\r\nvolcano_data$Group &lt;- \"Not significant\"\r\nvolcano_data$Group[volcano_data$PValue &lt; threshold_p_value &amp;\r\nabs(volcano_data$Log2FoldChange) &gt; threshold_log2_fold_change] &lt;- \"Significant\"\r\n\r\n# \u7ed8\u5236\u706b\u5c71\u56fe\r\np &lt;- ggplot(volcano_data, aes(x = Log2FoldChange, y = NegLog10PValue, color = Group)) +\r\ngeom_point(alpha = 0.8, size = 2) +\r\nscale_color_manual(values = c(\"Not significant\" = \"darkgray\", \"Significant\" = \"darkred\")) +\r\ngeom_hline(yintercept = -log10(threshold_p_value), linetype = \"dashed\", color = \"dodgerblue\") +\r\ngeom_vline(xintercept = c(-threshold_log2_fold_change, threshold_log2_fold_change), linetype = \"dashed\", color = \"dodgerblue\") +\r\nxlab(\"log2(Fold Change)\") +\r\nylab(\"-log10(P-Value)\") +\r\nggtitle(\"\u706b\u5c71\u56fe\") +\r\ntheme_minimal() +\r\ntheme(legend.position = \"bottom\",\r\naxis.title = element_text(size = 14),\r\nplot.title = element_text(size = 16, hjust = 0.5),\r\naxis.text = element_text(size = 12))\r\n\r\n# \u663e\u793a\u56fe\u5f62\r\nprint(p)\r\n\r\n# \u4fdd\u5b58\u4e3aPDF\u6587\u4ef6\r\nggsave(\"volcano_plot_improved.pdf\", plot = p, width = 10, height = 7, units = \"in\")<\/code><\/pre>\n<p>\u5728\u8fd9\u4e2a\u4fee\u6539\u540e\u7684\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u91c7\u7528\u4e86\u4ee5\u4e0b\u8c03\u6574\uff1a<\/p>\n<ol>\n<li>\u589e\u52a0\u70b9\u7684\u5927\u5c0f\uff08<code>size = 2<\/code>\uff09\uff0c\u4f7f\u5176\u66f4\u5bb9\u6613\u8fa8\u8ba4\u3002<\/li>\n<li>\u4f7f\u7528\u6df1\u7070\u8272\u548c\u6df1\u7ea2\u8272\u4f5c\u4e3a\u70b9\u7684\u989c\u8272\uff0c\u4f7f\u5176\u66f4\u9192\u76ee\u3002<\/li>\n<li>\u4f7f\u7528dodgerblue\u4f5c\u4e3a\u865a\u7ebf\u7684\u989c\u8272\uff0c\u4f7f\u5176\u4e0e\u70b9\u7684\u989c\u8272\u5f62\u6210\u5bf9\u6bd4\u3002<\/li>\n<li>\u589e\u52a0\u8f74\u6807\u9898\u3001\u56fe\u5f62\u6807\u9898\u548c\u5750\u6807\u8f74\u523b\u5ea6\u7684\u5b57\u4f53\u5927\u5c0f\uff0c\u4f7f\u5176\u66f4\u6613\u4e8e\u9605\u8bfb\u3002<\/li>\n<\/ol>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<p><img decoding=\"async\" src=\"https:\/\/yunshangtulv.com.cn\/wp-content\/uploads\/2023\/04\/1681976558755.webp\" \/><\/p>\n<h2>\u591a\u7ec4\u805a\u7c7b\u706b\u5c71\u56fe<\/h2>\n<p>\u4e3a\u4e86\u521b\u5efa\u591a\u7ec4\u805a\u7c7b\u706b\u5c71\u56fe\uff0c\u6211\u4eec\u9996\u5148\u9700\u8981\u751f\u6210\u4e00\u4e2a\u5305\u542b\u591a\u4e2a\u5206\u7ec4\u7684\u6570\u636e\u96c6\u3002\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u5c06\u521b\u5efa\u4e09\u4e2a\u5206\u7ec4\uff08A\u3001B\u548cC\uff09\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u4f7f\u7528<code>facet_wrap()<\/code>\u51fd\u6570\u5236\u4f5c\u591a\u7ec4\u805a\u7c7b\u706b\u5c71\u56fe\u3002\u8bf7\u6ce8\u610f\uff0c\u8fd9\u4e2a\u793a\u4f8b\u4f7f\u7528\u4e86\u968f\u673a\u751f\u6210\u7684\u6570\u636e\uff0c\u5b9e\u9645\u7814\u7a76\u4e2d\u5e94\u4f7f\u7528\u771f\u5b9e\u6570\u636e\u3002<\/p>\n<div class=\"bg-black rounded-md mb-4\"><\/div>\n<pre