{"id":473,"date":"2023-06-20T03:06:01","date_gmt":"2023-06-20T03:06:01","guid":{"rendered":"https:\/\/yunshangtulv.com.cn\/?p=473"},"modified":"2023-06-20T03:09:19","modified_gmt":"2023-06-20T03:09:19","slug":"sci%e5%9b%be%e7%89%87%e5%a4%8d%e7%8e%b0%ef%bc%9a%e9%85%8d%e5%af%b9%e4%ba%91%e9%9b%a8%e5%9b%be","status":"publish","type":"post","link":"https:\/\/yunshangtulv.com.cn\/?p=473","title":{"rendered":"SCI\u56fe\u7247\u590d\u73b0\uff1a\u914d\u5bf9\u4e91\u96e8\u56fe"},"content":{"rendered":"

\u9996\u5148\u8ba9\u6211\u4eec\u751f\u6210\u4e00\u4e9b\u793a\u4f8b\u6570\u636e\uff0c\u5047\u8bbe\u9700\u8981\u7684\u6570\u636e\u6846\uff08DataFrame\uff09\u5e94\u8be5\u6709\u5982\u4e0b\u51e0\u5217\uff1a'Family.ID'\u3001'Disease.state'\u548c'Richness'\u3002<\/p>\n

1. \u751f\u6210\u4ee3\u7801\u6240\u9700\u7684\u6570\u636e\uff0c\u5e76\u5217\u51fa\u6570\u636e\u524d\u51e0\u884c\uff1a<\/p>\n

library(dplyr)\r\ndf <- iris %>% \r\n  mutate(Family.ID = rep(1:50, each = 3),\r\n         Disease.state = rep(c(\"Patient\", \"Relative\", \"Control\"), 50),\r\n         Richness = Sepal.Length) \r\n\r\nhead(df)\r\n<\/code><\/pre>\n
\u5047\u8bbe\u7684\u6570\u636e\u53ef\u80fd\u5982\u4e0b\u6240\u793a\uff1a<\/p>\n
Family.ID | Disease.state | Richness
\n--- | --- | ---
\n1 | Patient | 5.1
\n1 | Relative | 4.9
\n1 | Control | 4.7
\n2 | Patient | 4.6
\n2 | Relative | 5.0
\n2 | Control | 5.4<\/p>\n
\u73b0\u5728\u6211\u4eec\u5f00\u59cb\u5904\u7406\u7b2c\u4e8c\u90e8\u5206\uff1a<\/p>\n
\u6211\u4eec\u9996\u5148\u5904\u7406\u7b2c\u4e00\u4e2a\u56fe\u8868\u7684\u4ee3\u7801\u3002\u6211\u4f1a\u5bf9\u539f\u59cb\u4ee3\u7801\u8fdb\u884c\u4e00\u4e9b\u8c03\u6574\uff0c\u4ee5\u9002\u5e94\u65b0\u7684\u6570\u636e\u96c6\uff0c\u5e76\u4e14\u6211\u4e5f\u4f1a\u589e\u52a0\u6ce8\u91ca\u6765\u89e3\u91ca\u6bcf\u4e00\u884c\u4ee3\u7801\u7684\u4f5c\u7528\u3002<\/p>\n
# \u52a0\u8f7d\u7ed8\u56fe\u5305\r\nlibrary(ggplot2)\r\n\r\n# \u628a'Family.ID'\u5217\u53d8\u4e3a\u56e0\u5b50\u7c7b\u578b\uff0c\u4ee5\u4fbf\u540e\u7eed\u8fdb\u884c\u5206\u7ec4\u64cd\u4f5c\r\ndf$Family.ID <- as.factor(df$Family.ID)\r\n\r\n# \u4f7f\u7528 ggplot \u521b\u5efa\u57fa\u7840\u7ed8\u56fe\u5bf9\u8c61\r\np <- ggplot(df, aes(x=Disease.state, y=Richness, fill=Disease.state))\r\n\r\n# \u6dfb\u52a0\u5c0f\u63d0\u7434\u56fe\u5c42\r\np <- p + geom_violin(width = 0.8, color = NA)\r\n\r\n# \u6dfb\u52a0\u7bb1\u7ebf\u56fe\u5c42\r\np <- p + geom_boxplot(alpha = 0.5, size = 1, outlier.shape = NA, width = 0.2)\r\n\r\n# \u6dfb\u52a0\u77e9\u5f62\u56fe\u5c42\uff0c\u4e3b\u8981\u7528\u4e8e\u5206\u9694\u4e0d\u540c\u7684\u5c0f\u63d0\u7434\u56fe\r\np <- p + geom_rect(aes(xmin = 0.98, ymin = -Inf, xmax = 2.02, ymax = Inf), fill = \"white\", size = 