{"id":27805,"date":"2024-02-02T16:33:38","date_gmt":"2024-02-02T08:33:38","guid":{"rendered":"http:\/\/www.biocloudservice.com\/wordpress\/?p=27805"},"modified":"2024-02-02T16:33:39","modified_gmt":"2024-02-02T08:33:39","slug":"%e4%b8%80%e9%81%8d%e5%b0%b1%e4%bc%9a%ef%bc%81pophelper%e5%8c%85%e8%ae%a9%e7%be%a4%e4%bd%93%e9%81%97%e4%bc%a0%e7%a0%94%e7%a9%b6%e8%bd%af%e4%bb%b6structure%e7%9a%84%e8%be%93%e5%87%ba%e7%bb%93%e6%9e%9c","status":"publish","type":"post","link":"http:\/\/www.biocloudservice.com\/wordpress\/?p=27805","title":{"rendered":"\u4e00\u904d\u5c31\u4f1a\uff01pophelper\u5305\u8ba9\u7fa4\u4f53\u9057\u4f20\u7814\u7a76\u8f6f\u4ef6structure\u7684\u8f93\u51fa\u7ed3\u679c\u201c\u6d3b\u201d\u8d77\u6765"},"content":{"rendered":"

\u5404\u4f4d\u5c0f\u4f19\u4f34\u5927\u5bb6\u597d\uff0c\u5c0f\u679c\u53c8\u548c\u5927\u5bb6\u89c1\u9762\u4e86\uff0c\u4eca\u5929\u60f3\u548c\u5927\u5bb6\u804a\u4e00\u4e0b\u7fa4\u4f53\u9057\u4f20\u76f8\u5173\u5185\u5bb9\u3002\u7fa4\u4f53\u9057\u4f20\u5b66\u662f\u9057\u4f20\u5b66\u7684\u4e00\u4e2a\u5206\u652f\uff0c\u7814\u7a76\u7684\u662f\u7fa4\u4f53\u6c34\u5e73\u4e0a\u57fa\u56e0\u7684\u4f20\u9012\u548c\u53d8\u5f02\u3002\u5b83\u5bf9\u7406\u89e3\u7269\u79cd\u7684\u6f14\u5316\u3001\u79cd\u7fa4\u7684\u9057\u4f20\u7ed3\u6784\u4ee5\u53ca\u9057\u4f20\u53d8\u5f02\u7684\u7ef4\u6301\u548c\u4f20\u9012\u5177\u6709\u91cd\u8981\u7684\u610f\u4e49\uff0c\u4e0d\u4ec5\u80fd\u5224\u65ad\u6bcf\u4e2a\u5c0f\u7fa4\u4f53\u7684\u4e2a\u6570\uff0c\u8fd8\u80fd\u5bf9\u7fa4\u4f53\u95f4\u7684\u57fa\u56e0\u4ea4\u6d41\u60c5\u51b5\u53ca\u7269\u79cd\u7684\u8d77\u6e90\u8fdb\u884c\u5224\u65ad\u3002<\/p>\n

\u76ee\u524d\u7fa4\u4f53\u9057\u4f20\u5e38\u7528\u7684\u8f6f\u4ef6\u6709strcture\u3001admixture\uff0c\u8fd9\u4e24\u4e2a\u8f6f\u4ef6\u5747\u80fd\u5bf9\u8fdb\u6e90\u7956\u5148\u7684\u7fa4\u4f53\u7ed3\u6784\u8fdb\u884c\u5206\u6790\uff0c\u4f46\u4e24\u76f8\u6bd4\u8f83\u4e4b\u4e0bstrcture\u8fd0\u884c\u65f6\u95f4\u8981\u6162\u4e00\u4e9b\uff0c\u56e0\u6b64admixture\u53ef\u80fd\u66f4\u53d7\u6b22\u8fce\u3002\u4f46\u4f5c\u4e3a\u8001\u724c\u7fa4\u4f53\u7ed3\u6784\u5206\u6790\u8f6f\u4ef6\uff0c\u5b83\u5728\u884c\u4e1a\u5185\u4f9d\u7136\u5360\u636e\u91cd\u8981\u5730\u4f4d\u3002\u76ee\u524dstrcture\u5206\u522b\u652f\u6301Linux\u3001windows\u4ee5\u53caMac\u7248\u672c\uff0c\u56e0\u4e3a\u6d89\u53ca\u5230\u683c\u5f0f\u8f6c\u6362\u95ee\u9898\uff0c\u6240\u4ee5\u6211\u66f4\u63a8\u8350Linux\u7cfb\u7edf\u4e0b\u7684structure\uff0c\u8fd9\u53ef\u4ee5\u51cf\u5c11\u5404\u4f4d\u5c0f\u4f19\u4f34\u5207\u6362\u8f6f\u4ef6\u7684\u9891\u7387\uff0c\u51cf\u5c11\u4e0d\u5fc5\u8981\u7684\u9ebb\u70e6\u3002\u4f46Linux\u7cfb\u7edf\u7ec8\u7a76\u4e5f\u6709\u5f31\u70b9\uff0c\u5c31\u662f\u4e0d\u80fd\u53ca\u65f6\u51fa\u56fe\uff0c\u56e0\u6b64\u9700\u8981\u914d\u5408\u7b2c\u4e09\u65b9\u8f6f\u4ef6R\u6765\u8fdb\u884c\u56fe\u5f62\u7ed8\u5236\u3002\u5f53\u7136\u5566\uff0cLinux\u53cawin\u4e2d\u90fd\u6709R\uff0c\u4e5f\u5c31\u662f\u8bf4\u4f60\u8981\u662f\u5b66\u4f1a\u4e86\u4ee5\u4e0b\u4ee3\u7801\u5185\u5bb9\uff0c\u5404\u4f4d\u5c0f\u4f19\u4f34\u4e5f\u662f\u53ef\u4ee5\u76f4\u63a5\u5728Linux\u4e2d\u5b9e\u73b0\u56fe\u5f62\u7ed8\u5236\u7684\u54e6\uff01<\/p>\n

