– \u6982\u8ff0<\/p>\n
– 16S\u6d4b\u5e8f\u5b9e\u9a8c\u6d41\u7a0b<\/p>\n
– 16S\u5206\u6790\u6d41\u7a0b<\/p>\n
– \u7ed3\u679c\u600e\u4e48\u770b<\/p>\n
– \u5e38\u89c1\u95ee\u9898<\/p>\n
– \u53c2\u8003\u6587\u732e<\/p>\n
\u4f60\u77e5\u9053\u5417\uff1f\u5c45\u4f4f\u5728\u6211\u4eec\u80a0\u9053\u5185\u7684\u7ec6\u83cc\u6570\u91cf\uff0c\u662f\u4eba\u4f53\u7ec6\u80de\u603b\u6570\u768410\u500d\u4e4b\u591a\uff01\u6211\u4eec\u6bcf\u5929\u6392\u51fa\u7684\u7caa\u4fbf\u4e2d\uff0c50%\u4ee5\u4e0a\u7684\u5e72\u91cd\u91cf\u662f\u7531\u8fd9\u4e9b\u7ec6\u83cc\u53ca\u5176\u201c\u5c38\u4f53\u201d\u6784\u6210\u7684\u3002\u56e0\u6b64\u6709\u4eba\u6253\u8da3\u7684\u8bf4\uff0c\u4ece\u6570\u91cf\u4e0a\u6765\u770b\uff0c\u6211\u4eec\u4eba\u7c7b\u5e76\u4e0d\u5e94\u8be5\u88ab\u79f0\u4e3a\u4eba\u7c7b\uff0c\u800c\u5e94\u88ab\u79f0\u4f5c\u7ec6\u83cc\u3002\u5982\u6b64\u5e9e\u5927\u7684\u7ec6\u83cc\u7fa4\u4f53\u9a7b\u624e\u5728\u80a0\u9053\u5185\uff0c\u6784\u6210\u4e86\u4e00\u4e2a\u6781\u4e3a\u590d\u6742\u7684\u7fa4\u4f53\uff0c\u88ab\u79f0\u4f5c\u80a0\u9053\u83cc\u7fa4\u3002\u80a0\u9053\u83cc\u7fa4\u88ab\u8ba4\u4e3a\u4e0e\u4eba\u7c7b\u5065\u5eb7\u606f\u606f\u76f8\u5173\uff0c\u636e\u4f30\u8ba1\uff0c\u6bcf\u4e2a\u4eba\u7684\u80a0\u9053\u83cc\u7fa4\u53ef\u5305\u62ec\uff5e500\u79cd\u7ec6\u83cc\u3002<\/p>\n<\/p>\n
\u90a3\u4e48\uff0c\u5982\u4f55\u9274\u522b\u80a0\u9053\u83cc\u7fa4\u7684\u79cd\u7c7b\u548c\u4e30\u5ea6\u5462\uff1f\u5b9e\u9a8c\u5ba4\u5e38\u7528\u7684\u7814\u7a76\u65b9\u6cd5\u4e3b\u8981\u6709\u54ea\u4e9b\u5462\uff1f<\/p>\n
\u5e38\u89c4\u7684\u57fa\u4e8e\u5206\u79bb\u57f9\u517b\u7684\u65b9\u6cd5\uff0c\u8be5\u65b9\u6cd5\u8f83\u4e3a\u6210\u719f\uff0c\u4f9d\u7136\u88ab\u8bb8\u591a\u80a0\u9053\u83cc\u7fa4\u7684\u7814\u7a76\u8005\u91c7\u7528\uff0c\u4f46\u662f\u80a0\u9053\u83cc\u7fa4\u5927\u591a\u4e0d\u80fd\u57f9\u517b\u4e14\u6bd4\u8f83\u8017\u65f6\u8017\u529b\uff0c\u65e0\u6cd5\u5168\u9762\u7684\u5206\u6790\u5bf9\u4e8e\u79cd\u7c7b\u548c\u6570\u91cf\u5de8\u5927\u7684\u80a0\u9053\u5fae\u751f\u6001\u7cfb\u7edf\uff1b<\/p>\n<\/li>\n
\u8d28\u8c31\u6280\u672f\uff0c\u57fa\u4e8e\u5bf9\u83cc\u4f53\u86cb\u767d\u8d28\u5206\u6790\u7684\u8d28\u8c31\u6280\u672f\u5177\u6709\u5728\u590d\u6742\u4f53\u7cfb\u4e2d\u540c\u65f6\u533a\u5206\u4e0d\u540c\u86cb\u767d\u7ec4\u5206\u7684\u7279\u70b9\uff0c\u4e3a\u80a0\u9053\u83cc\u7fa4\u7684\u5feb\u901f\u3001\u51c6\u786e\u3001\u9ad8\u901a\u91cf\u7684\u9274\u522b\u63d0\u4f9b\u4e86\u53ef\u9760\u65b9\u6cd5\uff1b<\/p>\n<\/li>\n
\u5bf9\u4e8e\u4e0d\u5bb9\u6613\u5206\u79bb\u57f9\u517b\u7684\u5fae\u751f\u7269\uff0c\u57fa\u56e0\u68c0\u6d4b\u66f4\u663e\u4f18\u52bf\uff0c\u5e38\u7528\u7684\u6709\u57fa\u4e8e\u5206\u5b50\u6742\u4ea4\u6280\u672f\u7684\u5206\u6790\u65b9\u6cd5\u3001\u57fa\u4e8e DNA \u6307\u7eb9\u56fe\u8c31\u7684\u5206\u6790\u65b9\u6cd5\u3001\u57fa\u4e8e DNA \u6d4b\u5e8f\u7684\u68c0\u6d4b\u65b9\u6cd5\u7b49\u3002<\/p>\n<\/li>\n<\/ul>\n
\u8fd1\u5e74\u6765\uff0c\u968f\u7740\u9ad8\u901a\u91cf\u6d4b\u5e8f\u6280\u672f\u7684\u53d1\u5c55\uff0c16S rRNA\u57fa\u56e0\u6d4b\u5e8f\u6280\u672f\u5728\u7ec6\u83cc\u7684\u9274\u5b9a\u4e0e\u5206\u7c7b\u7814\u7a76\u4e2d\u53d1\u6325\u7740\u8d8a\u6765\u8d8a\u91cd\u8981\u7684\u4f5c\u7528\u3002<\/p>\n<\/p>\n
16S rRNA\u57fa\u56e0\u666e\u904d\u5b58\u5728\u4e8e\u7ec6\u83cc\u7ec6\u80de\uff0c\u5728\u7ec6\u83cc\u57fa\u56e0\u7ec4\u4e2d\u4f4d\u4e8e\u6838\u7cd6\u4f53\u5c0f\u4e9a\u57fa\uff08\u7ea61540 bp\uff09\uff0c\u8be5\u533a\u57df\u517c\u987e\u4fdd\u5b88\u6027\u548c\u9ad8\u53d8\u6027\uff0c\u542b\u670910 \u4e2a\u4fdd\u5b88\u533a\u57df(Conserved Regions)\u548c 9 \u4e2a\u9ad8\u53d8\u533a\u57df(variable Regions)\uff0c\u4fdd\u5b88\u533a\u53ef\u7528\u4e8e\u8bbe\u8ba1\u5f15\u7269\u8fdb\u884c\u76ee\u7684\u7247\u6bb5\u7684\u6269\u589e\uff0c\u800c\u901a\u8fc7\u5bf9\u9ad8\u53d8\u533a\u7684\u5206\u6790\u53ef\u4ee5\u8fa8\u522b\u7ec6\u83cc\u79cd\u7c7b\u3002\u56e0\u6b64\uff0c16S rRNA\u57fa\u56e0\u88ab\u8ba4\u4e3a\u662f\u6700\u9002\u4e8e\u7ec6\u83cc\u7cfb\u7edf\u53d1\u80b2\u5b66\u7814\u7a76\u548c\u7269\u79cd\u5206\u7c7b\u9274\u5b9a\u3002\u76ee\u524d\u7528\u4e8e16S rRNA\u57fa\u56e0\u6df1\u5ea6\u6d4b\u5e8f\u7684\u533a\u57df\u4e3b\u8981\u6709V4\u533a\uff0cV3-V4\u533a\u3001\u548cV4-V5\u533a\u7b49\u3002<\/p>\n
