{"id":23675,"date":"2024-01-08T17:22:02","date_gmt":"2024-01-08T09:22:02","guid":{"rendered":"http:\/\/www.biocloudservice.com\/wordpress\/?p=23675"},"modified":"2024-01-08T17:22:03","modified_gmt":"2024-01-08T09:22:03","slug":"%e8%8a%b1%e4%b8%89%e5%88%86%e9%92%9f%ef%bc%8c%e8%ae%a9%e4%bd%a0%e5%af%b9xpclr%e4%ba%86%e5%a6%82%e6%8c%87%e6%8e%8c","status":"publish","type":"post","link":"http:\/\/www.biocloudservice.com\/wordpress\/?p=23675","title":{"rendered":"\u82b1\u4e09\u5206\u949f\uff0c\u8ba9\u4f60\u5bf9XPCLR\u4e86\u5982\u6307\u638c"},"content":{"rendered":"

\u5f88\u591a\u540c\u5b66\u505a\u5230\u68c0\u6d4b\u57fa\u56e0\u7ec4\u9009\u62e9\u4fe1\u53f7\u7684\u65f6\u5019\uff0c\u901a\u8fc7\u770b\u6587\u732e\u77e5\u9053\u4e86\u7528xpclr\u6700\u65b9\u4fbf\uff0c\u4f46\u662f\u5f88\u591a\u4eba\u5374\u88ab\u5b83\u7684\u5b89\u88c5\u6240\u6298\u670d\uff0c\u56e0\u4e3a\u5b9e\u5728\u662f\u592a\u591aerror\u548cwarning\u4e86\uff0c\u4e0d\u7528\u62c5\u5fc3\uff0c\u4eca\u5929\u5c0f\u679c\u5e26\u4f60\u5b8c\u6574\u7684\u8d70\u4e00\u904d\u5b83\u7684\u5b89\u88c5\u4e0e\u4f7f\u7528\u5427<\/p>\n

<\/a>xpclr<\/h2>\n

<\/a> \u5b98\u65b9\u6587\u6863\uff1ahttps:\/\/github.com\/hardingnj\/xpclr<\/a><\/p>\n

<\/a>XPCLR\u7684\u5b9a\u4e49<\/h3>\n

<\/a> XPCLR\uff08Cross-Population Longitudinal Test for the Composite of Multiple Rare Variants\uff09\u662f\u4e00\u79cd\u5e7f\u6cdb\u5e94\u7528\u4e8e\u4eba\u53e3\u9057\u4f20\u5b66\u7814\u7a76\u4e2d\u7684\u7edf\u8ba1\u65b9\u6cd5\u3002\u5b83\u57fa\u4e8e\u5047\u8bbe\u4eba\u7c7b\u57fa\u56e0\u7ec4\u4e0a\u7684\u5dee\u5f02\u53ef\u80fd\u662f\u901a\u8fc7\u9009\u62e9\u6216\u6f02\u79fb\u8fdb\u5316\u8fc7\u7a0b\u9020\u6210\u7684\uff0c\u7528\u4e8e\u68c0\u6d4b\u4e0d\u540c\u4eba\u7fa4\u4e4b\u95f4\u7684\u57fa\u56e0\u7ec4\u533a\u57df\u4e2d\u7684\u9009\u62e9\u4fe1\u53f7\u3002\u8fd9\u79cd\u65b9\u6cd5\u53ef\u4ee5\u63ed\u793a\u4e0d\u540c\u65cf\u7fa4\u4e4b\u95f4\u7684\u9057\u4f20\u53d8\u5f02\uff0c\u4e5f\u53ef\u4ee5\u63ed\u793a\u75be\u75c5\u548c\u5065\u5eb7\u56e0\u7d20\u7684\u5206\u5b50\u57fa\u7840\u3002<\/p>\n