\u6211\u4eec\u901a\u5e38\u4ee5\u5806\u53e0\u67f1\u72b6\u56fe\u7684\u5f62\u5f0f\u5c55\u793a\u7fa4\u4f53\u7ed3\u6784\u7ed3\u679c\uff0cpophelper\u5305\u5c31\u80fd\u5b9e\u73b0\u8be5\u8bc9\u6c42\uff0c\u4e14\u8fd8\u6709\u66f4\u591a\u7684\u51fd\u6570\u7b49\u5f85\u5927\u5bb6\u7684\u5f00\u53d1\u3002\u4f46\u662f\u672c\u6b21\u4ecb\u7ecd\u7684R\u5305\u4f7f\u7528\u65f6\u8f83\u4e3a\u8017\u8d39\u7cfb\u7edf\u8d44\u6e90\uff0c\u5e76\u975e\u5f88\u5efa\u8bae\u5229\u7528\u7535\u8111\u8fd0\u884c\uff0c\u5e0c\u671b\u5927\u5bb6\u4f7f\u7528\u670d\u52a1\u5668\u8fd0\u884c\uff0c\u5982\u679c\u6ca1\u6709\u81ea\u5df1\u7684\u670d\u52a1\u5668\u6b22\u8fce\u8054\u7cfb\u6211\u4eec\u8fdb\u884c\u670d\u52a1\u5668\u79df\u8d41\u54e6~<\/p>\n

\u4e0b\u9762\u8ba9\u6211\u4eec\u4e00\u8d77\u6765\u5b66\u4e60\u8fd9\u4e2a\u5389\u5bb3\u7684R\u5305\u5427\uff01\uff01\uff01<\/p>\n

#R\u5305\u7684\u5b89\u88c5\uff081\uff09<\/p>\n

install.packages(‘devtools’)<\/p>\n

devtools::install(‘royfrancis\/pophelper’)<\/p>\n

\u5982\u679c\u51fa\u73b0\u4ee5\u4e0b\u62a5\u9519\uff0c\u53ef\u4ee5\u4f7f\u7528\u7b2c\u4e8c\u79cd\u5b89\u88c5\u65b9\u6cd5<\/p>\n

<\/p>\n

#R\u5305\u7684\u5b89\u88c5\uff082\uff09<\/p>\n

install.packages(c(‘ggplot2′,’gridExtra’,’label’,’switching’,’tidyr’,’remotes’),<\/p>\n

repos = “http:\/\/cloud.r-project.org”)<\/p>\n

#\u68c0\u67e5\u662f\u5426\u6210\u529f\u5b89\u88c5\uff0c\u5982\u679c\u6210\u529f\u5b89\u88c5\u53ef\u62a5pophelper\u7684\u7248\u672c\u4fe1\u606f<\/p>\n

library(pophelper)<\/p>\n

<\/p>\n

\u4e0b\u9762\u8ba9\u6211\u4eec\u5f00\u59cb\u771f\u6b63\u4f7f\u7528\u8be5R\u5305\uff1a<\/p>\n