\u5c06\u68c0\u6d4b\u5408\u683c\u7684\u73af\u5883\u5fae\u751f\u7269DNA\u6837\u672c\u5bf9\u5176\u6307\u5b9a\u533a\u57df\u8fdb\u884cPCR\u6269\u589e\u3001\u6587\u5e93\u5236\u5907\u3001\u6587\u5e93\u8d28\u68c0\u3001\u5b9a\u91cf\uff0c\u4f7f\u7528\u8bbe\u5b9a\u7684TAG\u5e8f\u5217\u8fdb\u884c\u6837\u672c\u533a\u5206\u3002\u91c7\u7528Illumina Hiseq 2500\u9ad8\u901a\u91cf\u6d4b\u5e8f\u5e73\u53f0\u5bf9\u68c0\u6d4b\u5408\u683c\u7684\u6587\u5e93\u8fdb\u884c\u6d4b\u5e8f\u3002\u5b9e\u9a8c\u6d41\u7a0b\u5982\u4e0b\u56fe\u6240\u793a\uff1a<\/p>\n<\/p>\n
16S\u5206\u6790\u6d41\u7a0b\u4e3b\u8981\u5305\u62ec\uff1aHiseq\/Miseq\u6d4b\u5e8f\u83b7\u5f97\u7684Paired-end (PE) reads\u62fc\u63a5\u6210\u4e00\u6761\u5e8f\u5217\uff0c\u5bf9\u76ee\u6807\u5e8f\u5217\u8fdb\u884c\u8d28\u63a7\u8fc7\u6ee4\uff0c\u8fc7\u6ee4\u540e\u7684\u5e8f\u5217\u4e0e\u53c2\u8003\u6570\u636e\u5e93\u4f5c\u6bd4\u5bf9\uff0c\u53bb\u9664\u5d4c\u5408\u4f53\u5e8f\u5217\u5f97\u5230\u6700\u7ec8\u5f97\u4f18\u5316\u5e8f\u5217\u3002\u57fa\u4e8e\u4f18\u5316\u5e8f\u5217\u8fdb\u884cOTU\u805a\u7c7b\u5206\u6790\u548c\u7269\u79cd\u5206\u7c7b\u6ce8\u91ca\uff0c\u57fa\u4e8eOTU\u805a\u7c7b\u7ed3\u679c\u8fdb\u884c\u591a\u6837\u6027\u6307\u6570\u5206\u6790\uff0c\u57fa\u4e8e\u5206\u7c7b\u5b66\u4fe1\u606f\u8fdb\u884c\u7269\u79cd\u7ed3\u6784\u5206\u6790\u548c\u7269\u79cd\u5dee\u5f02\u5206\u6790\u3002<\/p>\n<\/p>\n
\u6839\u636eFastq\u6587\u4ef6\u5bf9\u6d4b\u5e8f\u6837\u54c1\u8fdb\u884c\u6570\u636e\u8d28\u91cf\u8bc4\u4f30\uff08\u53ef\u4ee5\u53c2\u8003\u751f\u4fe1\u5165\u95e8\uff1aFasta\u4e0eFastq\u683c\u5f0f\u6587\u4ef6\u8be6\u89e3\u8be6\u7ec6\u4e86\u89e3fastq\u6587\u4ef6\uff09\u3002\u5355\u4e2a\u6837\u54c1\u7684\u78b1\u57fa\u8d28\u91cf\u5206\u5e03\u5982\u4e0b\u56fe\u6240\u793a\uff1a<\/p>\n
\u6ce8\uff1a\u6a2a\u5750\u6807\u4e3areads\u7684\u78b1\u57fa\u4f4d\u7f6e\uff0c\u7eb5\u5750\u6807\u4e3a\u5355\u78b1\u57fa\u5e73\u5747Phred\u503c\u3002\u524d250bp \u4e3a\u53cc\u7aef\u6d4b\u5e8f\u5e8f\u5217\u7684Read1\u7684\u78b1\u57fa\u8d28\u91cf\u503c\u5206\u5e03\u60c5\u51b5\uff0c\u540e250bp\u4e3aread2 \u7684\u78b1\u57fa\u8d28\u91cf\u503c\u5206\u5e03\u60c5\u51b5\u3002<\/p>\n
\u4e5f\u53ef\u4ee5\u4f7f\u7528\u4e00\u6587\u641e\u5b9a\u7ec6\u83cc\u57fa\u56e0\u7ec4De Novo\u6d4b\u5e8f\u5206\u6790\u4e2d\u63d0\u5230\u7684fastqc\u548cfastp\u8fdb\u884c\u8d28\u63a7\u3002<\/p>\n
\u5982\u679c\u60f3\u786e\u5b9a\u62ff\u5230\u624b\u91cc\u7684\u5e8f\u5217fastq\u5e8f\u5217\u5c31\u662f16S\u7684\u4e00\u90e8\u5206\uff0c\u800c\u4e0d\u662f\u5176\u4ed6\u7684\u795e\u9a6c\u9b3c\uff0c\u53ef\u4ee5\u5728NCBI\u7684blast\u4e0a\u6bd4\u4e00\u6bd4\uff08\u53ef\u53c2\u8003\u751f\u4fe1\u5165\u95e8\uff1a\u5e8f\u5217\u6bd4\u5bf9\u4e4bblast\u5728\u7ebf\u548c\u672c\u5730\u4f7f\u7528\uff09\u3002<\/p>\n
\u6839\u636ePE reads\u4e4b\u95f4\u7684overlap\u91c7\u7528Flash\u8f6f\u4ef6\u5bf9\u6570\u636e\u8fdb\u884c\u62fc\u63a5\u3002<\/p>\n
#\u6ce8\u610f\u53c2\u6570-M, –max-overlap=NUM \u7684\u8bbe\u7f6e\uff0c\u6839\u636e\u6d4b\u5e8f\u7b56\u7565\u548cPCR\u4ea7\u7269\u7684\u957f\u77ed\u51b3\u5b9a\u3002<\/p>\n<\/li>\n
flash -o extendedFrags test_1.fas tq test_2.fastq -M 180 -t 8<\/p>\n<\/li>\n
\u7531\u4e8e\u6d4b\u5e8f\u8fc7\u7a0b\u4e2d\u4f1a\u5f15\u5165\u9519\u8bef\u6216\u8005\u4e0d\u53ef\u9760\u78b1\u57fa\uff0c\u4e25\u91cd\u5f71\u54cd\u540e\u7eed\u5206\u6790\u7ed3\u679c\u51c6\u786e\u6027\u3002\u56e0\u6b64\uff0c\u91c7\u7528fastx-toolkit\u5de5\u5177\u8fc7\u6ee4\u6570\u636e\uff0c\u53ea\u4fdd\u7559\u9ad8\u8d28\u91cf\uff08Q\u503c>=25\uff09\u7684\u78b1\u57fa\u6bd4\u4f8b\u5927\u4e8e\u7b49\u4e8e90%\u7684reads\u3002<\/p>\n
