{"id":27980,"date":"2024-02-04T17:16:44","date_gmt":"2024-02-04T09:16:44","guid":{"rendered":"http:\/\/www.biocloudservice.com\/wordpress\/?p=27980"},"modified":"2024-02-04T17:19:32","modified_gmt":"2024-02-04T09:19:32","slug":"%e5%b0%8f%e6%9e%9c%e5%b8%a6%e4%bd%a0%e7%8e%a9%e8%bd%ac%e5%a4%9a%e5%8f%98%e9%87%8f%e6%95%b0%e6%8d%ae%ef%bc%9a%e5%a6%82%e4%bd%95%e5%b7%a7%e7%94%a8corrplot%e5%8c%85%e8%a7%a3%e6%9e%90%e5%90%84%e5%8f%98","status":"publish","type":"post","link":"http:\/\/www.biocloudservice.com\/wordpress\/?p=27980","title":{"rendered":"\u5c0f\u679c\u5e26\u4f60\u73a9\u8f6c\u591a\u53d8\u91cf\u6570\u636e\uff1a\u5982\u4f55\u5de7\u7528corrplot\u5305\u89e3\u6790\u5404\u53d8\u91cf\u95f4\u7684\u76f8\u5173\u6027"},"content":{"rendered":"

Hello\uff0c\u5404\u4f4d\u5c0f\u4f19\u4f34\u5927\u5bb6\u597d\uff0c\u5f88\u5f00\u5fc3\uff0c\u5c0f\u679c\u53c8\u5982\u671f\u548c\u5927\u5bb6\u89c1\u9762\u4e86\u54e6\uff0c\u4e0d\u77e5\u9053\u5927\u5bb6\u6709\u6ca1\u6709\u9047\u5230\u8fc7\u8fd9\u6837\u7684\u95ee\u9898\uff1a\u6211\u4eec\u5728\u505a\u5b9e\u9a8c\u6216\u6570\u636e\u5206\u6790\u7684\u65f6\u5019\u8bbe\u7f6e\u4e86\u591a\u4e2a\u53d8\u91cf\uff0c\u7a81\u7136\uff0c\u7075\u611f\u8ff8\u53d1\uff0c\u60f3\u8981\u770b\u4e00\u4e0b\u662f\u5426\u8fd9\u51e0\u4e2a\u53d8\u91cf\u4e4b\u95f4\u4e5f\u5b58\u5728\u4ec0\u4e48\u5173\u7cfb\u5462\uff1f\u8fd9\u65f6\u5927\u5bb6\u5e94\u8be5\u5982\u4f55\u5904\u7406\uff0c\u8981\u600e\u4e48\u624d\u80fd\u8c01\u548c\u8c01\u7684\u5173\u7cfb\u662f\u6b63\u76f8\u5173\uff0c\u6216\u8005\u54ea\u4e24\u4e2a\u53d8\u91cf\u4e4b\u95f4\u662f\u8d1f\u76f8\u5173\u5462\uff1f\u4eca\u5929\u5404\u4f4d\u5c0f\u4f19\u4f34\u53ef\u771f\u662f\u770b\u5bf9\u4e86\uff0c\u5c0f\u679c\u544a\u8bc9\u5927\u5bb6\uff0c\u5728R\u8bed\u8a00\u4e2d\u7684\u786e\u6709\u4e00\u4e2a\u51fd\u6570\u80fd\u8ba1\u7b97\u5404\u53d8\u91cf\u4e4b\u95f4\u7684\u76f8\u5173\u6027\u7cfb\u6570\u2014 cor()<\/strong>\u3002<\/p>\n