1.5)\r\n\r\n# \u6dfb\u52a0\u6296\u52a8\u70b9\u56fe\u5c42\uff0c\u663e\u793a\u6bcf\u4e2a\u6837\u672c\u7684\u5177\u4f53\u503c\r\np <- p + geom_jitter(aes(group=Family.ID, color=Disease.state), size = 2, shape = 16, stroke = 0.15, show.legend = FALSE, position = position_dodge(0.05))\r\n\r\n# \u6dfb\u52a0\u7ebf\u56fe\u5c42\uff0c\u5c06\u5c5e\u4e8e\u540c\u4e00\u7ec4\u7684\u70b9\u8fde\u63a5\u8d77\u6765\r\np <- p + geom_line(aes(group = Family.ID), color = 'grey40', lwd = 0.5, position = position_dodge(0.05))\r\n\r\n# \u8bbe\u7f6e\u7ed8\u56fe\u4e3b\u9898\r\np <- p + theme_bw() + \r\n         theme(text = element_text(size=10, colour = \"black\"), \r\n               panel.grid = element_blank(),\r\n               axis.text.x = element_text(colour = \"black\", size = 14),\r\n               axis.text.y = element_text(colour = \"black\", size = 14),\r\n               axis.title.y = element_text(color = 'black', size = 14),\r\n               axis.title.x = element_blank(),\r\n               legend.position = 'none')\r\n\r\n# \u8bbe\u7f6e\u56fe\u5f62\u6807\u9898\u548c\u5750\u6807\u8f74\u6807\u7b7e\r\np <- p + labs(title = \"\", y = \"Expression\", x=\" \")\r\n\r\n# \u8bbe\u7f6e\u586b\u5145\u8272\r\np <- p + scale_fill_manual(values = c('#E69F00', \"#009E73\"))\r\n\r\n# \u6253\u5370\u56fe\u5f62\r\nprint(p)\r\n<\/code><\/pre>\n
\u73b0\u5728\u6211\u4eec\u5df2\u7ecf\u6709\u4e86\u4e00\u4e2a\u5de5\u4f5c\u7684\u4ee3\u7801\uff0c\u4e0b\u4e00\u6b65\u662f\u4f18\u5316\u8fd9\u6bb5\u4ee3\u7801\u4ee5\u4f7f\u5f97\u56fe\u7247\u66f4\u4e3a\u4e30\u5bcc\u548c\u7f8e\u89c2\uff0c\u7136\u540e\u4fdd\u5b58\u751f\u6210\u7684\u7ed3\u679c\uff0c\u5e76\u63d0\u4f9b\u5982\u4f55\u4f7f\u7528\u81ea\u5df1\u7684\u6570\u636e\u8fdb\u884c\u683c\u5f0f\u5316\u7684\u5efa\u8bae\u3002<\/p>\n
\u73b0\u5728\u6211\u4eec\u7ee7\u7eed\u8fdb\u884c\u7b2c\u4e09\u6b65\uff1a\u4f18\u5316\u4ee3\u7801\u4ee5\u4f7f\u56fe\u7247\u66f4\u4e30\u5bcc\u548c\u7f8e\u89c2\u3002<\/p>\n
# \u6dfb\u52a0\u4e3b\u9898\u548c\u989c\u8272\u8bbe\u7f6e\r\ntheme_update(\r\n  plot.title = element_text(face=\"bold\", hjust = 0.5, size=20),\r\n  axis.title = element_text(face=\"bold\", size=15),\r\n  axis.text = element_text(size=13),\r\n  legend.title = element_text(face=\"bold\", size=12),\r\n  legend.text = element_text(size = 11),\r\n  panel.grid = element_blank(),\r\n  strip.text = element_text(face=\"bold\", size=15),\r\n  strip.background = element_rect(fill=\"lightgrey\", colour=\"black\", size=1)\r\n)\r\n\r\n# \u4f7f\u7528\u6211\u4eec\u7684\u4e3b\u9898\u548c\u989c\u8272\u8fdb\u884c\u7ed8\u56fe\r\np <- ggplot(df, aes(x=Disease.state, y=Richness, fill=Disease.state)) +\r\n  geom_violin(width = 0.8, color = \"black\") +\r\n  geom_boxplot(alpha = 0.5, size = 1, outlier.shape = NA, width = 0.2, color = \"black\") +\r\n  geom_rect(aes(xmin = 0.98, ymin = -Inf, xmax = 2.02, ymax = Inf), fill = \"white\", size = 1.5) +\r\n  geom_jitter(aes(group=Family.ID, color=Disease.state), size = 2, shape=16, stroke = 0.15, position = position_dodge(0.05)) +\r\n  geom_line(aes(group = Family.ID), color = 'grey40', lwd = 0.5, position = position_dodge(0.05)) +\r\n  scale_fill_manual(values = c('#E69F00', \"#009E73\")) +\r\n  labs(title = \"Disease State vs Richness\", y = \"Expression\", x = \"Disease State\") +\r\n  theme_bw()\r\n\r\nprint(p)\r\n<\/code><\/pre>\n
 <\/p>\n
\u7b2c\u56db\u6b65\uff1a\u4fdd\u5b58\u6bcf\u4e00\u4e2a\u751f\u6210\u7684\u7ed3\u679c\u3002<\/p>\n
# \u4fdd\u5b58\u56fe\u50cf\u4e3a PDF \u683c\u5f0f\r\nggsave(filename = \"violin_plot.pdf\", plot = p, device = \"pdf\", width = 10, height = 6)\r\n\r\n# \u4fdd\u5b58\u6570\u636e\u4e3a CSV \u683c\u5f0f\r\nwrite.csv(df, \"df.csv\")\r\n<\/code><\/pre>\n
 <\/p>\n
\u6700\u540e\uff0c\u5982\u679c\u60f3\u8981\u4f7f\u7528\u81ea\u5df1\u7684\u6570\u636e\uff0c\u5e94\u8be5\u786e\u4fdd\u6570\u636e\u8868\u662f\u4e0b\u9762\u8fd9\u79cd\u683c\u5f0f\uff1a<\/p>\n
- Family.ID: \u8fd9\u4e2a\u5b57\u6bb5\u8868\u793a\u6bcf\u4e00\u7ec4\u7684\u552f\u4e00\u6807\u8bc6\u3002\u8fd9\u4e2a\u5b57\u6bb5\u7684\u6570\u636e\u7c7b\u578b\u5e94\u8be5\u662f\u56e0\u5b50\u6216\u5b57\u7b26\u3002
\n- Disease.state: \u8fd9\u4e2a\u5b57\u6bb5\u8868\u793a\u75be\u75c5\u72b6\u6001\uff0c\u4f8b\u5982\uff0c\"Patient\"\u3001\"Relative\"\u7b49\u3002\u8fd9\u4e2a\u5b57\u6bb5\u7684\u6570\u636e\u7c7b\u578b\u5e94\u8be5\u662f\u56e0\u5b50\u6216\u5b57\u7b26\u3002
\n- Richness: \u8fd9\u4e2a\u5b57\u6bb5\u8868\u793a\u6211\u4eec\u611f\u5174\u8da3\u7684\u6d4b\u91cf\u6216\u6570\u503c\u3002\u8fd9\u4e2a\u5b57\u6bb5\u7684\u6570\u636e\u7c7b\u578b\u5e94\u8be5\u662f\u6570\u503c\u3002<\/p>\n
\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u5904\u7406\u7b2c\u4e8c\u4e2a\u56fe\u8868\u7684\u4ee3\u7801\u3002<\/p>\n
\u73b0\u5728\u6211\u4eec\u5904\u7406\u7b2c\u4e8c\u4e2a\u56fe\u8868\u7684\u4ee3\u7801\uff0c\u8fd9\u6b21\u6211\u4eec\u8981\u4f7f\u7528`gghalves`\u5305\u6765\u521b\u5efa\u5206\u522b\u671d\u5411\u4e0d\u540c\u65b9\u5411\u7684\u5c0f\u63d0\u7434\u56fe\u3002<\/p>\n
\u9996\u5148\uff0c\u8ba9\u6211\u4eec\u4fee\u6539\u539f\u59cb\u4ee3\u7801\u4ee5\u9002\u5e94\u6211\u4eec\u7684\u6570\u636e\uff0c\u5e76\u6dfb\u52a0\u5fc5\u8981\u7684\u6ce8\u91ca\u3002<\/p>\n