fastq_quality_filter -h<\/p>\n<\/li>\n
usage: fastq_quality_filter [-h] [-v] [-q N] [-p N] [-z] [-i INFILE] [-o OUTFILE]<\/p>\n<\/li>\n
Part of FASTX Toolkit 0.0.13.2 by A. Gordon (gordon@cshl.edu)<\/p>\n<\/li>\n
[-h] = This helpful help screen.<\/p>\n<\/li>\n
[-q N] = Minimum quality score to keep.<\/p>\n<\/li>\n
[-p N] = Minimum percent of bases that must have [-q] quality.<\/p>\n<\/li>\n
[-z] = Compress output with GZIP.<\/p>\n<\/li>\n
[-i INFILE] = FASTA\/Q input file. default is STDIN.<\/p>\n<\/li>\n
[-o OUTFILE] = FASTA\/Q output file. default is STDOUT.<\/p>\n<\/li>\n
[-v] = Verbose – report number of sequences.<\/p>\n<\/li>\n
If [-o] is specified, report will be printed to STDOUT.<\/p>\n<\/li>\n
If [-o] is not specified (and output goes to STDOUT),<\/p>\n<\/li>\n
report will be printed to STDERR.<\/p>\n<\/li>\n
fastq_quality_filter -i extendedFrags.fastq -p 90 -q 25 -Q33<\/p>\n<\/li>\n
\u5d4c\u5408\u4f53\u5728\u9057\u4f20\u5b66\u4e0a\u7528\u4ee5\u6307\u4e0d\u540c\u9057\u4f20\u6027\u72b6\u5d4c\u5408\u6216\u6df7\u6742\u8868\u73b0\u7684\u4e2a\u4f53\u3002\u5d4c\u5408\u4f53\u5e8f\u5217\u7684\u51fa\u73b0\u4f1a\u5bfc\u81f4\u6d4b\u5e8f\u7ed3\u679c\u4e2d\u4ea7\u751f\u4e00\u4e9b\u5b9e\u9645\u5e76\u4e0d\u5b58\u5728\u7684\u6838\u9178\u5e8f\u5217\uff0c\u5f71\u54cd\u7ed3\u679c\u7684\u53ef\u9760\u6027\u3002<\/p>\n<\/p>\n
\u56e0\u6b64\uff0c\u53ef\u4ee5\u7528usearch 64-bit\u8f6f\u4ef6\u8fdb\u884c\u5d4c\u5408\u4f53\u5e8f\u5217\u7684\u68c0\u6d4b\u53ca\u8fc7\u6ee4\u3002<\/p>\n
usearch 64-bit\u662f\u6536\u8d39\u7684\uff0c\u4e3b\u8981\u4f18\u52bf\u662f\u652f\u6301\u5927\u5185\u5b58\u5904\u7406\u6d77\u91cf\u6570\u636e\uff0c\u5b83\u662f\u8d85\u5feb\u7684\u5e8f\u5217\u5206\u6790\u8f6f\u4ef6\uff0c\u5728\u5e8f\u5217\u6bd4\u5bf9\u3001\u805a\u7c7b\u3001\u64cd\u4f5c\u7b49\u591a\u9886\u57df\u5e7f\u6cdb\u5e94\u7528\u3002<\/p>\n
usearch8.0 -uchime_ref input.fasta -db gold.fasta -strand plus -nonchimeras good.fasta<\/p>\n<\/li>\n
# -db \u63a8\u8350\u7684\u6570\u636e\u4e3a’Gold’ database\uff08http:\/\/\/uchime\/uchime_download.html\uff09\uff0cITS\u7684\u6570\u636e\uff0c\u63a8\u8350\u4f7f\u7528UNITE\u6570\u636e\u5e93\u3002<\/p>\n<\/li>\n
OTU\uff08Operational Taxonomic Units\uff0c\u64cd\u4f5c\u5206\u7c7b\u5355\u5143\uff09\u662f\u5728\u7cfb\u7edf\u53d1\u751f\u5206\u6790\u6216\u7fa4\u4f53\u9057\u4f20\u7814\u7a76\u4e2d\u7684\u4e00\u4e2a\u5047\u5b9a\u7684\u5206\u7c7b\u5355\u5143\uff0c\u901a\u8fc7\u4e00\u5b9a\u7684\u8ddd\u79bb\u5ea6\u91cf\u65b9\u6cd5\u8ba1\u7b97\u4e24\u4e24\u4e0d\u540c\u5e8f\u5217\u4e4b\u95f4\u7684\u8ddd\u79bb\u5ea6\u91cf\u6216\u76f8\u4f3c\u6027\uff0c\u7ee7\u800c\u8bbe\u7f6e\u7279\u5b9a\u7684\u5206\u7c7b\u9608\u503c\uff0c\u83b7\u5f97\u540c\u4e00\u9608\u503c\u4e0b\u7684\u8ddd\u79bb\u77e9\u9635\uff0c\u8fdb\u884c\u805a\u7c7b\u64cd\u4f5c\uff0c\u5f62\u6210\u4e0d\u540c\u7684\u5206\u7c7b\u5355\u5143\u3002<\/p>\n
OTU\u805a\u7c7b\u7684\u76ee\u7684\uff1a<\/p>\n
1. \u6bcf\u4e2aOTU\uff0897%\uff09\u5728\u7ea7\u522b\u4e0a\u5bf9\u5e94\u4e00\u4e2a\u79cd\/\u5c5e\uff1b<\/p>\n
2. \u6bcf\u4e2aOTU\u6311\u9009\u51fa\u4e00\u4e2a\u4ee3\u8868\u5e8f\u5217\u53c2\u4e0e\u540e\u7eed\u5206\u6790\uff0c\u8282\u7ea6\u8ba1\u7b97\u8d44\u6e90\uff1b<\/p>\n
3. \u51cf\u5c11PCR\u6216\u6d4b\u5e8f\u8fc7\u7a0b\u4e2d\u5f15\u5165\u7684\u9519\u8bef\uff08\u9519\u8bef\u5e8f\u5217\u4e0e\u5176\u6765\u6e90\u5e8f\u5217\u8f83\u4e3a\u76f8\u4f3c\uff0c\u4f1a\u805a\u6210\u4e00\u4e2aOTU\uff09\u3002<\/p>\n
\u6839\u636e97%\u7684\u5e8f\u5217\u76f8\u4f3c\u6027\u6c34\u5e73\uff0c\u5229\u7528QIIME\u8f6f\u4ef6\u5305\u4e2d\u7684Uclust \u65b9\u6cd5\u8fdb\u884cOTU\u805a\u7c7b\u5206\u6790\u3002\u7136\u540e\u57fa\u4e8eSilva\uff08\u4f8b\u5982\uff1aRelease132 https:\/\/www.\/documentation\/release-132\uff09\u53c2\u8003\u6570\u636e\u5e93\uff0c\u5bf9\u6bcf\u4e2a\u6837\u54c1\u7684OTUs\u8fdb\u884c\u7269\u79cd\u5206\u7c7b\u5b66\uff08Taxonomy\uff09\u6ce8\u91ca\u3002<\/p>\n<\/p>\n