cor()<\/strong>\u51fd\u6570\u53ef\u4ee5\u975e\u5e38\u7b80\u4fbf\u7684\u8ba1\u7b97\u51fa\u5404\u8fde\u7eed\u53d8\u91cf\u4e4b\u95f4\u7684\u76f8\u5173\u7cfb\u6570\uff0c\u4f46\u5f53\u53d8\u91cf\u975e\u5e38\u591a\u65f6\u8fd4\u56de\u7684\u76f8\u5173\u7cfb\u6570\u4e00\u5b9a\u4f1a\u8ba9\u5404\u4f4d\u5c0f\u4f19\u4f34\u770b\u82b1\u4e86\u773c\u3002\u56e0\u6b64\u6211\u4eec\u8feb\u4e0d\u53ca\u5f85\u7684\u9700\u8981\u4e00\u4e2a\u80fd\u5c06\u76f8\u5173\u6027\u77e9\u9635\u53ef\u89c6\u5316\u7684\u65b9\u6cd5\uff0c\u867d\u7136\u6709\u5f88\u591a\u65b9\u6cd5\u80fd\u8fdb\u884c\u76f8\u5173\u6027\u77e9\u9635\u7684\u53ef\u89c6\u5316\uff0c\u4e14\u57fa\u7840\u7ed8\u56fe\u4e5f\u80fd\u5b8c\u6210\uff0c\u4f46\u5728\u6211\u5fc3\u76ee\u4e2d\uff0c\u6700\u597d\u7528\u7684\u4e00\u5b9a\u8fd8\u662fcorrplot\u5305\u3002<\/p>\n

\u6487\u5f00\u5b83\u662f\u56fd\u4ea7\u7684R\u5305\u5916\uff0c\u672c\u8eab\u5b83\u7684\u4f7f\u7528\u5c31\u975e\u5e38\u7b80\u4fbf\uff0c\u5e76\u80fd\u6309\u7167\u81ea\u5df1\u7684\u5ba1\u7f8e\u5bf9\u5176\u53ef\u89c6\u5316\u65b9\u6cd5\u3001\u56fe\u5f62\u5e03\u5c40\u3001\u989c\u8272\u3001\u56fe\u4f8b\u3001\u6587\u672c\u6807\u7b7e\u7b49\u5904\u8fdb\u884c\u81ea\u5b9a\u4e49\u7ed8\u5236\u3002\u53e6\u5916\uff0c\u867d\u7136\u8be5\u5305\u63d0\u4f9b\u4e86\u7ea650\u4e2a\u53c2\u6570\uff0c\u4f46\u662f\u5e38\u7528\u7684\u4e5f\u5c3110\u4e2a\u5de6\u53f3\uff0c\u975e\u5e38\u9002\u7528\u4e8e\u521a\u4e0a\u624b\u7684\u5c0f\u4f19\u4f34\u54e6\uff01<\/p>\n

\u4e14corrplot\u5305\u5728\u751f\u7269\u4fe1\u606f\u5b66\u4e2d\u7684\u4f7f\u7528\u9891\u7387\u4e5f\u5f88\u9ad8\u54e6\uff1a\u6bd4\u5982\u5728\u57fa\u56e0\u8868\u8fbe\u548c\u86cb\u767d\u8d28\u7ec4\u5b66\u7684\u7814\u7a76\u4e2d\uff0ccorrplot\u5305\u65e2\u80fd\u5e2e\u52a9\u5927\u5bb6\u5bfb\u627e\u5230\u6709\u76f8\u540c\u8868\u8fbe\u6a21\u5f0f\u7684\u57fa\u56e0\uff0c\u52a9\u529b\u6211\u4eec\u5bf9\u7814\u7a76\u5bf9\u8c61\u7684\u67d0\u79cd\u5206\u5b50\u673a\u5236\u7684\u89e3\u6790\uff1b\u4e5f\u80fd\u5e2e\u52a9\u5404\u4f4d\u5c0f\u4f19\u4f34\u53ef\u89c6\u5316\u86cb\u767d\u8d28\u4e4b\u95f4\u7684\u76f8\u4e92\u5173\u7cfb\uff0c\u5e2e\u52a9\u5206\u6790\u7f51\u7edc\u7684\u6a21\u5f0f\u548c\u7ed3\u6784\uff0c\u4ee5\u6b64\u6765\u7b80\u5316\u5404\u4f4d\u7684\u7814\u7a76\u54e6\u3002<\/p>\n