# \u52a0\u8f7d gghalves \u5305\r\nlibrary(gghalves)\r\n\r\n# \u521b\u5efa\u56fe\u50cf\r\np2 <- ggplot(df, aes(x = Disease.state, y = Richness, fill = Disease.state))\r\n\r\n# \u5728\u60a3\u8005\u7ec4\u6dfb\u52a0\u671d\u5411\u5de6\u7684\u5c0f\u63d0\u7434\u56fe\u548c\u7bb1\u7ebf\u56fe\r\np2 <- p2 + geom_half_violin(data = subset(df, Disease.state == 'Patient'), position = position_nudge(x = 0), side = \"l\", color = NA)\r\np2 <- p2 + geom_half_boxplot(data = subset(df, Disease.state == 'Patient'), position = position_nudge(x = 0), side = 'l', width = 0.2)\r\n\r\n# \u5728\u4eb2\u5c5e\u7ec4\u6dfb\u52a0\u671d\u5411\u53f3\u7684\u5c0f\u63d0\u7434\u56fe\u548c\u7bb1\u7ebf\u56fe\r\np2 <- p2 + geom_half_violin(data = subset(df, Disease.state == 'Relative'), position = position_nudge(x = 0), side = \"r\", color = NA)\r\np2 <- p2 + geom_half_boxplot(data = subset(df, Disease.state == 'Relative'), position = position_nudge(x = 0), side = 'r', width = 0.2)\r\n\r\n# \u6dfb\u52a0\u6296\u52a8\u70b9\u56fe\u5c42\u548c\u8fde\u7ebf\u56fe\u5c42\uff0c\u548c\u4e0a\u9762\u7684\u56fe\u4e00\u6837\r\np2 <- p2 + geom_jitter(aes(group = Family.ID, color = Disease.state), size = 2, shape = 16, stroke = 0.15, position = position_dodge(0.05))\r\np2 <- p2 + geom_line(aes(group = Family.ID), color = 'grey40', lwd = 0.5, position = position_dodge(0.05))\r\n\r\n# \u5e94\u7528\u6211\u4eec\u4e4b\u524d\u521b\u5efa\u7684\u4e3b\u9898\u548c\u989c\u8272\u8bbe\u7f6e\r\np2 <- p2 + labs(title = \"Disease State vs Richness (Halves)\", y = \"Expression\", x = \"Disease State\") + theme_bw()\r\n\r\n# \u663e\u793a\u56fe\u50cf\r\nprint(p2)\r\n<\/code><\/pre>\n
 <\/p>\n
\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u4fdd\u5b58\u8fd9\u4e2a\u56fe\u50cf\u548c\u6570\u636e\uff0c\u5e76\u63d0\u4f9b\u7528\u6237\u5982\u4f55\u7528\u81ea\u5df1\u7684\u6570\u636e\u8fdb\u884c\u683c\u5f0f\u5316\u7684\u5efa\u8bae\u3002<\/p>\n
# \u4fdd\u5b58\u56fe\u50cf\u4e3a PDF \u683c\u5f0f\r\nggsave(filename = \"half_violin_plot.pdf\", plot = p2, device = \"pdf\", width = 10, height = 6)\r\n\r\n# \u56e0\u4e3a\u6570\u636e\u5df2\u7ecf\u5728\u4e4b\u524d\u4fdd\u5b58\u8fc7\u4e86\uff0c\u6240\u4ee5\u8fd9\u91cc\u4e0d\u518d\u91cd\u590d\r\n<\/code><\/pre>\n
 <\/p>\n
\u4e0b\u9762\u6240\u6709\u7684\u6b65\u9aa4\u6c47\u603b\u4e00\u4e0b\u3002<\/p>\n
# \u751f\u6210\u6570\u636e\r\nset.seed(123)\r\nFamily.ID <- rep(1:30, each = 2)\r\nDisease.state <- rep(c(\"Patient\", \"Relative\"), 30)\r\nRichness <- c(rnorm(30, 10, 2), rnorm(30, 15, 2))\r\ndf <- data.frame(Family.ID, Disease.state, Richness)\r\n\r\n# \u5c06'Family.ID'\u5217\u53d8\u4e3a\u56e0\u5b50\u7c7b\u578b\uff0c\u4ee5\u4fbf\u540e\u7eed\u8fdb\u884c\u5206\u7ec4\u64cd\u4f5c\r\ndf$Family.ID <- as.factor(df$Family.ID)\r\n\r\n# \u52a0\u8f7d\u7ed8\u56fe\u5305\r\nlibrary(ggplot2)\r\nlibrary(gghalves)\r\n\r\n# \u521b\u5efa\u4e3b\u9898\r\ntheme_update(\r\n  plot.title = element_text(face=\"bold\", hjust = 0.5, size=20),\r\n  axis.title = element_text(face=\"bold\", size=15),\r\n  axis.text = element_text(size=13),\r\n  legend.title = element_text(face=\"bold\", size=12),\r\n  