<\/a> XPCLR\u65b9\u6cd5\u7684\u4f18\u52bf\u5728\u4e8e\u5176\u7cbe\u5ea6\u548c\u9ad8\u6548\u6027\uff0c\u5c24\u5176\u9002\u7528\u4e8e\u8bc6\u522b\u5927\u89c4\u6a21\u57fa\u56e0\u7ec4\u6570\u636e\u4e2d\u7fa4\u4f53\u95f4\u7684\u9009\u62e9\u5dee\u5f02\u3002\u5177\u4f53\u6765\u8bf4\uff0c\u8be5\u65b9\u6cd5\u662f\u57fa\u4e8e\u90a3\u4e9b\u5728\u7279\u5b9a\u4eba\u7fa4\u4e2d\u9891\u7387\u6781\u4f4e\u7684\u7f55\u89c1\u53d8\u5f02\uff08\u65e0\u91cd\u590d\u7684\u53d8\u5f02\uff09\u8fdb\u884c\u68c0\u6d4b\u7684\u3002\u901a\u8fc7\u8fd9\u79cd\u65b9\u5f0f\uff0cXPCLR\u80fd\u591f\u5feb\u901f\u800c\u51c6\u786e\u5730\u5206\u6790\u57fa\u56e0\u7ec4\u5750\u6807\u5bf9\u6570\u636e\uff0c\u68c0\u6d4b\u51fa\u662f\u5426\u5b58\u5728\u7fa4\u4f53\u95f4\u9009\u62e9\u7684\u4fe1\u53f7\uff0c\u8fdb\u800c\u63a8\u65ad\u8be5\u57fa\u56e0\u7ec4\u533a\u57df\u53ef\u80fd\u5b58\u5728\u7684\u8fdb\u5316\u5386\u53f2\u548c\u9002\u5e94\u6027\u3002<\/p>\n

<\/a>XPCLR\u7684\u5f00\u53d1<\/h3>\n

<\/a> \u4e0a\u9762\u4ecb\u7ecd\u4e86\uff0cXPCLR\u662f\u4e00\u79cd\u7528\u4e8e\u4f30\u8ba1\u5b8c\u5168\u548c\u90e8\u5206\u9009\u62e9\u4fe1\u53f7\u7684\u7edf\u8ba1\u65b9\u6cd5\u3002\u5b83\u4f7f\u7528\u9690\u85cf\u9a6c\u5c14\u53ef\u592b\u6a21\u578b\u548c\u975e\u53c2\u6570\u56de\u5f52\u6765\u8ba1\u7b97\u4ece\u6574\u4e2a\u57fa\u56e0\u7ec4\u4e2d\u68c0\u6d4b\u5230\u7684\u7a97\u53e3\u4e2d\u7684\u9009\u62e9\u5f3a\u5ea6\u3002XPCLR\u53ef\u4ee5\u5728\u5355\u4e00\u6837\u672c\u548c\u4eb2\u4ee3\u95f4\u6570\u636e\u4e2d\u4f7f\u7528\uff0c\u5e76\u4e14\u4e0eHapMap\u6570\u636e\u517c\u5bb9\u3002<\/p>\n

<\/a> \u68c0\u6d4b\u57fa\u56e0\u7ec4\u9009\u62e9\u4fe1\u53f7\u7684\u65b9\u6cd5\u6709\u5f88\u591a\u79cd\uff0c\u5176\u4e2d XP-CLR \u65b9\u6cd5\u662f\u5e38\u7528\u7684\u4e00\u79cd\u3002XP-CLR \u662f\u9648\u534e\u8001\u5e08\u3001Nick Patterson \u548c David Reich \u5728 2010 \u5e74\u53d1\u8868\u7684\u65b9\u6cd5\uff0c\u5168\u79f0\u53eb the cross-population composite likelihood ratio test\uff08\u8de8\u7fa4\u4f53\u590d\u5408\u4f3c\u7136\u6bd4\u68c0\u9a8c\uff09\uff0c\u662f\u4e00\u79cd\u662f\u57fa\u4e8e\u9009\u62e9\u626b\u8361\uff08selective sweeep\uff09\u7684\u4f3c\u7136\u65b9\u6cd5\u3002\u9009\u62e9\u626b\u8361\u53ef\u4ee5\u589e\u52a0\u7fa4\u4f53\u4e4b\u95f4\u7684\u9057\u4f20\u5206\u5316\uff0c\u5bfc\u81f4\u7b49\u4f4d\u57fa\u56e0\u9891\u7387\u504f\u79bb\u4e2d\u6027\u6761\u4ef6\u4e0b\u7684\u9884\u671f\u503c\u3002XP-CLR \u5229\u7528\u4e86\u4e24\u4e2a\u7fa4\u4f53\u4e4b\u95f4\u7684\u591a\u57fa\u56e0\u5ea7\u7b49\u4f4d\u57fa\u56e0\u9891\u7387\u5dee\u5f02\uff08multilocus allele frequency differentiation\uff09\u5efa\u7acb\u6a21\u578b\uff0c\u4f7f\u7528\u5e03\u6717\u8fd0\u52a8\u6765\u6a21\u62df\u4e2d\u6027\u4e0b\u7684\u9057\u4f20\u6f02\u79fb\uff0c\u5e76\u4f7f\u7528\u786e\u5b9a\u6027\u6a21\u578b\u6765\u8fd1\u4f3c\u5730\u5bf9\u9644\u8fd1\u7684\u5355\u6838\u82f7\u9178\u591a\u6001\u6027\uff08SNPs\uff09\u8fdb\u884c\u9009\u62e9\u6027\u626b\u63cf\u3002<\/p>\n