\u603b\u7684\u6765\u8bf4\uff0ccorrplot \u5305\u5728\u751f\u7269\u4fe1\u606f\u5b66\u4e2d\u63d0\u4f9b\u4e86\u4e00\u4e2a\u5f3a\u5927\u800c\u7075\u6d3b\u7684\u5de5\u5177\uff0c\u53ef\u4ee5\u901a\u8fc7\u76f4\u89c2\u53ef\u89c6\u5316\u7684\u65b9\u5f0f\u5e2e\u52a9\u5927\u5bb6\u7406\u89e3\u751f\u7269\u5206\u5b50\u4e4b\u95f4\u7684\u5173\u7cfb\uff0c\u8fdb\u800c\u4ece\u5927\u89c4\u6a21\u6570\u636e\u4e2d\u63d0\u53d6\u6709\u610f\u4e49\u7684\u4fe1\u606f\u3002\u8bf4\u5230\u5927\u89c4\u6a21\u6570\u636e\uff0c\u4e0d\u77e5\u9053\u5927\u5bb6\u90fd\u7528\u4ec0\u4e48\u8f6f\u4ef6\u6216\u8005\u7cfb\u7edf\u8fdb\u884c\u5904\u7406\uff0c\u5c0f\u679c\u8fd9\u91cc\u5462\u63a8\u8350\u5927\u5bb6\u4f7f\u7528Linux\u7cfb\u7edf\u54e6\uff0c\u8be5\u7cfb\u7edf\u754c\u9762\u5e72\u51c0\uff0c\u547d\u4ee4\u7b80\u5355\uff0c\u6709\u57fa\u56e0\u7ec4\u3001\u8f6c\u5f55\u7ec4\u7b49\u6d4b\u5e8f\u6570\u636e\u7684\u5904\u7406\u6781\u5176\u53cb\u597d\uff0c\u5982\u679c\u5927\u5bb6\u6ca1\u6709\u7684\u8bdd\uff0c\u53ef\u4ee5\u7ec3\u4e60\u6548\u679c\u8fdb\u884c\u79df\u8d41\u54e6\u3002<\/p>\n

\u90a3\u597d\u5427\uff0c\u5404\u4f4d\u770b\u5b98\uff0c\u54b1\u4eec\u95f2\u8bdd\u5c11\u53d9\uff0c\u4e0a\u5e72\u8d27\uff01<\/p>\n

#corrplot\u7684\u5b89\u88c5\u4e0e\u8c03\u7528<\/p>\n

install.packages(‘corrplot’)<\/p>\n

library(corrplot)<\/p>\n

library(tidyverse)<\/p>\n

library(RColorBrewer)<\/p>\n

\u4eca\u5929\u6211\u4eec\u7684\u6d4b\u8bd5\u6570\u636e\u662f\u6211\u4eec20\u4e2a\u6837\u672c\u76847\u4e2a\u5171\u540c\u57fa\u56e0\u7684\u5dee\u5f02\u500d\u6570<\/p>\n

<\/a> #\u8bfb\u5165\u6570\u636e<\/p>\n

data <- read.table(‘\u8f93\u5165\u6570\u636e.txt’)<\/p>\n

<\/p>\n

#\u5bf9\u4ee5\u4e0a\u6570\u636e\u8fdb\u884c\u76f8\u5173\u6027\u5206\u6790<\/p>\n

cor <- cor(data)<\/p>\n

cor<\/p>\n

<\/p>\n

\u4ee5\u4e0a\u5c31\u662fdata\u7684\u76f8\u5173\u6027\uff0c\u5927\u5bb6\u5176\u5b9e\u5f88\u96be\u5feb\u901f\u51c6\u786e\u7684\u627e\u5230\u60f3\u8981\u4fe1\u606f\uff0c\u56e0\u6b64\u6211\u4eec\u5f15\u5165\u53ef\u89c6\u5316\u5de5\u5177corrplot\u3002<\/p>\n

