{"id":998,"date":"2023-01-14T22:01:08","date_gmt":"2023-01-14T14:01:08","guid":{"rendered":"http:\/\/www.biocloudservice.com\/wordpress\/?p=998"},"modified":"2023-01-14T22:01:10","modified_gmt":"2023-01-14T14:01:10","slug":"00d1870735","status":"publish","type":"post","link":"http:\/\/www.biocloudservice.com\/wordpress\/?p=998","title":{"rendered":"\u6851\u57fa\u56fe\uff08Sankey diagram\uff09"},"content":{"rendered":"
\n

\"\u6851\u57fa\u56fe\uff08Sankey<\/p>\n

\n
\n
\n
\n
\n
\n
\n
\n

\u6851\u57fa\u56fe\uff08Sankey diagram\uff09\uff0c\u5373\u6851\u57fa\u80fd\u91cf\u5206\u6d41\u56fe\uff0c\u4e5f\u53eb\u6851\u57fa\u80fd\u91cf\u5e73\u8861\u56fe\u3002\u5b83\u662f\u4e00\u79cd\u7279\u5b9a\u7c7b\u578b\u7684\u6d41\u7a0b\u56fe\uff0c\u56fe\u4e2d\u5ef6\u4f38\u7684\u5206\u652f\u7684\u5bbd\u5ea6\u5bf9\u5e94\u6570\u636e<\/span>\u6d41\u91cf<\/span><\/strong>\u7684\u5927\u5c0f\uff0c\u6bd4\u8f83\u9002\u7528\u4e8e\u7528\u6237\u6d41\u91cf\u7b49\u6570\u636e\u7684\u53ef\u89c6\u5316\u5206\u6790\u3002\u56e01898\u5e74Matthew Henry Phineas Riall Sankey\u7ed8\u5236\u7684\u201c\u84b8\u6c7d\u673a\u7684\u80fd\u6e90\u6548\u7387\u56fe\u201d\u800c\u95fb\u540d\uff0c\u6b64\u540e\u4fbf\u4ee5\u5176\u540d\u5b57\u547d\u540d\u4e3a\u201c\u6851\u57fa\u56fe\u201d\u3002<\/span><\/p>\n

\u611f\u5174\u8da3\u7684\u5c0f\u4f19\u4f34\u53ef\u4ee5\u53bb\u770b\u770bCharles Minard\u57281869\u5e74\u6240\u4f5c\u7684\u62ff\u7834\u4ed1\u4e1c\u5f81\u4fc4\u56fd\u7684\u4fe1\u606f\u56fe\uff0c\u7528\u5230\u7684\u5c31\u662f\u6851\u845a\u56fe\u5c55\u793a\u7684\u54e6\u3002<\/span><\/p>\n

\"\u6851\u57fa\u56fe\uff08Sankey<\/p>\n<\/section>\n

\n

\u90a3\u4e48\u6851\u57fa\u56fe\u8981\u600e\u4e48\u770b\uff1f\u5c0f\u679c\u5728\u8fd9\u91cc\u4e3a\u5927\u5bb6\u68b3\u7406\u4e00\u4e0b\uff01<\/span><\/strong><\/span><\/p>\n

\uff081<\/span>\uff09\u770b<\/span>\u7ebf\u6761\u7684\u8d70\u5411<\/span>\uff082<\/span>\uff09\u770b<\/span>\u7c97\u7ec6\u7684\u53d8\u5316<\/span>\uff083<\/span>\uff09\u770b<\/span>\u8282\u70b9\u95f4\u7684\u6bd4\u8f83<\/span><\/p>\n

\u6851\u57fa\u56fe\u4e3b\u8981\u7531\u8fb9\u3001\u6d41\u91cf\u548c\u8282\u70b9\u7ec4\u6210\uff0c\u5176\u4e2d\u8fb9\u4ee3\u8868\u4e86\u6d41\u52a8\u7684\u6570\u636e\uff0c\u6d41\u91cf\u4ee3\u8868\u4e86\u6570\u636e\u6d41\u52a8\u7684\u5177\u4f53\u6570\u503c\uff0c\u8282\u70b9\u4ee3\u8868\u4e86\u4e0d\u540c\u7684\u5206\u7c7b\uff0c\u8fb9\u7684\u5bbd\u5ea6\u4e0e\u6d41\u91cf\u6210\u6bd4\u4f8b\uff0c\u8fb9\u8d8a\u5bbd\uff0c\u6570\u503c\u8d8a\u5927\u3002<\/span><\/p>\n