<\/a> XPCLR\u662f\u4ee5Python\u7f16\u5199\u7684\u5f00\u6e90\u8f6f\u4ef6\u3002\u4f60\u53ef\u4ee5\u4ece\u4ee5\u4e0bGitHub\u94fe\u63a5\u4e0b\u8f7d\uff1a<\/p>\n

https:\/\/github.com\/hardingnj\/xpclr<\/a><\/p>\n

<\/a>XPCLR\u7684\u5b89\u88c5<\/h3>\n

<\/a>1\u3001git\u5b89\u88c5<\/h4>\n

<\/a> ## lone this git repository into your working directory and cd.
\n## \u514b\u9686\u4e0b\u6765xpclr
\ngit clone https:\/\/github.com\/hardingnj\/xpclr.git
\n## \u4f7f\u7528python\u811a\u672c\u5b89\u88c5
\npython setup.py install<\/p>\n

<\/a> \u4e0b\u8f7d\u8be6\u7ec6\u8bf4\u660e\uff1a<\/p>\n

<\/a> \u5728\u4e0b\u8f7d\u540e\uff0c\u4f60\u53ef\u4ee5\u6309\u7167\u5176\u4e2d\u7684\u8bf4\u660e\u8fdb\u884c\u5b89\u88c5\u548c\u4f7f\u7528\u3002XPCLR\u7684\u4f7f\u7528\u65b9\u6cd5\u6bd4\u8f83\u590d\u6742\uff0c\u9700\u8981\u8f93\u5165\u4e00\u4e9b\u53c2\u6570\u4ee5\u6307\u5b9a\u8ba1\u7b97\u8fc7\u7a0b\u7684\u5404\u4e2a\u65b9\u9762\u3002\u56e0\u6b64\uff0c\u6211\u4eec\u5efa\u8bae\u4f60\u5728\u4f7f\u7528\u524d\u4ed4\u7ec6\u9605\u8bfb\u5176\u6587\u6863\u548c\u8bf4\u660e\u3002<\/p>\n

<\/a>2\u3001conda\u5b89\u88c5<\/h4>\n

<\/a> \u53e6\u5916\uff0c\u5982\u679c\u4f60\u4f7f\u7528Anaconda\u6216Miniconda\u7ba1\u7406Python\u8f6f\u4ef6\u5305\uff08\u63a8\u8350\u4f7f\u7528\uff09\u4f60\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u5728conda\u73af\u5883\u4e2d\u5b89\u88c5XPCLR\uff1a<\/p>\n

<\/a> ## Also available via conda via the bioconda channel:
\n## \u5148\u521b\u5efa\u4e00\u4e2a\u865a\u62df\u73af\u5883\uff0c\u4ee5\u9632\u4e07\u4e00\uff0c\u65b9\u4fbf\u8bd5\u9519
\nconda create -n xpclr python=3
\n## \u4f7f\u7528conda\u5b89\u88c5xpclr\uff0c\u7701\u5fc3\u7701\u529b
\nconda install -c bioconda xpclr<\/p>\n

<\/a>3\u3001\u7f16\u8bd1\u5b89\u88c5<\/h4>\n

<\/a> \u6b64\u5904\u4e0b\u8f7dhttps:\/\/reich.hms.harvard.edu\/software<\/a><\/p>\n

<\/a> wget https:\/\/reich.hms.harvard.edu\/sites\/reich.hms.harvard.edu\/files\/inline-files\/XPCLR.tar
\ntar XPCLR.tar<\/p>\n

<\/a> \u5728bin\u76ee\u5f55\u4e0b\u6709\u6267\u884c\u7a0b\u5e8f\uff0c\u4ee5\u53ca3\u4e2a\u793a\u4f8b\u6587\u4ef6<\/p>\n

<\/a> \u5982\u679c XPCLR \u65e0\u6cd5\u5728\u4f60\u7684\u7cfb\u7edf\u4e2d\u8fd0\u884c\uff0c\u5219\u9700\u8981\u81ea\u5df1\u7528 src \u7684\u6e90\u7801\u7f16\u8bd1\uff1a<\/p>\n

<\/a> cd src
\nmake
\nmake install<\/p>\n

<\/a>\u5e38\u89c1\u62a5\u9519<\/h3>\n

<\/a>python\u53c2\u6570\u683c\u5f0f<\/h4>\n

<\/a> No permission to write in the specified directory: {0}”.format(outdir<\/p>\n