class=\"corepress-code-pre\"><code>\r\n\r\n# \u52a0\u8f7d\u6240\u9700\u7684\u5305\r\nlibrary(ggplot2)# \u793a\u4f8b\u6570\u636e\r\nset.seed(123) # \u8bbe\u7f6e\u968f\u673a\u6570\u79cd\u5b50\uff0c\u4ee5\u4fbf\u751f\u6210\u53ef\u91cd\u73b0\u7684\u6570\u636e\r\ngroup_labels &lt;- c(\"A\", \"B\", \"C\")\r\ngene_ids &lt;- paste0(\"Gene\", 1:1000)\r\n\r\n# \u751f\u6210\u6bcf\u4e2a\u5206\u7ec4\u7684\u6570\u636e\r\ngroup_data_list &lt;- lapply(group_labels, function(group_label) {\r\nlog2_fold_changes &lt;- rnorm(1000, mean = 0, sd = 1.5)\r\np_values &lt;- runif(1000, min = 0, max = 1)\r\ndata.frame(Group = group_label,\r\nGeneID = gene_ids,\r\nLog2FoldChange = log2_fold_changes,\r\nPValue = p_values)\r\n})\r\n\r\n# \u5408\u5e76\u6240\u6709\u5206\u7ec4\u7684\u6570\u636e\r\nall_data &lt;- do.call(rbind, group_data_list)\r\n\r\n# \u8ba1\u7b97-log10(PValue)\u5e76\u8fdb\u884c\u663e\u8457\u6027\u5206\u7ec4\r\nall_data$NegLog10PValue &lt;- -log10(all_data$PValue)\r\n\r\nthreshold_p_value &lt;- 0.05\r\nthreshold_log2_fold_change &lt;- 1\r\n\r\nall_data$Significance &lt;- \"Not significant\"\r\nall_data$Significance[all_data$PValue &lt; threshold_p_value &amp;\r\nabs(all_data$Log2FoldChange) &gt; threshold_log2_fold_change] &lt;- \"Significant\"\r\n\r\n# \u7ed8\u5236\u591a\u7ec4\u805a\u7c7b\u706b\u5c71\u56fe\r\np &lt;- ggplot(all_data, aes(x = Log2FoldChange, y = NegLog10PValue, color = Significance)) +\r\ngeom_point(alpha = 0.8, size = 2) +\r\nscale_color_manual(values = c(\"Not significant\" = \"darkgray\", \"Significant\" = \"darkred\")) +\r\ngeom_hline(yintercept = -log10(threshold_p_value), linetype = \"dashed\", color = \"dodgerblue\") +\r\ngeom_vline(xintercept = c(-threshold_log2_fold_change, threshold_log2_fold_change), linetype = \"dashed\", color = \"dodgerblue\") +\r\nxlab(\"log2(Fold Change)\") +\r\nylab(\"-log10(P-Value)\") +\r\nggtitle(\"\u591a\u7ec4\u805a\u7c7b\u706b\u5c71\u56fe\") +\r\ntheme_minimal() +\r\ntheme(legend.position = \"bottom\",\r\naxis.title = element_text(size = 14),\r\nplot.title = element_text(size = 16, hjust = 0.5),\r\naxis.text = element_text(size = 12)) +\r\nfacet_wrap(~ Group, ncol = 3)\r\n\r\n# \u663e\u793a\u56fe\u5f62\r\nprint(p)\r\n\r\n# \u4fdd\u5b58\u4e3aPDF\u6587\u4ef6\r\nggsave(\"multi_group_volcano_plot.pdf\", plot = p, width = 16, height = 7, units = \"in\")<\/code><\/pre>\n<p>\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u8fdb\u884c\u4e86\u4ee5\u4e0b\u64cd\u4f5c\uff1a<\/p>\n<ol>\n<li>\u4e3a\u4e09\u4e2a\u5206\u7ec4\uff08A\u3001B\u548cC\uff09\u751f\u6210\u968f\u673a\u6570\u636e\u3002<\/li>\n<li>\u4f7f\u7528<code>lapply()<\/code>\u51fd\u6570\uff0c\u4e3a\u6bcf\u4e2a\u5206\u7ec4\u521b\u5efa\u6570\u636e\u6846\uff0c\u5e76\u4f7f\u7528<code>do.call()<\/code>\u51fd\u6570\u5c06\u8fd9\u4e9b\u6570\u636e\u6846\u5408\u5e76\u4e3a\u4e00\u4e2a\u6570\u636e\u6846\u3002<\/li>\n<li>\u8ba1\u7b97-log10(PValue)\u5e76\u6309\u663e\u8457\u6027\u548c\u5dee\u5f02\u8868\u8fbe\u9608\u503c\u5bf9\u57fa\u56e0\u8fdb\u884c\u5206\u7ec4\u3002<\/li>\n<li>\u4f7f\u7528<code>facet_wrap()<\/code>\u51fd\u6570\u5728\u706b\u5c71\u56fe\u4e2d\u6dfb\u52a0\u5206\u7ec4\u4fe1\u606f\u3002<code>facet_wrap(~ Group, ncol = 3)<\/code>\u7684\u4f5c\u7528\u662f\u6839\u636e\"Group\"\u53d8\u91cf\u5c06\u6570\u636e\u5206\u6210\u591a\u4e2a\u5b50\u56fe\uff0c\u6bcf\u884c\u5305\u542b3\u4e2a\u5b50\u56fe\u3002<\/li>\n<li>\u4f7f\u7528\u4e0e\u4e4b\u524d\u7684\u706b\u5c71\u56fe\u76f8\u540c\u7684\u6837\u5f0f\uff0c\u5305\u62ec\u70b9\u7684\u5927\u5c0f\u3001\u989c\u8272\u3001\u865a\u7ebf\u548c\u5b57\u4f53\u5927\u5c0f\uff0c\u4f7f\u56fe\u50cf\u66f4\u7f8e\u89c2\u3002<\/li>\n<li>\u4f7f\u7528<code>ggsave()<\/code>\u51fd\u6570\u5c06\u591a\u7ec4\u805a\u7c7b\u706b\u5c71\u56fe\u4fdd\u5b58\u4e3aPDF\u6587\u4ef6\u3002\n<ol start=\"2\"><\/ol>\n<p>\u8fd9\u4e2a\u793a\u4f8b\u5c55\u793a\u4e86\u5982\u4f55\u521b\u5efa\u4e00\u4e2a\u591a\u7ec4\u805a\u7c7b\u706b\u5c71\u56fe\u3002\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u4f60\u9700\u8981\u4f7f\u7528\u5b9e\u9645\u7684\u5dee\u5f02\u8868\u8fbe\u57fa\u56e0\u6570\u636e\u6765\u751f\u6210\u706b\u5c71\u56fe\u3002\u591a\u7ec4\u805a\u7c7b\u706b\u5c71\u56fe\u53ef\u4ee5\u5e2e\u52a9\u7814\u7a76\u4eba\u5458\u4e00\u76ee\u4e86\u7136\u5730\u6bd4\u8f83\u4e0d\u540c\u5b9e\u9a8c\u7ec4\u4e4b\u95f4\u7684\u57fa\u56e0\u8868\u8fbe\u53d8\u5316\u548c\u663e\u8457\u6027\u6c34\u5e73\u3002<\/li>\n<\/ol>\n<p>&nbsp;<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/yunshangtulv.com.cn\/wp-content\/uploads\/2023\/04\/1681976767587.webp\" \/><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u5e38\u89c4\u706b\u5c71\u56fe \u4e0b\u9762\u7684\u793a\u4f8b\u4e2d\uff0c\u6211\u5c06\u521b\u5efa\u4e00\u4e2a\u865a\u6784\u7684\u6570\u636e\u96c6\uff0c\u5c55\u793a\u524d\u51e0\u884c\uff0c\u5e76\u7ed8\u5236\u4e00\u5f20\u7f8e\u89c2\u3001\u8be6\u5c3d\u7684\u706b\u5c71\u56fe\u3002\u6211\u4eec\u5c06\u4f7f\u7528ggp [&hellip;]<\/p>\n","protected":false},"author":111,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[9],"tags":[],"class_list":["post-439","post","type-post","status-publish","format-standard","hentry","category-r"],"_links":{"self":[{"href":"https:\/\/yunshangtulv.com.cn\/index.php?rest_route=\/wp\/v2\/posts\/439","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/yunshangtulv.com.cn\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/yunshangtulv.com.cn\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/yunshangtulv.com.cn\/index.php?rest_route=\/wp\/v2\/users\/111"}],"replies":[{"embeddable":true,"href":"https:\/\/yunshangtulv.com.cn\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=439"}],"version-history":[{"count":0,"href":"https:\/\/yunshangtulv.com.cn\/index.php?rest_route=\/wp\/v2\/posts\/439\/revisions"}],"wp:attachment":[{"href":"https:\/\/yunshangtulv.com.cn\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=439"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/yunshangtulv.com.cn\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=439"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/yunshangtulv.com.cn\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=439"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}