#\u7b80\u5355\u51fa\u56fe<\/p>\n

P1 <- corrplot(cor)<\/p>\n

<\/p>\n

#\u6539\u53d8\u5c55\u793a\u5f62\u72b6<\/p>\n

P2 <- corrplot(cor, #\u7b80\u5355\u7ed8\u56fe<\/p>\n

#\u6539\u53d8\u5f62\u5f0f”circle”, “square”, “ellipse”, “number”, “shade”, “color”, “pie”<\/p>\n

method = ‘color’,<\/p>\n

#\u5c55\u793a\u7c7b\u578b”full”, “lower”, “upper”<\/p>\n

type = ‘upper’)<\/p>\n

<\/p>\n

#\u6539\u53d8\u989c\u8272<\/p>\n

col <- colorRampPalette(c(“blue”, “red”))(20)<\/p>\n

P3 <- corrplot(cor, #\u7b80\u5355\u7ed8\u56fe<\/p>\n

#\u6539\u53d8\u5f62\u5f0f”circle”, “square”, “ellipse”, “number”, “shade”, “color”, “pie”<\/p>\n

method = ‘color’,<\/p>\n

#\u5c55\u793a\u7c7b\u578b”full”, “lower”, “upper”<\/p>\n

type = ‘upper’,<\/p>\n

col = col, #\u6539\u53d8\u989c\u8272\uff0c<\/p>\n

# bg = ‘black’ , #\u6539\u53d8\u80cc\u666f\u8272<\/p>\n

title = ‘test for corrplot’,<\/p>\n

is.corr = T , #\u8f93\u5165\u662f\u5426\u4e3a\u76f8\u5173\u77e9\u9635\uff0c\u4e00\u822c\u90fd\u662fT<\/p>\n

mar = c(5,5,5,5)) #\u4e0e\u4e0a\u4e0b\u5de6\u53f3\u7684\u8ddd\u79bb<\/p>\n

<\/p>\n

#\u6539\u53d8\u8fb9\u6846\u989c\u8272\u5e76\u6dfb\u52a0\u76f8\u5173\u6027\u7cfb\u6570<\/p>\n

P4 <- corrplot(cor, #\u7b80\u5355\u7ed8\u56fe<\/p>\n

#\u6539\u53d8\u5f62\u5f0f”circle”, “square”, “ellipse”, “number”, “shade”, “color”, “pie”<\/p>\n

method = ‘color’,<\/p>\n

#\u5c55\u793a\u7c7b\u578b”full”, “lower”, “upper”<\/p>\n

type = ‘upper’,<\/p>\n

col = col, #\u6539\u53d8\u989c\u8272\uff0c<\/p>\n

# bg = ‘black’ , #\u6539\u53d8\u80cc\u666f\u8272<\/p>\n

title = ‘test for corrplot’,<\/p>\n

is.corr = T , #\u8f93\u5165\u662f\u5426\u4e3a\u76f8\u5173\u77e9\u9635\uff0c\u4e00\u822c\u90fd\u662fT<\/p>\n

#add = T , #\u53ef\u901a\u8fc7\u6539\u53d8type\u5408\u5e76\u4e24\u79cd\u7c7b\u578b\u7684\u56fe<\/p>\n

diag = F, #\u662f\u5426\u5c55\u793a\u5bf9\u89d2\u7ebf\u7ed3\u679c<\/p>\n

outline = T, #\u662f\u5426\u52a0\u5916\u6846\u7ebf<\/p>\n

addgrid.col = ‘black’, #\u6539\u53d8\u5916\u6846\u7ebf\u7684\u989c\u8272<\/p>\n

addCoef.col = ‘grey’, #\u6539\u53d8\u6dfb\u52a0\u6570\u5b57\u7684\u989c\u8272<\/p>\n

addCoefasPercent = T, #\u6539\u53d8\u586b\u5145\u6570\u636e\u5f62\u5f0f\uff0c\u6210\u4e3a\u767e\u5206\u6bd4\u5f62\u5f0f<\/p>\n