OTU\u805a\u7c7b\u90e8\u5206\u7ed3\u679c\u5982\u4e0b\u8868\u6240\u793a\uff1a<\/p>\n<\/p>\n
\u7edf\u8ba1\u6240\u6709\u6837\u672c\u5728\u95e8\u3001\u7eb2\u3001\u76ee\u3001\u79d1\u3001\u5c5e\u5404\u5c42\u6b21\u4e0a\u7684\u5206\u7c7b\u7ed3\u679c\u3002\u57fa\u4e8e\u4e30\u5ea6\u524d\u5341\u4e94\u7684\u7269\u79cd\u91c7\u7528\u7d2f\u79ef\u67f1\u72b6\u56fe\u6bd4\u8f83\u6837\u672c\u95f4\u7684\u7269\u79cd\u7ec4\u6210\u5dee\u5f02\uff0c\u5e76\u8fdb\u884c\u5217\u8868\u5c55\u793a\u3002\u5168\u6837\u672c\u5728\u95e8\u5c42\u6b21\u7684\u7fa4\u843d\u7ed3\u6784\u5206\u6790\u7ed3\u679c\u5982\u4e0b\u56fe\u6240\u793a\uff1a<\/p>\n<\/p>\n
\u57fa\u4e8e\u5c5e\u6c34\u5e73\u4e0a\u6bcf\u4e2a\u6837\u54c1\u7684\u7269\u79cd\u4e30\u5ea6\u4fe1\u606f\uff0c\u9009\u53d6\u4e30\u5ea6\u524d50\u7684\u5c5e\uff0c\u6839\u636e\u5404\u6837\u54c1\u7684\u4e30\u5ea6\u4fe1\u606f\u5bf9\u6837\u54c1\u548c\u7269\u79cd\u8fdb\u884c\u805a\u7c7b\uff0c\u7ed8\u5236\u70ed\u56fe\u3002\u4fbf\u4e8e\u89c2\u5bdf\u6837\u54c1\u5bf9\u5e94\u7269\u79cd\u542b\u91cf\u5f97\u9ad8\u4f4e\u3002\u7ed3\u679c\u5982\u4e0b\u56fe\u6240\u793a\uff1a<\/p>\n<\/p>\n
\u5229\u7528KRONA\u8f6f\u4ef6\u5bf9\u7269\u79cd\u6ce8\u91ca\u7ed3\u679c\u8fdb\u884c\u53ef\u89c6\u5316\u5c55\u793a\uff0c \u5706\u5708\u56fe\u5f97\u5404\u5c42\u4f9d\u6b21\u4ee3\u8868\u7269\u79cd\u5f97\u5206\u7c7b\u7ea7\u522b\uff0c\u6247\u5f62\u7684\u5927\u5c0f\u4ee3\u8868\u6ce8\u91ca\u7269\u79cd\u7684\u6bd4\u4f8b\u3002<\/p>\n<\/p>\n
Alpha\u591a\u6837\u6027\u662f\u6307\u4e00\u4e2a\u7279\u5b9a\u533a\u57df\u6216\u751f\u6001\u7cfb\u7edf\u5185\u7684\u591a\u6837\u6027\u3002\u591a\u6837\u6027\u6307\u6570\u662f\u53cd\u6620\u6837\u672c\u4e2d\u5fae\u751f\u7269\u4e30\u5bcc\u5ea6\u548c\u5747\u5300\u5ea6\u7684\u7efc\u5408\u6307\u6807\u3002<\/p>\n
Alpha\u591a\u6837\u6027\u5206\u6790\u4e3b\u8981\u5305\u62ecShannon\u591a\u6837\u6027\u6307\u6570\u3001Simpson\u6307\u6570\u3001Chao1\u4e30\u5bcc\u5ea6\u6307\u6570\u7b49\u591a\u6837\u6027\u6307\u6570\u7684\u8ba1\u7b97.<\/p>\n
\u91c7\u7528\u968f\u673a\u62bd\u6837\u7684\u65b9\u6cd5\uff0c\u4ece\u6837\u672c\u4e2d\u968f\u673a\u62bd\u53d6\u4e00\u5b9a\u6570\u91cf\u7684\u4e2a\u4f53\uff0c\u7edf\u8ba1\u51fa\u8fd9\u4e9b\u4e2a\u4f53\u6240\u4ee3\u8868\u7269\u79cd\u6570\u76ee\uff0c\u5e76\u4ee5\u4e2a\u4f53\u6570\u4e0e\u7269\u79cd\u6570\u6765\u6784\u5efa\u66f2\u7ebf\uff0c\u5373\u7a00\u91ca\u6027\u66f2\u7ebf\uff08rarefaction curve\uff09\u3002\u5b83\u53ef\u4ee5\u7528\u6765\u6bd4\u8f83\u6d4b\u5e8f\u6570\u91cf\u4e0d\u540c\u7684\u6837\u672c\u7269\u79cd\u7684\u4e30\u5bcc\u5ea6\uff0c\u4e5f\u53ef\u4ee5\u7528\u6765\u8bf4\u660e\u6837\u672c\u7684\u53d6\u6837\u5927\u5c0f\u662f\u5426\u5408\u7406\u3002<\/p>\n
\u7a00\u91ca\u66f2\u7ebf\u662f\u5229\u7528\u5df2\u6d4b\u5f9716S rRNA\u5e8f\u5217\u4e2d\u5df2\u77e5\u7684\u5404\u79cdOTU\u7684\u76f8\u5bf9\u6bd4\u4f8b\uff0c\u6765\u8ba1\u7b97\u62bd\u53d6n\u4e2a\uff08n\u5c0f\u4e8e\u6d4b\u5f97reads\u5e8f\u5217\u603b\u6570\uff09reads\u65f6\u51fa\u73b0OTU\u6570\u91cf\u7684\u671f\u671b\u503c\uff0c\u7136\u540e\u6839\u636e\u4e00\u7ec4n\u503c\uff08\u4e00\u822c\u4e3a\u4e00\u7ec4\u5c0f\u4e8e\u603b\u5e8f\u5217\u6570\u7684\u7b49\u5dee\u6570\u5217\uff09\u4e0e\u5176\u76f8\u5bf9\u5e94\u7684OTU\u6570\u91cf\u7684\u671f\u671b\u503c\uff08\u6b64\u5904\u91c7\u7528chao1\u7b97\u6cd5\u4f30\u8ba1\uff09\uff0c\u5f53\u66f2\u7ebf\u8d8b\u5411\u5e73\u5766\u65f6\uff0c\u8bf4\u660e\u6d4b\u5e8f\u6570\u636e\u91cf\u5408\u7406\uff0c\u66f4\u591a\u7684\u6570\u636e\u91cf\u53ea\u4f1a\u4ea7\u751f\u5c11\u91cf\u65b0\u7684OTU\uff0c\u53cd\u4e4b\u5219\u8868\u660e\u7ee7\u7eed\u6d4b\u5e8f\u8fd8\u53ef\u80fd\u4ea7\u751f\u8f83\u591a\u65b0\u7684OTU\u3002<\/p>\n