<\/a> \u89e3\u51b3\u529e\u6cd5\uff1a\u627e\u5230\u5bf9\u5e94xpclr\u6587\u4ef6\uff0c\u52a0\u5165<\/p>\n

<\/a> fn = args.out
\nfn = os.path.abspath(args.out)
\noutdir = os.path.dirname(fn)<\/p>\n

<\/a>python\u7248\u672c\u62a5\u9519\uff1a<\/h4>\n

<\/a> \u5982\u679c\u7528\u6237\u7684\u673a\u5b50\u4e4b\u524d\u88c5\u7684python\u7248\u672c\u662f2.X\u7248\u672c\uff0c\u53ef\u80fd\u4f1a\u62a5\u51fd\u6570\u9519\u8bef<\/p>\n

<\/a> \u89e3\u51b3\u529e\u6cd5\uff1a<\/p>\n

<\/a> # \u7528conda\u521b\u5efa\u865a\u62df\u73af\u5883
\nconda create -n xpclr python=3
\nconda activate xpclr<\/p>\n

<\/a>numpy\u6216\u8005panda\u62a5\u9519<\/h4>\n

<\/a> \u91cd\u65b0\u7528pip\u5b89\u88c5\u5373\u53ef<\/p>\n

<\/a> pip install numpy
\npip install panda<\/p>\n

<\/a> git\u514b\u9686\u62a5\u9519<\/p>\n

<\/a>Git Clone\u9519\u8bef\uff1a<\/h4>\n

<\/a> GnuTLS recv error (-110): The TLS connection was non-properly terminated.<\/p>\n

<\/a> \u89e3\u51b3\u65b9\u6cd5\uff1a<\/p>\n

<\/a> ubuntu\u7cfb\u7edf\u590d\u5236\u4ee3\u7801\u5373\u53ef\uff0ccentos\u7cfb\u7edf\u628aapt-get install\u6362\u6210yum install\u5373\u53ef<\/p>\n

<\/a> apt-get install gnutls-bin
\ngit config –global http.sslVerify false
\ngit config –global http.postBuffer 1048576000<\/p>\n

<\/a>XPCLR\u7684\u53c2\u6570\u4ecb\u7ecd<\/h3>\n

<\/a> \u65e2\u7136XPCLR\u662f\u4e00\u79cd\u8ba1\u7b97\u9057\u4f20\u53d8\u5f02\u7279\u5f81\u7684\u7edf\u8ba1\u65b9\u6cd5\uff0c\u90a3\u4e48\u5728\u4f7f\u7528\u65f6\u53ef\u4ee5\u8bbe\u7f6e\u8bb8\u591a\u4e0d\u540c\u7684\u53c2\u6570\u4ee5\u6307\u5b9a\u8ba1\u7b97\u8fc7\u7a0b\u7684\u4e00\u4e9b\u7ec6\u8282\u3002<\/p>\n

<\/a> usage:<\/p>\n

<\/a> \u8be5\u8f6f\u4ef6\u53ef\u63a5\u53d7\u8f93\u5165\u683c\u5f0f\u4e3a:(1) hdf5\uff0c\u901a\u8fc7scikit-allel<\/a> \u5c06vcf\u8f6c\u6362\u6210\u8be5\u683c\u5f0f\uff0c(2) vcf\u683c\u5f0f(3) \u6216\u8005\u50cf\u4e4b\u524dxpclr\u4e2d\u76843\u79cd\u7c7b\u578b\u683c\u5f0f\u5177\u4f53\u53ef\u4ee5\u770bhttps:\/\/github.com\/hardingnj\/xpclr<\/a>\u4e2d\u7684xpclr-master\/fixture\/\u4e0b\u7684\u793a\u4f8b\u6587\u4ef6<\/p>\n

<\/a> usage: xpclr [-h] –out OUT [–format FORMAT] [–input INPUT]
\n[–gdistkey GDISTKEY] [–samplesA SAMPLESA] [–samplesB SAMPLESB]
\n[–rrate RRATE] [–map MAP] [–popA POPA] [–popB POPB] –chr
\nCHROM [–ld LDCUTOFF] [–phased] [–verbose VERBOSE]
\n[–maxsnps MAXSNPS] [–minsnps MINSNPS] [–size SIZE]
\n[–start START] [–stop STOP] [–step STEP]<\/p>\n

<\/a> \u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u7528\u7684XPCLR\u53c2\u6570\u53ca\u5176\u542b\u4e49\uff1a<\/p>\n