#\u9996\u5148\u8bbe\u7f6e\u5de5\u4f5c\u76ee\u5f55\uff0c\u6211\u7684structure\u7ed3\u679c\u6587\u4ef6\u88ab\u5b58\u50a8\u5728\u2018F:\\\u7fa4\u4f53\u9057\u4f20\u5b66\u4e60\\2.\u7fa4\u4f53\u7ed3\u6784\u5206\u6790\\2.5structure\u5206\u6790\u2019\u4e2d<\/p>\n

setwd(‘F:\\\\\u7fa4\u4f53\u9057\u4f20\u5b66\u4e60\\\\2.\u7fa4\u4f53\u7ed3\u6784\u5206\u6790\\\\2.5structure\u5206\u6790’)<\/p>\n

#\u8bfb\u53d6\u6587\u4ef6\uff0c\u5c0f\u4f19\u4f34\u4eec\u5728\u505astructure\u65f6\u53ef\u77e5\uff0c\u5176\u8f93\u5165\u6587\u4ef6\u5982\u4e0b\uff0c\u56e0\u6b64\u4e3a\u907f\u514d\u91cd\u590d\u4e66\u5199\u65e0\u7528\u4ee3\u7801\uff0c\u6211\u4eec\u5229\u7528\u5faa\u73af\u8fdb\u884c\u8f93\u5165<\/p>\n

<\/p>\n

files <- list.files(path = ‘.’, #\u6587\u4ef6\u8def\u5f84<\/p>\n

pattern = ‘_f$’, #\u4ee5_f\u7ed3\u5c3e\u7684\u6587\u4ef6<\/p>\n

full.names = F) #\u662f\u5426\u5c55\u793a\u8def\u5f84\u4fe1\u606f<\/p>\n

files #\u67e5\u770bfiles\u7684\u5185\u5bb9<\/p>\n

<\/p>\n

#Q\u77e9\u9635\u9605\u8bfb<\/p>\n

slist <- readQ(files = files, #\u6587\u4ef6<\/p>\n

indlabfromfile = T, #\u6587\u4ef6\u4e2d\u6bcf\u884c\u7684\u547d\u540d<\/p>\n

filetype = ‘structure’) #\u6587\u4ef6\u7c7b\u578bauto’, ‘structure’,’tess2′,’baps’,’basic’ or ‘clumpp’<\/p>\n

<\/p>\n

#\u5bf9\u9f50<\/p>\n

xlist <- alignK(slist)<\/p>\n

<\/p>\n

#\u5408\u5e76\uff0c\u5171\u751f\u621011\u4e2a\u5217\u8868\u5f62\u5f0f\u7684\u6587\u4ef6\uff0c\u5bf9\u5e94\u4e00\u5f00\u59cb\u8bfb\u5165\u768411\u4e2ak\u503c\u6587\u4ef6<\/p>\n

xlist2 <- mergeQ(qlist)<\/p>\n

#\u5982\u679c\u62a5\u9519\u5982\u4e0b<\/p>\n

<\/p>\n

<\/a> #\u9700\u8981\u5229\u7528\u4ee5\u4e0b\u51fd\u6570\u89e3\u51b3\uff0c\u53ef\u76f4\u63a5\u590d\u5236\uff0c\u4f46\u6b63\u5e38\u8f93\u51fa\u7684\u7ed3\u679c\u90fd\u53ef\u7528\u4e0a\u8ff0mergeQ\u8fdb\u884c\u5408\u5e76\uff0c\u5e94\u4e3aalignK\u7ee7\u800cmergeQ\u662f\u540c\u4e00\u4e2a\u51fd\u6570\u4e0b\u7684\u529f\u80fd\u4e14\u5e94\u7528\u987a\u5e8f\u7d27\u6328\u7740<\/p>\n

mergy <- function(x) {<\/p>\n

return(list(Reduce(`+`, x)\/length(x)))<\/p>\n

}<\/p>\n

fun1 <- function(x) as.matrix(unlist(attributes(x)))<\/p>\n

a <- lapply(xlist, fun1)<\/p>\n

b <- as.data.frame(t(as.data.frame(lapply(a, function(x,y) x[y, ], “k”), stringAsFactors = FALSE)), stringsAsFactors = FALSE)<\/p>\n