Chao1\uff1a\u7528chao1\u7b97\u6cd5\u4f30\u8ba1\u7fa4\u843d\u4e2d\u542bOTU\u6570\u76ee\u7684\u6307\u6570\uff0c\u5728\u751f\u6001\u5b66\u4e2d\u5e38\u7528\u6765\u4f30\u8ba1\u7269\u79cd\u603b\u6570\uff0c\u7531Chao\u57281984\u5e74\u6700\u65e9\u63d0\u51fa\u3002\u8ba1\u7b97\u516c\u5f0f\u5982\u4e0b\uff1a<\/p>\n<\/p>\n
\u5176\u4e2dchao1\u662f\u4f30\u8ba1\u7684OTU\u6570\uff1b\u662f\u5b9e\u9645\u89c2\u5bdf\u7684OTU\u6570\uff1bF1\u662f\u53ea\u6709\u4e00\u6761\u5e8f\u5217\u7684OTU\u6570\u76ee\uff08\u5982\u201csingletons\u201d\uff09\uff1bF2\u662f\u53ea\u6709\u4e24\u6761\u5e8f\u5217\u7684OTU\u6570\u76ee\uff08\u5982\u201cdoubletons\u201d\uff09\u3002\u7ed8\u5236\u5404\u6837\u672c\u7a00\u91ca\u66f2\u7ebf\u5982\u4e0b\u56fe\u6240\u793a\uff1a<\/p>\n<\/p>\n
\u7531\u56fe\u53ef\u77e5\uff0c\u5f53\u6d4b\u5e8f\u91cf\uff08\u6a2a\u5750\u6807\uff09\u589e\u52a0\u518d\u591a\uff0c\u5bf9OTU\u6570\uff08\u7eb5\u5750\u6807\uff09\u7684\u589e\u957f\u8d21\u732e\u4e0d\u5927\uff0c\u8bf4\u660e\u6d4b\u5e8f\u91cf\u5df2\u7ecf\u8db3\u591f\uff0c\u589e\u52a0\u6d4b\u5e8f\u91cf\u4e0d\u80fd\u63d0\u4f9b\u66f4\u591a\u7684\u65b0\u7684OTU\u3002<\/p>\n
Shannon-Wiener\u6307\u6570\u662f\u7531Shannon, C. E. and Weaver W\u57281948\u5e74\u63d0\u51fa\u3002\u53cd\u6620\u6837\u54c1\u4e2d\u5fae\u751f\u7269\u591a\u6837\u6027\u7684\u6307\u6570\uff0c\u5229\u7528\u5404\u6837\u54c1\u7684\u6d4b\u5e8f\u91cf\u5728\u4e0d\u540c\u6d4b\u5e8f\u6df1\u5ea6\u65f6\u7684\u5fae\u751f\u7269\u591a\u6837\u6027\u6307\u6570\u6784\u5efa\u66f2\u7ebf\uff0c\u4ee5\u6b64\u53cd\u6620\u5404\u6837\u672c\u5728\u4e0d\u540c\u6d4b\u5e8f\u6570\u91cf\u65f6\u7684\u5fae\u751f\u7269\u591a\u6837\u6027\u3002<\/p>\n
\u7ed8\u5236Shannon\u66f2\u7ebf\u5982\u4e0b\u56fe\u6240\u793a\uff1a<\/p>\n<\/p>\n
\u7269\u79cd\u7d2f\u79ef\u66f2\u7ebf( species accumulation curves) \u662f\u7528\u4e8e\u63cf\u8ff0\u968f\u7740\u6837\u54c1\u6570\u91cf\u7684\u52a0\u5927\u800c\u7269\u79cd\u589e\u52a0\u7684\u72b6\u51b5\uff0c\u662f\u8c03\u67e5\u6837\u54c1\u7684\u7269\u79cd\u7ec4\u6210\u548c\u9884\u6d4b\u6837\u54c1\u4e2d\u7269\u79cd\u4e30\u5ea6\u7684\u6709\u6548\u5de5\u5177\uff0c\u88ab\u5e7f\u6cdb\u7528\u4e8e\u6837\u54c1\u91cf\u662f\u5426\u5145\u5206\u7684\u5224\u65ad\u4ee5\u53ca\u7269\u79cd\u4e30\u5bcc\u5ea6( species richness) \u7684\u4f30\u8ba1\u3002\u56e0\u6b64\uff0c\u901a\u8fc7\u7269\u79cd\u7d2f\u79ef\u66f2\u7ebf\u4e0d\u4ec5\u53ef\u4ee5\u5224\u65ad\u6837\u54c1\u91cf\u662f\u5426\u5145\u5206\uff0c\u5728\u6837\u54c1\u91cf\u5145\u5206\u7684\u524d\u63d0\u4e0b\uff0c\u8fd0\u7528\u7269\u79cd\u7d2f\u79ef\u66f2\u7ebf\u8fd8\u53ef\u4ee5\u5bf9\u7269\u79cd\u4e30\u5bcc\u5ea6\u8fdb\u884c\u9884\u6d4b\uff08\u9ed8\u8ba4\u5728\u6837\u54c1\u91cf\u5927\u4e8e10\u4e2a\u5206\u6790\uff09\u3002<\/p>\n<\/p>\n
Beta Diversity\u662f\u5bf9\u4e0d\u540c\u6837\u672c\/\u4e0d\u540c\u7ec4\u95f4\u6837\u672c\u7684\u5fae\u751f\u7269\u7fa4\u843d\u6784\u6210\u8fdb\u884c\u6bd4\u8f83\u5206\u6790\u3002<\/p>\n
\u53ef\u4ee5\u7528OTUs\u7684\u4e30\u5ea6\u4fe1\u606f\u8fdb\u884c\u6837\u672c\u95f4\u8ddd\u79bb\u8ba1\u7b97\uff0c \u4e5f\u53ef\u4ee5\u7528OTUs\u4e4b\u95f4\u7684\u7cfb\u7edf\u53d1\u751f\u5173\u7cfb\u8fdb\u884c\u8ba1\u7b97\u3002<\/p>\n
UniFrac\u662f\u7528\u4e8e\u6bd4\u8f83\u751f\u7269\u7fa4\u843d\u7684\u4e00\u79cd\u8ddd\u79bb\u5ea6\u91cf\uff0c\u5b83\u5728\u8ba1\u7b97\u8fc7\u7a0b\u4e2d\u5305\u542b\u4e86\u9057\u4f20\u8ddd\u79bb\uff08phylogenetic distances\uff09\u7684\u4fe1\u606f, \u6839\u636e\u6784\u5efa\u7684\u8fdb\u5316\u6811\u679d\u7684\u957f\u5ea6\u8ba1\u91cf\u4e24\u4e2a\u4e0d\u540c\u73af\u5883\u6837\u54c1\u4e4b\u95f4\u7684\u5dee\u5f02\u3002<\/p>\n
UniFrac \u5206\u6790\u5206\u4e3aweighted unifrac \u548cunweighted unifrac \u4e24\u79cd\u5ea6\u91cf\u65b9\u6cd5\uff0c\u4e24\u8005\u4e4b\u95f4\u5dee\u5f02\u5728\u4e8e\u662f\u5426\u8ba1\u5165\u4e0d\u540c\u73af\u5883\u6837\u54c1\u7684\u5e8f\u5217\u76f8\u5bf9\u4e30\u5ea6\u3002<\/p>\n