mar = c(5,5,5,5), #\u4e0e\u4e0a\u4e0b\u5de6\u53f3\u7684\u8ddd\u79bb<\/p>\n

#\u5bf9\u56fe\u5f62\u8fdb\u884c\u6392\u5e8f”original”, “AOE”, “FPC”, “hclust”, “alphabet”<\/p>\n

order = c(‘AOE’),<\/p>\n

#\u5c42\u6b21\u805a\u7c7b\u7684\u65b9\u6cd5”complete”, “ward”, “ward.D”, “ward.D2”, “single”, “average”,”mcquitty”, “median”, “centroid”<\/p>\n

hclust.method = c(‘median’))<\/p>\n

<\/p>\n

#\u6539\u53d8\u884c\u5217\u540d\u7684\u8868\u73b0\u65b9\u5f0f\uff0c\u4ee5\u66f4\u597d\u7684\u62fc\u56fe<\/p>\n

P5 <- corrplot(cor, #\u7b80\u5355\u7ed8\u56fe<\/p>\n

#\u6539\u53d8\u5f62\u5f0f”circle”, “square”, “ellipse”, “number”, “shade”, “color”, “pie”<\/p>\n

method = ‘color’,<\/p>\n

#\u5c55\u793a\u7c7b\u578b”full”, “lower”, “upper”<\/p>\n

type = ‘upper’,<\/p>\n

col = col, #\u6539\u53d8\u989c\u8272\uff0c<\/p>\n

# bg = ‘black’ , #\u6539\u53d8\u80cc\u666f\u8272<\/p>\n

title = ‘test for corrplot’,<\/p>\n

is.corr = T , #\u8f93\u5165\u662f\u5426\u4e3a\u76f8\u5173\u77e9\u9635\uff0c\u4e00\u822c\u90fd\u662fT<\/p>\n

#add = T , #\u53ef\u901a\u8fc7\u6539\u53d8type\u5408\u5e76\u4e24\u79cd\u7c7b\u578b\u7684\u56fe<\/p>\n

diag = F, #\u662f\u5426\u5c55\u793a\u5bf9\u89d2\u7ebf\u7ed3\u679c<\/p>\n

outline = T, #\u662f\u5426\u52a0\u5916\u6846\u7ebf<\/p>\n

addgrid.col = ‘black’, #\u6539\u53d8\u5916\u6846\u7ebf\u7684\u989c\u8272<\/p>\n

addCoef.col = ‘grey’, #\u6539\u53d8\u6dfb\u52a0\u6570\u5b57\u7684\u989c\u8272<\/p>\n

addCoefasPercent = T, #\u6539\u53d8\u586b\u5145\u6570\u636e\u5f62\u5f0f\uff0c\u6210\u4e3a\u767e\u5206\u6bd4\u5f62\u5f0f<\/p>\n

mar = c(5,5,5,5), #\u4e0e\u4e0a\u4e0b\u5de6\u53f3\u7684\u8ddd\u79bb<\/p>\n

#\u5bf9\u56fe\u5f62\u8fdb\u884c\u6392\u5e8f”original”, “AOE”, “FPC”, “hclust”, “alphabet”<\/p>\n

order = c(‘hclust’),<\/p>\n

#\u5c42\u6b21\u805a\u7c7b\u7684\u65b9\u6cd5”complete”, “ward”, “ward.D”, “ward.D2”, “single”, “average”,”mcquitty”, “median”, “centroid”<\/p>\n

hclust.method = c(‘median’),<\/p>\n

#\u6539\u53d8\u6587\u672c\u6807\u7b7e\u7684\u4f4d\u7f6e’lt’, ‘ld’, ‘td’, ‘d’ or ‘n’. ‘lt’<\/p>\n

tl.pos = ‘dt’, #\u53ef\u7528\u4e8e\u4e24\u4e2a\u56fe\u62fc\u63a5\u65f6\u4f7f\u7528<\/p>\n