fun2 <- function(x) if (all(!is.na(as.numeric(as.character(x))))) {<\/p>\n

return(as.numeric(as.character(x)))<\/p>\n

}else {<\/p>\n

return(x)<\/p>\n

}<\/p>\n

b <- as.data.frame(sapply(b, fun2), stringAsFactors = FALSE)<\/p>\n

ord <- order(b[, “k”])<\/p>\n

qlist <- xlist[ord]<\/p>\n

labels <- summariseQ(tabulateQ(qlist, sorttable = FALSE))$k<\/p>\n

x <- unlist(lapply(splitQ(qlist), mergy), recursive = FALSE)<\/p>\n

names(x) <- labels<\/p>\n

xlist2 <- as.qlist(x)<\/p>\n

xlist2<\/p>\n

<\/p>\n

#\u968f\u540e\u8fdb\u884c\u56fe\u5f62\u7ed8\u5236<\/p>\n

P1 <- plotQ(xlist2, #Q\u77e9\u9635<\/p>\n

#\u56fe\u7247\u5408\u5e76,\u56e0\u4e3a\u6211\u4eec\u8f93\u5165\u4e8611\u4e2a\u6587\u4ef6\u6240\u4ee5\u4e0d\u80fd\u9009\u7528sep(\u5355\u4e2a\u8f93\u51fa)<\/p>\n

imgoutput = “join”,<\/p>\n

imgtype = “pdf”,#\u8f93\u51fa\u683c\u5f0f”png”,”jpeg”,”tiff” or “pdf”.<\/p>\n

width = 20,height = 1.2, #\u5bbd\u5ea6\u548c\u9ad8\u5ea6<\/p>\n

showindlab = T, #\u662f\u5426\u5bf9\u6bcf\u4e2aK\u503c\u56fe\u5f62\u7ed8\u5236\u8fb9\u6846<\/p>\n

useindlab = T, #\u5c55\u793a\u5355\u682a\u6807\u7b7e<\/p>\n

indlabhjust = 0.5, #\u5355\u682a\u6807\u7b7e\u6c34\u5e73\u5c45\u4e2d<\/p>\n

indlabangle = 0, #\u5355\u682a\u6807\u7b7e\u89d2\u5ea6<\/p>\n

indlabsize = 1.2, #\u5355\u682a\u6807\u7b7e\u6587\u672c\u5927\u5c0f<\/p>\n

sortind = ‘all’, #\u6392\u5e8f\uff0c\u57fa\u4e8e\u805a\u7c7b\u6392\u5e8f<\/p>\n

#K\u503c\u56fe\u4e0d\u4f1a\u5171\u4eab\u5355\u682a\u6807\u7b7e\u540d,\u4e14\u53ea\u5728 imgoutput = “join”\u65f6\u6709\u6548<\/p>\n

sharedindlab = F,<\/p>\n

panelspacer = 0.02, #\u4e0d\u540ck\u503c\u56fe\u7684\u95f4\u9699<\/p>\n

indlabspacer = 0, #\u4e0d\u540ck\u503c\u56fe\u4e2d\u5355\u682a\u7a7a\u9699<\/p>\n

indlabcol = “black”, #k\u503c\u6587\u672c\u989c\u8272<\/p>\n

showtitle = T,titlelab = “”,titlecol = “black”,titlehjust = 0.5, #\u6807\u9898<\/p>\n

showsp = T,sppos = “left”, #k\u503c\u6807\u7b7e\u5c55\u793a,\u4e5f\u6709\u2018right\u2019<\/p>\n

splab = paste0(“K=”,1:11), #k\u503c\u6807\u7b7e<\/p>\n

splabangle = 180, #\u6807\u7b7e\u89d2\u5ea6<\/p>\n

dpi = 600, #\u8f93\u51fa\u5206\u8fa8\u7387<\/p>\n

outputfilename = paste0(“structure1”), #\u8f93\u51fa\u6587\u4ef6\u7684\u540d\u79f0<\/p>\n

units = “cm”, #\u8f93\u51fa\u6587\u4ef6\u7684\u5927\u5c0f<\/p>\n

exportplot = T, #\u56fe\u7247\u4fdd\u5b58<\/p>\n

exportpath = getwd()) #\u4fdd\u5b58\u8def\u5f84<\/p>\n

#\u5c4a\u65f6\u4f1a\u5728\u81ea\u5df1\u8bbe\u7f6e\u7684\u5de5\u4f5c\u76ee\u5f55\u4e0b\u51fa\u73b0\u540d\u4e3astructure1.pdf\u7684\u76ee\u6807\u6587\u4ef6<\/p>\n

<\/p>\n

#\u6b64\u5916\u6211\u4eec\u8fd8\u53ef\u4ee5\u8fdb\u884c\u5206\u7ec4\u663e\u793a<\/p>\n