Unweighted UniFrac\u53ea\u8003\u8651\u4e86\u7269\u79cd\u6709\u65e0\u7684\u53d8\u5316\uff0c\u56e0\u6b64\u7ed3\u679c\u4e2d\uff0c\u8ddd\u79bb\u4e3a0\u8868\u793a\u4e24\u4e2a\u5fae\u751f\u7269\u7fa4\u843d\u95f4OTU\u7684\u79cd\u7c7b\u4e00\u81f4\u3002\u800cWeighted UniFrac\u5219\u540c\u65f6\u8003\u8651\u7269\u79cd\u6709\u65e0\u548c\u7269\u79cd\u4e30\u5ea6\u7684\u53d8\u5316\uff0c\u8ddd\u79bb\u4e3a0\u5219\u8868\u793a\u7fa4\u843d\u95f4OTU\u7684\u79cd\u7c7b\u548c\u6570\u91cf\u90fd\u4e00\u81f4\u3002<\/p>\n
\u5b9e\u9645\u5e94\u7528\u7684\u5408\u7406\u6027\uff1a\u5728\u73af\u5883\u6837\u672c\u7684\u68c0\u6d4b\u4e2d\uff0c\u7531\u4e8e\u5f71\u54cd\u56e0\u7d20\u590d\u6742\uff0c\u7fa4\u843d\u95f4\u7269\u79cd\u7684\u7ec4\u6210\u5dee\u5f02\u66f4\u4e3a\u5267\u70c8\uff0c\u56e0\u6b64\u5f80\u5f80\u91c7\u7528\u975e\u52a0\u6743\u65b9\u6cd5\u8fdb\u884c\u5206\u6790\u3002\u4f46\u5982\u679c\u8981\u7814\u7a76\u5bf9\u7167\u4e0e\u5b9e\u9a8c\u5904\u7406\u7ec4\u4e4b\u95f4\u7684\u5173\u7cfb\uff0c\u4f8b\u5982\u7814\u7a76\u77ed\u671f\u9752\u9709\u7d20\u5904\u7406\u540e\uff0c\u4eba\u80a0\u9053\u7684\u83cc\u843d\u53d8\u5316\u60c5\u51b5\uff0c\u7531\u4e8e\u5904\u7406\u540e\u7fa4\u843d\u7684\u7ec4\u6210\u4e00\u822c\u4e0d\u4f1a\u53d1\u751f\u5927\u6539\u53d8\uff0c\u4f46\u7fa4\u843d\u7684\u4e30\u5ea6\u53ef\u80fd\u4f1a\u53d1\u751f\u5927\u53d8\u5316\uff0c\u56e0\u6b64\u66f4\u9002\u5408\u7528\u52a0\u6743\u65b9\u6cd5\u53bb\u8ba1\u7b97\u3002<\/p>\n
\u4e3b\u5750\u6807\u5206\u6790\uff08Principal Coordinate Analysis\uff0cPCoA\uff09\u5c06\u591a\u7ef4\u6570\u636e\u8fdb\u884c\u964d\u7ef4\uff0c\u662f\u4e00\u79cd\u7814\u7a76\u6570\u636e\u76f8\u4f3c\u6027\u6216\u5dee\u5f02\u6027\u7684\u53ef\u89c6\u5316\u65b9\u6cd5\uff0c\u57fa\u4e8e\u8ddd\u79bb\u77e9\u9635\u6765\u5bfb\u627e\u4e3b\u5750\u6807\uff0c\u901a\u8fc7\u4e00\u7cfb\u5217\u7684\u7279\u5f81\u503c\u548c\u7279\u5f81\u5411\u91cf\u8fdb\u884c\u6392\u5e8f\u540e\uff0c\u9009\u62e9\u4e3b\u8981\u6392\u5728\u524d\u51e0\u4f4d\u7684\u7279\u5f81\u503c\uff0c\u6709\u6548\u5730\u627e\u51fa\u6570\u636e\u4e2d\u6700\u201c\u4e3b\u8981\u201d\u7684\u5143\u7d20\u548c\u7ed3\u6784\uff0c\u5bf9\u6837\u672c\u4e4b\u95f4\u7684\u5173\u7cfb\u8fdb\u884c\u63cf\u8ff0\u3002\u9996\u5148\u968f\u673a\u53d6\u6837\u8ba1\u7b97\u5404\u6837\u672c\u4e4b\u95f4\u7684unifrac\u8ddd\u79bb\uff0c\u518d\u6839\u636e\u8ddd\u79bb\u77e9\u9635\u7ed8\u5236\u4e8c\u7ef4PCoA\u56fe\uff0c\u5982\u679c\u6837\u672c\u7684\u8ddd\u79bb\u8d8a\u63a5\u8fd1\uff08\u5373\u7269\u79cd\u7684\u4e30\u5ea6\u548c\u6784\u6210\u8d8a\u76f8\u4f3c\uff09\uff0c\u5219\u5b83\u4eec\u5728PCoA\u56fe\u4e2d\u7684\u8ddd\u79bb\u8d8a\u8fd1\u3002\u7ed3\u679c\u53ef\u89c1\u4e0b\u56fe \u3002<\/p>\n<\/p>\n
NMDS\uff08Non-metric Multidimensional scaling\uff09\u975e\u5ea6\u91cf\u591a\u7ef4\u5c3a\u5ea6\u5206\u6790\u662f\u4e00\u79cd\u5c06\u591a\u7ef4\u7a7a\u95f4\u7684\u7814\u7a76\u5bf9\u8c61\uff08\u6837\u672c\u6216\u53d8\u91cf\uff09\u7b80\u5316\u5230\u4f4e\u7ef4\u7a7a\u95f4\u8fdb\u884c\u5b9a\u4f4d\u3001\u5206\u6790\u548c\u5f52\u7c7b\uff0c\u540c\u65f6\u53c8\u4fdd\u7559\u5bf9\u8c61\u95f4\u539f\u59cb\u5173\u7cfb\u7684\u6570\u636e\u5206\u6790\u65b9\u6cd5\u3002\u9002\u7528\u4e8e\u65e0\u6cd5\u83b7\u5f97\u7814\u7a76\u5bf9\u8c61\u95f4\u7cbe\u786e\u7684\u76f8\u4f3c\u6027\u6216\u76f8\u5f02\u6027\u6570\u636e\uff0c\u4ec5\u80fd\u5f97\u5230\u4ed6\u4eec\u4e4b\u95f4\u7b49\u7ea7\u5173\u7cfb\u6570\u636e\u7684\u60c5\u5f62\u3002\u5176\u57fa\u672c\u7279\u5f81\u662f\u5c06\u5bf9\u8c61\u95f4\u7684\u76f8\u4f3c\u6027\u6216\u76f8\u5f02\u6027\u6570\u636e\u770b\u6210\u70b9\u95f4\u8ddd\u79bb\u7684\u5355\u8c03\u51fd\u6570\uff0c\u5728\u4fdd\u6301\u539f\u59cb\u6570\u636e\u6b21\u5e8f\u5173\u7cfb\u7684\u57fa\u7840\u4e0a\uff0c\u7528\u65b0\u7684\u76f8\u540c\u6b21\u5e8f\u7684\u6570\u636e\u5217\u66ff\u6362\u539f\u59cb\u6570\u636e\u8fdb\u884c\u5ea6\u91cf\u578b\u591a\u7ef4\u5c3a\u5ea6\u5206\u6790\u3002\u5176\u7279\u70b9\u662f\u6839\u636e\u6837\u54c1\u4e2d\u5305\u542b\u7684\u7269\u79cd\u4fe1\u606f\uff0c\u4ee5\u70b9\u7684\u5f62\u5f0f\u53cd\u6620\u5728\u591a\u7ef4\u7a7a\u95f4\u4e0a\uff0c\u800c\u5bf9\u4e0d\u540c\u6837\u54c1\u95f4\u7684\u5dee\u5f02\u7a0b\u5ea6\uff0c\u5219\u662f\u901a\u8fc7\u70b9\u4e0e\u70b9\u95f4\u7684\u8ddd\u79bb\u4f53\u73b0\u7684\uff0c\u6700\u7ec8\u83b7\u5f97\u6837\u54c1\u7684\u7a7a\u95f4\u5b9a\u4f4d\u70b9\u56fe\u3002<\/p>\n<\/p>\n