tl.cex = 0.8,tl.col = ‘black’ #\u6587\u672c\u5927\u5c0f\u548c\u989c\u8272<\/p>\n

)<\/p>\n

<\/p>\n

#\u5bf9\u56fe\u4f8b\u8fdb\u884c\u8c03\u6574<\/p>\n

P6 <- corrplot(cor, #\u7b80\u5355\u7ed8\u56fe<\/p>\n

#\u6539\u53d8\u5f62\u5f0f”circle”, “square”, “ellipse”, “number”, “shade”, “color”, “pie”<\/p>\n

method = ‘color’,<\/p>\n

#\u5c55\u793a\u7c7b\u578b”full”, “lower”, “upper”<\/p>\n

type = ‘upper’,<\/p>\n

cl.pos = ‘r’, #’r”b”n’\u7684\u56fe\u4f8b\u4f4d\u7f6e<\/p>\n

cl.cex = 0.5 , cl.ratio = 0.3, #\u56fe\u4f8b\u5927\u5c0f\u548c\u5bbd\u5ea6<\/p>\n

cl.length = 7 , #\u6807\u7b7e\u4e2a\u6570<\/p>\n

cl.align.text = ‘r’, #\u6807\u7b7e\u6587\u672c\u5bf9\u9f50\u65b9\u5f0fl,r,c\u4e09\u79cd<\/p>\n

cl.offset = 0.1 #\u6807\u7b7e\u4e0e\u56fe\u4f8b\u7684\u504f\u79fb\u91cf<\/p>\n

)<\/p>\n

<\/p>\n

#\u5bf9\u5148\u7684\u4f4d\u7f6e\u8fdb\u884c\u8c03\u6574<\/p>\n

P7 <- corrplot(cor, #\u7b80\u5355\u7ed8\u56fe<\/p>\n

#\u6539\u53d8\u5f62\u5f0f”circle”, “square”, “ellipse”, “number”, “shade”, “color”, “pie”<\/p>\n

method = ‘shade’,<\/p>\n

#\u5c55\u793a\u7c7b\u578b”full”, “lower”, “upper”<\/p>\n

type = ‘upper’,<\/p>\n

addshade = ‘positive’ #\u5728shade\u4e0b\u6709\u7528’negative’, ‘positive’ or ‘all<\/p>\n

)<\/p>\n

<\/p>\n

#\u5bf9\u6570\u5b57\u8fdb\u884c\u8c03\u6574<\/p>\n

P8 <- corrplot(cor, #\u7b80\u5355\u7ed8\u56fe<\/p>\n

#\u6539\u53d8\u5f62\u5f0f”circle”, “square”, “ellipse”, “number”, “shade”, “color”, “pie”<\/p>\n

method = ‘number’,<\/p>\n

#\u5c55\u793a\u7c7b\u578b”full”, “lower”, “upper”<\/p>\n

type = ‘upper’,<\/p>\n

number.cex = 2, #\u6570\u5b57\u5927\u5c0f<\/p>\n

number.font = 1, #\u5b57\u4f53\u5f62\u5f0f<\/p>\n

number.digits = 2) #\u5c0f\u6570\u7684\u4fdd\u7559\u7ed3\u679c<\/p>\n

<\/p>\n

#\u62fc\u56fe<\/p>\n

P9 <- corrplot(cor, #\u7b80\u5355\u7ed8\u56fe<\/p>\n

#\u6539\u53d8\u5f62\u5f0f”circle”, “square”, “ellipse”, “number”, “shade”, “color”, “pie”<\/p>\n

method = ‘number’,<\/p>\n

#\u5c55\u793a\u7c7b\u578b”full”, “lower”, “upper”<\/p>\n

type = ‘lower’,<\/p>\n

col = col, #\u6539\u53d8\u989c\u8272<\/p>\n

number.cex = 1, #\u6570\u5b57\u5927\u5c0f<\/p>\n

number.font = 1, #\u5b57\u4f53\u5f62\u5f0f<\/p>\n

#add= T, #\u6dfb\u52a0\u53e6\u4e00\u4e2a\u56fe<\/p>\n

#\u6539\u53d8\u6587\u672c\u6807\u7b7e\u7684\u4f4d\u7f6e’lt’, ‘ld’, ‘td’, ‘d’ or ‘n’. ‘lt’<\/p>\n