legend.text = element_text(size = 11),\r\n  panel.grid = element_blank(),\r\n  strip.text = element_text(face=\"bold\", size=15),\r\n  strip.background = element_rect(fill=\"lightgrey\", colour=\"black\", size=1)\r\n)\r\n\r\n# \u521b\u5efa\u7b2c\u4e00\u4e2a\u56fe\u50cf\r\np <- ggplot(df, aes(x = Disease.state, y = Richness, fill = Disease.state)) +\r\n  geom_violin(width = 0.8, color = \"black\") +\r\n  geom_boxplot(alpha = 0.5, size = 1, outlier.shape = NA, width = 0.2, color = \"black\") +\r\n  geom_rect(aes(xmin = 0.98, ymin = -Inf, xmax = 2.02, ymax = Inf), fill = \"white\", size = 1.5) +\r\n  geom_jitter(aes(group = Family.ID, color = Disease.state), size = 2, shape = 16, stroke = 0.15, position = position_dodge(0.05)) +\r\n  geom_line(aes(group = Family.ID), color = 'grey40', lwd = 0.5, position = position_dodge(0.05)) +\r\n  scale_fill_manual(values = c('#E69F00', \"#009E73\")) +\r\n  labs(title = \"Disease State vs Richness\", y = \"Expression\", x = \"Disease State\") +\r\n  theme_bw()\r\n\r\n# \u521b\u5efa\u7b2c\u4e8c\u4e2a\u56fe\u50cf\r\np2 <- ggplot(df, aes(x = Disease.state, y = Richness, fill = Disease.state)) +\r\n  geom_half_violin(data = subset(df, Disease.state == 'Patient'), position = position_nudge(x = 0), side = \"l\", color = NA) +\r\n  geom_half_boxplot(data = subset(df, Disease.state == 'Patient'), position = position_nudge(x = 0), side = 'l', width = 0.2) +\r\n  geom_half_violin(data = subset(df, Disease.state == 'Relative'), position = position_nudge(x = 0), side = \"r\", color = NA) +\r\n  geom_half_boxplot(data = subset(df, Disease.state == 'Relative'), position = position_nudge(x = 0), side = 'r', width = 0.2) +\r\n  geom_jitter(aes(group = Family.ID, color = Disease.state), size = 2, shape = 16, stroke = 0.15, position = position_dodge(0.05)) +\r\n  geom_line(aes(group = Family.ID), color = 'grey40', lwd = 0.5, position = position_dodge(0.05)) +\r\n  labs(title = \"Disease State vs Richness (Halves)\", y = \"Expression\", x = \"Disease State\") +\r\n  theme_bw()\r\n\r\n# \u4fdd\u5b58\u56fe\u50cf\r\nggsave(filename = \"violin_plot.pdf\", plot = p, device = \"pdf\", width = 10, height = 6)\r\nggsave(filename = \"half_violin_plot.pdf\", plot = p2, device = \"pdf\", width = 10, height = 6)\r\n\r\n# \u4fdd\u5b58\u6570\u636e\r\nwrite.csv(df, \"df.csv\")\r\n<\/code><\/pre>\n
\u8fd9\u4e2a\u5b8c\u6574\u7684R\u811a\u672c\u5305\u62ec\u4e86\u4ece\u751f\u6210\u6570\u636e\u5f00\u59cb\uff0c\u7136\u540e\u7ed8\u5236\u4e24\u79cd\u4e0d\u540c\u7684\u56fe\u8868\uff0c\u5e76\u4fdd\u5b58\u8fd9\u4e9b\u56fe\u8868\u548c\u6570\u636e\u7684\u6240\u6709\u6b65\u9aa4\u3002
\n\"\"
\n<\/span><\/p>\n
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