LEfSe\u5206\u6790\u5373LDA Effect Size\u5206\u6790\uff0c\u662f\u4e00\u79cd\u7528\u4e8e\u53d1\u73b0\u9ad8\u7ef4\u751f\u7269\u6807\u8bc6\u548c\u63ed\u793a\u57fa\u56e0\u7ec4\u7279\u5f81\u7684\u5206\u6790\uff0c\u4f7f\u7528non-parametric factorial Kruskal-Wallis (KW) sum-rank test\uff08\u975e\u53c2\u6570\u56e0\u5b50\u514b\u9c81\u65af\u5361\u5c14\u2014\u6c83\u5229\u65af\u548c\u79e9\u9a8c\u68c0\uff09\u68c0\u6d4b\u5177\u6709\u663e\u8457\u4e30\u5ea6\u5dee\u5f02\u7279\u5f81\uff0c\u5e76\u627e\u5230\u4e0e\u4e30\u5ea6\u6709\u663e\u8457\u6027\u5dee\u5f02\u7684\u7c7b\u7fa4\u3002\u6700\u540e\uff0cLEfSe\u91c7\u7528\u7ebf\u6027\u5224\u522b\u5206\u6790\uff08LDA\uff09\u6765\u4f30\u7b97\u6bcf\u4e2a\u7ec4\u5206\uff08\u7269\u79cd\uff09\u4e30\u5ea6\u5bf9\u5dee\u5f02\u6548\u679c\u5f71\u54cd\u7684\u5927\u5c0f\u3002\u80fd\u591f\u5728\u7ec4\u4e0e\u7ec4\u4e4b\u95f4\u5bfb\u627e\u5177\u6709\u7edf\u8ba1\u5b66\u5dee\u5f02\u7684\u751f\u7269\u6807\u8bc6\uff08Biomarker\uff09\uff0c\u5373\u7ec4\u95f4\u5dee\u5f02\u663e\u8457\u7684\u7269\u79cd\u3002<\/p>\n
\u901a\u8fc7LDA\u5206\u6790\uff08\u7ebf\u6027\u56de\u5f52\u5206\u6790\uff09\u7edf\u8ba1\u4e0d\u540c\u7ec4\u522b\u4e2d\u6709\u663e\u8457\u4f5c\u7528\u5fae\u751f\u7269\u7c7b\u7fa4\u7684LDA\u5206\u503c\uff0c\u5c55\u793a\u4e86LDA \u5206\u503c\u5927\u4e8e\u8bbe\u5b9a\u9608\u503c\u7684\u7269\u79cd\uff0c\u5373\u5177\u6709\u7edf\u8ba1\u5b66\u5dee\u5f02\u7684biomaker\u3002\u67f1\u72b6\u56fe\u7684\u957f\u5ea6\u4ee3\u8868\u663e\u8457\u5dee\u5f02\u7269\u79cd\u7684\u5f71\u54cd\u5927\u5c0f\uff1b<\/p>\n<\/p>\n
#\u7b2c\u4e00\u6b65\uff1a\u9700\u8981\u628a\u4e30\u5ea6\u4fe1\u606f\u7684\u8868\u683c\u8f6c\u5316\u6210LEfSe\u8bc6\u522b\u7684\u683c\u5f0f\u3002\u8fd9\u4e00\u6b65\u4f1a\u751f\u6210.in\u7ed3\u5c3e\u7684\u6587\u4ef6<\/p>\n<\/li>\n
format_input.py inputfile inputfile.in -c 1 -s -1 -u 2 -o 1000000<\/p>\n<\/li>\n
#\u7b2c\u4e8c\u6b65\uff1a\u7edf\u8ba1\u663e\u8457\u5dee\u5f02\u7684biomarker\u3001\u7edf\u8ba1\u5b50\u7ec4\u7ec4\u95f4\u5dee\u5f02\u3001\u7edf\u8ba1effect sizes\uff08LDA score\uff09\uff0c\u751f\u6210.res\u683c\u5f0f\u7684\u6587\u4ef6<\/p>\n<\/li>\n
run_lefse.py -l 2 inputfile.in inputfile.res<\/p>\n<\/li>\n
#\u7b2c\u4e09\u6b65\uff1a\u57fa\u4e8e\u7b2c\u4e8c\u6b65\u7684\u6570\u636e\uff0c\u751f\u6210\u591a\u79cd\u8f93\u51fa\u6587\u4ef6\uff0c\u4f8b\u5982png\u548cpdf\u3002<\/p>\n<\/li>\n
plot_res.py –dpi 400 inputfile.res inputfile.png<\/p>\n<\/li>\n
#\u8fdb\u5316\u5206\u652f\u56fe<\/p>\n<\/li>\n
plot_cladogram.py –dpi 400 inputfile.res inputfile.cladogram.png –format png<\/p>\n<\/li>\n
\u8fdb\u5316\u5206\u652f\u56fe<\/p>\n
\u7531\u5185\u81f3\u5916\u8f90\u5c04\u7684\u5706\u5708\u4ee3\u8868\u4e86\u7531\u95e8\u81f3\u5c5e\uff08\u6216\u79cd\uff09\u7684\u5206\u7c7b\u7ea7\u522b\u3002\u5728\u4e0d\u540c\u5206\u7c7b\u7ea7\u522b\u4e0a\u7684\u6bcf\u4e00\u4e2a\u5c0f\u5706\u5708\u4ee3\u8868\u8be5\u6c34\u5e73\u4e0b\u7684\u4e00\u4e2a\u5206\u7c7b\uff0c\u5c0f\u5706\u5708\u76f4\u5f84\u5927\u5c0f\u4e0e\u76f8\u5bf9\u4e30\u5ea6\u5927\u5c0f\u5448\u6b63\u6bd4\u3002<\/p>\n