\"\u6851\u57fa\u56fe\uff08Sankey<\/p>\n<\/section>\n

\n

\u6851\u57fa\u56fe\u53ef\u4ee5\u8fd0\u7528\u7684\u573a\u666f\u4e3b\u8981\u6709\uff1a<\/span><\/strong><\/span><\/p>\n

\n
\n
<\/section>\n
<\/section>\n
\n
\n

\u573a\u666f\u4e00\uff1a<\/strong><\/p>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n

miRNA\u548c\u9776\u57fa\u56e0\u7684\u5173\u7cfb\u3002<\/span><\/p>\n

<\/section>\n
<\/section>\n
\n
\n

\u573a\u666f\u4e8c\uff1a<\/strong><\/p>\n<\/section>\n<\/section>\n

\u4e00\u4e2agroup\u5305\u542b\u591a\u4e2a\u57fa\u56e0\uff0c\u540c\u4e00\u4e2a\u57fa\u56e0\u7684\u4e0d\u540c\u7a81\u53d8\u53ef\u80fd\u5c5e\u4e8e\u591a\u4e2agroup\u3002\u50cf\u4f8b\u56fe\u4e00\u6837\uff0c\u5c55\u793a\u9ad8\u9891\u7a81\u53d8\u57fa\u56e0\u6240\u5904\u7684\u5206\u7ec4\u3002<\/span><\/p>\n<\/section>\n

\n
<\/section>\n
<\/section>\n
\n
\n

\u573a\u666f\u4e09\uff1a<\/strong><\/p>\n<\/section>\n<\/section>\n<\/section>\n

\n

\u4eba\u7fa4\u6309\u6027\u522b\u3001\u5e74\u9f84\u3001\u5bb6\u65cf\u53f2\u7b49\u7279\u5f81\u5206\u7ec4\uff0c\u5c55\u793a\u4e0d\u540c\u5206\u7ec4\u5f97\u764c\u75c7\u7684\u89c4\u5f8b\u3002<\/span><\/p>\n

\"\u6851\u57fa\u56fe\uff08Sankey<\/p>\n<\/section>\n

\n

\u4e0b\u9762\u662f\u5177\u4f53\u7684\u4ee3\u7801\u5b9e\u6218\u90e8\u5206\uff1a<\/span><\/strong><\/span><\/p>\n

###<\/span>\u8bfb\u53d6\u6570\u636e\uff0c\u67e5\u770b\u6570\u636e<\/span><\/p>\n

df <- read.table(“sankey.txt”,sep = “t”,row.names = 1,header = T)<\/span><\/p>\n

head(df)<\/span><\/p>\n

<\/span><\/p>\n

<\/span><\/p>\n

###install.packages(“ggalluvial”)<\/span><\/p>\n

###<\/span>\u52a0\u8f7dR<\/span>\u5305<\/span><\/p>\n

library(ggalluvial)<\/span><\/p>\n

<\/span><\/p>\n

<\/span><\/p>\n

#<\/span>\u5b9a\u4e49\u989c\u8272\uff0c\u540e\u9762\u4ece\u8fd9\u91cc\u9009\u989c\u8272<\/span><\/p>\n

mycol <- rep(c(“#223D6C”,”#D20A13″,”#FFD121″,”#088247″,”#11AA4D”,”#58CDD9″,”#7A142C”,”#5D90BA”,”#029149″,”#431A3D”,”#91612D”,”#6E568C”,”#E0367A”,”#D8D155″,”#64495D”,”#7CC767″),3)<\/span><\/p>\n