tl.pos = ‘d’,<\/p>\n

tl.col = ‘black’,<\/p>\n

number.digits = 2 #\u5c0f\u6570\u7684\u4fdd\u7559\u7ed3\u679c<\/p>\n

)<\/p>\n

P9 <- corrplot(cor, #\u7b80\u5355\u7ed8\u56fe<\/p>\n

#\u6539\u53d8\u5f62\u5f0f”circle”, “square”, “ellipse”, “number”, “shade”, “color”, “pie”<\/p>\n

method = ‘color’,<\/p>\n

#\u5c55\u793a\u7c7b\u578b”full”, “lower”, “upper”<\/p>\n

type = ‘upper’,<\/p>\n

col = col, #\u6539\u53d8\u989c\u8272\uff0c<\/p>\n

# bg = ‘black’ , #\u6539\u53d8\u80cc\u666f\u8272<\/p>\n

title = ‘test for corrplot’,<\/p>\n

is.corr = T , #\u8f93\u5165\u662f\u5426\u4e3a\u76f8\u5173\u77e9\u9635\uff0c\u4e00\u822c\u90fd\u662fT<\/p>\n

add = T , #\u53ef\u901a\u8fc7\u6539\u53d8type\u5408\u5e76\u4e24\u79cd\u7c7b\u578b\u7684\u56fe<\/p>\n

diag = F, #\u662f\u5426\u5c55\u793a\u5bf9\u89d2\u7ebf\u7ed3\u679c<\/p>\n

#\u6539\u53d8\u6587\u672c\u6807\u7b7e\u7684\u4f4d\u7f6e’lt’, ‘ld’, ‘td’, ‘d’ or ‘n’. ‘lt’<\/p>\n

tl.pos = ‘d’, #\u53ef\u7528\u4e8e\u4e24\u4e2a\u56fe\u62fc\u63a5\u65f6\u4f7f\u7528<\/p>\n

tl.cex = 0.8,tl.col = ‘black’, #\u6587\u672c\u5927\u5c0f\u548c\u989c\u8272<\/p>\n

cl.pos = ‘n’<\/p>\n

) <\/p>\n

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\u90a3\u5728\u6211\u4eec\u8fd9\u4e2a\u4e8b\u4f8b\u4e2d\u5982\u4f55\u6b63\u786e\u89e3\u8bfb\u4e0a\u56fe\u7684\u751f\u7269\u5b66\u610f\u4e49\u5462\uff1f<\/p>\n

\u5047\u8bbe\u4ee5\u4e0a\u6837\u672c\u662f\u5b9e\u9a8c\u7ec4\u4e0e\u8f6c\u5f55\u7ec4\u7684\u5dee\u5f02\u8868\u8fbe\u57fa\u56e0\u4e2d\u663e\u8457\u5dee\u5f02\u7684\u5b9e\u9a8c\u7ec4\u4e2d\u76847\u4e2a\u57fa\u56e0\uff0c\u90a3\u4e48\u968f\u7740\u76f8\u5bf9\u4e8e\u5bf9\u7167\u7ec4\u7684\u5b9e\u9a8c\u6761\u4ef6\u7684\u6539\u53d8\uff0c\u4f7f\u5f97gene3\u3001gene4\u3001gene5\u548cgene6\u6709\u572810\u4e2a\u6837\u672c\u4e2d\u7740\u76f8\u540c\u7684\u8868\u8fbe\u6a21\u5f0f\uff0c\u5373\u4e00\u540c\u4e0a\u8c03\u6216\u4e0b\u8c03\uff0c\u8bf4\u660e\u4ed6\u4eec\u53ef\u80fd\u81f4\u529b\u4e8e\u540c\u610f\u901a\u8def\u6216\u540c\u4e00\u751f\u7269\u5b66\u4f5c\u7528\u54e6\uff01<\/p>\n