#\u5f15\u5165\u5206\u7ec4\u4fe1\u606f<\/p>\n

pop <- read.table(‘group.txt’, header = T, sep = ‘\\t’, stringsAsFactors = F,row.names = 1)<\/p>\n

pop<\/p>\n

<\/p>\n

##\u7ed8\u56fe<\/p>\n

P2 <- plotQ(xlist2,imgoutput = “join”,<\/p>\n

imgtype = “png”, #\u8f93\u51fa\u683c\u5f0f\u7684\u53d8\u5316<\/p>\n

height = 1.2,width = 20,<\/p>\n

showindlab = T,useindlab = T,sharedindlab = T,<\/p>\n

showsp = T,sppos = “left”,splab = paste0(“K=”,1:11),splabangle = 180,<\/p>\n

showlegend = F,ordergrp = T,grplab = pop, #\u6dfb\u52a0\u5206\u7ec4<\/p>\n

subsetgrp = LETTERS[1:9], #\u6dfb\u52a0\u7ec4\u540d<\/p>\n

dpi = 600,<\/p>\n

outputfilename = paste0(“structure_barplot_pop1”),units = “cm”,<\/p>\n

exportpath = getwd())<\/p>\n

<\/p>\n

#\u6b64\u65f6\u5df2\u7ecf\u53ef\u4ee5\u5728\u7ed3\u6784\u56fe\u4e0b\u9762\u770b\u5230\u5206\u7ec4\u4fe1\u606f<\/p>\n

#\u6700\u540e\u63a8\u65ad\u6700\u4f18\u7684\u5206\u7fa4\u6570\u76ee<\/p>\n

#\u5229\u7528k\u503c\u53cadeltaK\u9753\u5217\u6570\u786e\u5b9a\u6700\u4f18k\u503c\uff0cdeltaK\u6700\u5927\u7684\u6700\u4f18<\/p>\n

dt <- evannoMethodStructure(summariseQ(tabulateQ(slist,writetable = F,sorttable = T)),writetable = T,exportpath = getwd())<\/p>\n

<\/p>\n

#\u5199\u51fa\u6700\u4f18Q\u77e9\u9635,\u7b2c6\u4e2a\u662f\u6700\u4f18\u7684<\/p>\n

write.table(x = xlist2[[6]],file =’best_k6_Qscore’,quote = F,sep = ‘\\t’)<\/p>\n

\u90a3\u65e2\u7136\u5927\u5bb6\u5df2\u7ecf\u770b\u5230\u4e86\u8fd9\u91cc\uff0c\u76f8\u4fe1\u4f60\u4eec\u4e5f\u662f\u5b8c\u7f8e\u7684\u8fdb\u884c\u4e86\u590d\u73b0\uff0c\u90a3\u54b1\u4eec\u73b0\u5728\u5c31\u5bf9\u7ed3\u679c\u56fe\u8fdb\u884c\u8be6\u7ec6\u7684\u89e3\u91ca\u5427\uff01<\/p>\n

\u54b1\u4eec\u628a\u5e26\u6709\u5206\u7ec4\u4fe1\u606f\u7684P2\u5f53\u505a\u6700\u540e\u7684\u7ed3\u679c\u56fe\uff0c\u4ece\u4e0b\u5f80\u4e0a\u770b\u5462\uff0c\u9996\u5148\u53ef\u4ee5\u770b\u5230A-I\u76849\u4e2a\u5206\u7ec4\uff0c\u800c\u5728\u8fd99\u4e2a\u5206\u7ec4\u7684\u8303\u56f4\u4e4b\u5185\u5747\u6709\u4ee5R\u5f00\u5934\u7684\u83cc\u682a\u5b58\u5728\uff0c\u5176\u5b9e\u8fd9\u662f\u5c0f\u679c\u81ea\u5df1\u5bf9\u6837\u54c1\u8fdb\u884c\u7684\u5206\u7ec4\u54e6\uff0c\u5927\u5bb6\u5982\u679c\u60f3\u8981\u6539\u53d8\u7684\u8bdd\u4e5f\u662f\u53ef\u4ee5\u7684\u554a\u3002\u8fd9\u4e2a\u5206\u7ec4\u53ef\u4ee5\u6839\u636e\u5927\u5bb6\u7684\u5b9e\u9a8c\u6765\u51b3\u5b9a\u54e6\uff0c\u6bd4\u5982\u4e0d\u540c\u7684\u91c7\u6837\u65f6\u95f4\u3001\u4e0d\u540c\u7684\u91c7\u6837\u5730\u70b9\u6216\u540c\u4e00\u5c5e\u7684\u4e0d\u540c\u79cd\u6837\u54c1\u90fd\u662f\u53ef\u4ee5\u7684\u3002<\/p>\n

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