<\/span><\/p>\n

#<\/span>\u683c\u5f0f\u8f6c\u6362<\/span><\/p>\n

UCB_lodes <- to_lodes_form(df[,1:ncol(df)],<\/span><\/p>\n

axes = 1:ncol(df),<\/span><\/span><\/p>\n

id = “Cohort”)<\/span><\/span><\/p>\n

dim(UCB_lodes)<\/span><\/p>\n

<\/span><\/p>\n

head(UCB_lodes)<\/span><\/p>\n

<\/span><\/p>\n

pdf(“1sankey.pdf”)<\/span><\/p>\n

<\/span><\/p>\n

ggplot(UCB_lodes,<\/span><\/p>\n

aes(x = x, stratum = stratum, alluvium = Cohort,<\/span><\/span><\/p>\n

fill = stratum, label = stratum)) +<\/span><\/span><\/p>\n

scale_x_discrete(expand = c(0, 0)) +<\/span><\/span><\/p>\n

geom_flow(width = 1\/8) + #<\/span>\u7ebf\u8ddf\u65b9\u5757\u95f4\u7a7a\u9699\u7684\u5bbd\u7a84<\/span><\/p>\n

geom_stratum(alpha = .9,width = 1\/10) + #<\/span>\u65b9\u5757\u7684\u900f\u660e\u5ea6\u3001\u5bbd\u5ea6<\/span><\/p>\n

geom_text(stat = “stratum”, size = 3,color=”black”) + #<\/span>\u6587\u5b57\u5927\u5c0f\u3001\u989c\u8272<\/span><\/p>\n

<\/span><\/p>\n

#<\/span>\u4e0d\u559c\u6b22\u9ed8\u8ba4\u7684\u914d\u8272\u65b9\u6848\uff0c\u7528\u524d\u9762\u81ea\u5df1\u5199\u7684\u914d\u8272\u65b9\u6848<\/span><\/p>\n

scale_fill_manual(values = mycol) +<\/span><\/span><\/p>\n

<\/span><\/p>\n

xlab(“”) + ylab(“”) +<\/span><\/p>\n

theme_bw() + #<\/span>\u53bb\u9664\u80cc\u666f\u8272<\/span><\/p>\n

theme(panel.grid =element_blank()) + #<\/span>\u53bb\u9664\u7f51\u683c\u7ebf<\/span><\/p>\n

theme(panel.border = element_blank()) + #<\/span>\u53bb\u9664\u5916\u5c42\u8fb9\u6846<\/span><\/p>\n

theme(axis.line = element_blank(),axis.ticks = element_blank(),axis.text = element_blank()) + #<\/span>\u53bb\u6389\u5750\u6807\u8f74<\/span><\/p>\n

ggtitle(“”)+<\/span><\/span><\/p>\n

guides(fill = FALSE)<\/span><\/span><\/p>\n

dev.off()<\/span><\/p>\n

<\/span><\/p>\n

###<\/span>\u8fd8\u53ef\u4ee5\u53ea\u9009\u5176\u4e2d\u4e00\u90e8\u5206\u5217\u6765\u753b\uff0c\u6b64\u5904\u53ea\u753b\u7b2c\u4e00\u5217\u548c\u7b2c\u4e09\u5217<\/span><\/p>\n

UCB_lodes <- to_lodes_form(df[,c(1,3)],<\/span><\/p>\n

axes = 1:2,<\/span><\/span><\/p>\n

id = “Cohort”)<\/span><\/span><\/p>\n<\/section>\n

\n

\"\u6851\u57fa\u56fe\uff08Sankey<\/p>\n

\u7ed3\u679c\u56fe\u5c55\u793a<\/span><\/p>\n

\u6587\u672b\u9644\u4ee3\u7801\u548c\u6570\u636e\uff0c\u5173\u6ce8\u5c0f\u679c\uff0c\u6084\u6084\u53d8\u5f3a\u54e6\u3002<\/span><\/p>\n<\/section>\n

\n

\"\u6851\u57fa\u56fe\uff08Sankey<\/p>\n<\/section>\n<\/section>\n

\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n

\n
\n
\n
\n
\n
<\/section>\n<\/section>\n<\/section>\n<\/section>\n
\n
\n

\u63a8\u8350\u9605\u8bfb<\/strong><\/p>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n