\u5f53\u7136\uff0c\u5bf9\u4e8e\u76f8\u5173\u6027\u70ed\u56fe\u7ed8\u5236\u7684R\u5305\u8fdc\u4e0d\u6b62\u4e8e\u6b64\uff0c\u8fd8\u6709\u5176\u4f59\u591a\u79cdR\u5305\u80fd\u5b8c\u6210\u8fd9\u9879\u5de5\u4f5c\uff0c\u5982\u679c\u5927\u5bb6\u611f\u5174\u8da3\u7684\u8bdd\uff0c\u53ef\u4ee5\u5173\u6ce8\u5c0f\u679c\u5f80\u671f\u521b\u4f5c\u7684\u5185\u5bb9\u6216\u70b9\u51fb\u4e0b\u65b9\u94fe\u63a5\u8fdb\u5165\u6211\u4eec\u7684\u4e91\u751f\u4fe1\u5e73\u53f0\u67e5\u770b\u54e6\uff01<\/p>\n

\u53e6\u5916\u5982\u679c\u5728\u4f7f\u7528\u8fc7\u7a0b\u4e2d\u9047\u5230\u4e86\u4efb\u4f55\u95ee\u9898\uff0c\u90fd\u53ef\u4ee5\u968f\u65f6\u6765\u627e\u5c0f\u679c\u8ba8\u8bba\u54e6\uff0c\u8d76\u5feb\u52a0\u5165\u6211\u4eec\u5427\uff01\uff01\u53ef\u80fd\u8fd9\u4e2a\u989c\u8272\u4e0d\u662f\u5f88\u7b26\u5408\u5927\u5bb6\u7684\u9884\u671f\uff0c\u6240\u4ee5\u5404\u4f4d\u5c0f\u4f19\u4f34\u4eec\u53ef\u4ee5\u81ea\u5b9a\u4e49\u989c\u8272\u54e6\uff0c\u5982\u679c\u5927\u5bb6\u89c9\u5f97\u914d\u7f6e\u989c\u8272\u597d\u96be\u554a\uff0c\u4e5f\u53ef\u4ee5\u52a0\u5165\u6211\u4eec\u7684\u4e91\u751f\u4fe1\u5e73\u53f0\uff0c\u91cc\u9762\u6709\u6210\u719f\u7684\u4ee3\u7801\uff0c\u5927\u5bb6\u53ef\u4ee5\u76f4\u63a5\u5c06\u6570\u636e\u4e0a\u4f20\u5230\u670d\u52a1\u5668\u4e2d\u5c31\u53ef\u4ee5\u968f\u610f\u751f\u6210\u60f3\u8981\u7684\u56fe\u7247\u4e86\uff0c\u5e76\u4e14\u4e5f\u652f\u6301\u5404\u79cd\u989c\u8272\u7684\u5b9a\u5236\u54e6\uff0c\u5feb\u6765\u52a0\u5165\u6211\u4eec\u5427\uff01\uff01<\/p>\n

http:\/\/www.biocloudservice.com\/home.html<\/p>\n","protected":false},"excerpt":{"rendered":"

Hello\uff0c\u5404\u4f4d\u5c0f\u4f19\u4f34\u5927\u5bb6\u597d\uff0c\u5f88\u5f00\u5fc3\uff0c\u5c0f\u679c\u53c8\u5982\u671f\u548c\u5927\u5bb6\u89c1\u9762\u4e86\u54e6\uff0c\u4e0d\u77e5\u9053\u5927\u5bb6\u6709\u6ca1\u6709\u9047\u5230\u8fc7\u8fd9\u6837\u7684\u95ee\u9898\uff1a\u6211\u4eec\u5728\u505a\u5b9e\u9a8c […]<\/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\/27980"}],"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=27980"}],"version-history":[{"count":1,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/27980\/revisions"}],"predecessor-version":[{"id":27992,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/27980\/revisions\/27992"}],"wp:attachment":[{"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=27980"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=27980"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=27980"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}