\u7740\u8272\u539f\u5219\uff1a\u65e0\u663e\u8457\u5dee\u5f02\u7684\u7269\u79cd\u7edf\u4e00\u7740\u8272\u4e3a\u9ec4\u8272\uff0c\u5dee\u5f02\u7269\u79cd Biomarker\u8ddf\u968f\u7ec4\u8fdb\u884c\u7740\u8272\uff0c\u7ea2\u8272\u8282\u70b9\u8868\u793a\u5728\u7ea2\u8272\u7ec4\u522b\u4e2d\u8d77\u5230\u91cd\u8981\u4f5c\u7528\u7684\u5fae\u751f\u7269\u7c7b\u7fa4\uff0c\u7eff\u8272\u8282\u70b9\u8868\u793a\u5728\u7eff\u8272\u7ec4\u522b\u4e2d\u8d77\u5230\u91cd\u8981\u4f5c\u7528\u7684\u5fae\u751f\u7269\u7c7b\u7fa4\uff0c\u5176\u5b83\u5708\u989c\u8272\u610f\u4e49\u7c7b\u540c\u3002\u56fe\u4e2d\u82f1\u6587\u5b57\u6bcd\u8868\u793a\u7684\u7269\u79cd\u540d\u79f0\u5728\u53f3\u4fa7\u56fe\u4f8b\u4e2d\u8fdb\u884c\u5c55\u793a\u3002<\/p>\n
\u5148\u770b\u62a5\u544a\u4e2d\u6570\u636e\u91cf\u662f\u591a\u5c11\uff0c\u6709\u591a\u5c11\u6761\u5e8f\u5217\uff0c\u4e00\u822c\u81f3\u5c11\u9700\u89811\u4e07\u6761\u5e8f\u5217\u8fdb\u884c\u540e\u7eed\u5206\u6790\u3002\u770b\u770b\u5f97\u5230\u591a\u5c11\u4e2aOTU\uff0c\u4ee5\u53ca\u4e30\u5ea6\u524d10\u7684\u5fae\u751f\u7269\u662f\u4ec0\u4e48\u4ee5\u53ca\u5728\u4e0d\u540c\u5206\u7ec4\u4e2d\u4e30\u5ea6\u7684\u53d8\u5316\u3002<\/p>\n<\/li>\n
\u5728OTU \u5206\u6790\u6587\u4ef6\u4e2d\u770b\u5404\u5fae\u751f\u7269\u4e30\u5ea6\u6587\u4ef6\uff0c\u4e00\u822c\u91cc\u9762\u6709\u95e8\u3001\u7eb2\u3001\u76ee\u3001\u79d1\u3001\u5c5e\u6c34\u5e73\u7684\u4e30\u5ea6\uff0c\u76ee\u524d\u4e3b\u6d41\u770b\u95e8\u6c34\u5e73\u548c\u5c5e\u6c34\u5e73\u3002<\/p>\n<\/li>\n
\u770bAlpha\u591a\u6837\u6027\u4e2d\u7a00\u91ca\u66f2\u7ebf\u3001Shannon\u6216Rank abundance\u66f2\u7ebf\u662f\u5426\u9971\u548c\uff0cgoods_coverage\u662f\u542698%\u4ee5\u4e0a\uff08\u6570\u636e\u91cf\u662f\u5426\u591f\uff09\u3002\u770b\u770b\u6bcf\u4e2a\u6837\u672c\u7684\u591a\u6837\u6027 Alpha\u591a\u6837\u6027\uff0c\u56db\u5927\u6307\u6570\uff08Shannon\u3001simpson\u3001ace\u3001chao1\uff09\uff0c\u770b\u770b\u7ec4\u95f4\u662f\u5426\u6709\u591a\u6837\u6027\u5dee\u5f02\uff0c\u4e00\u822c\u6307\u6570\u95f4\u53d8\u5316\u662f\u4e00\u81f4\u7684\uff0c\u5982\u679c\u4e0d\u4e00\u81f4\u53ef\u4ee5\u9009\u62e9\u5176\u4e2d\u7684\u4e00\u4e24\u79cd\u4f5c\u4e3a\u7ed3\u679c\u3002<\/p>\n<\/li>\n
Beta\u591a\u6837\u6027\u4e2dPCA\u3001PCOA\u3001NMDS\u964d\u7ef4\u5206\u6790\u7684\u56fe\uff0c\u770b\u770b\u4e0d\u540c\u5206\u7ec4\u662f\u5426\u80fd\u5206\u5f00\uff0c\u5982\u679c\u8089\u773c\u80fd\u770b\u5230\u660e\u663e\u7684\u5206\u79bb\uff0c\u8bf4\u660e\u7ec4\u95f4\u7684\u5dee\u5f02\u5f88\u5927\u3002\u5f88\u591a\u60c5\u51b5\u4e0b\uff0c\u4e0d\u4e00\u5b9a\u6709\u660e\u663e\u7684\u5206\u79bb\uff0c\u8fd9\u65f6\u9700\u8981\u770b\u770badonis\u6216\u8005anosim\u7684P\u503c\uff0c\u770b\u7ec4\u95f4\u662f\u5426\u6709\u7edf\u8ba1\u5b66\u7684\u5dee\u5f02\u3002<\/p>\n<\/li>\n
\u770b\u770bLEfSe\u548cMetastats\u5206\u6790\u51fa\u6765\u7684\u663e\u8457\u5dee\u5f02\u7684\u7269\u79cd\uff0c\u6ce8\u610f\uff1aMetastats\u5206\u6790\u662f\u4e24\u4e24\u7ec4\u95f4\u6bd4\u8f83\uff0cLEfSe\u5206\u6790\u662f\u591a\u7ec4\u95f4\u5dee\u5f02\u7684\u6bd4\u8f83\u3002<\/p>\n<\/li>\n
\u901a\u5e38\u7814\u7a76\u662f\u7684\u5065\u5eb7\u4eba\u548c\u60a3\u75c5\u4eba\u7fa4\u7684\u7caa\u4fbf\u6837\u672c\uff0c\u89e3\u6790\u60a3\u75c5\u4eba\u7fa4\u80a0\u9053\u5fae\u751f\u7269\u7684\u53d8\u5316\u60c5\u51b5\u3002\u5176\u4e2d\u6700\u5173\u952e\u7684\u662f\u627e\u5230\u5305\u62ec\u6709\u76ca\u83cc\u548c\u6709\u5bb3\u83cc\u5728\u5185\u7684\u5dee\u5f02\u7269\u79cd\u3002\u5982\u679c\u6837\u54c1\u7684\u6570\u76ee\u4e0d\u591f\uff0c\u4f1a\u4f7f\u5f97\u7ec4\u95f4\u7684\u7edf\u8ba1\u5b66\u5dee\u5f02\u4e0d\u591f\u663e\u8457\uff0c\u8fd9\u4e2a\u65f6\u5019\u770b\u8d8b\u52bf\u4e5f\u53ef\u4ee5\u3002<\/p>\n<\/li>\n
\u6837\u672c\u7684\u91cd\u590d\u5bf9\u4e8e\u6d4b\u5e8f\u7684\u5b9e\u9a8c\u8bbe\u8ba1\u4ee5\u53ca\u540e\u7eed\u4fe1\u606f\u5206\u6790\u90fd\u975e\u5e38\u91cd\u8981\uff0c\u8bbe\u7f6e\u591a\u4e2a\u6837\u54c1\u91cd\u590d\u4e3b\u8981\u6709\u4ee5\u4e0b\u51e0\u4e2a\u4f5c\u7528\uff1a<\/p>\n
1\uff09\u80fd\u591f\u6d88\u9664\u7ec4\u5185\u8bef\u5dee\u3001\u68c0\u6d4b\u79bb\u7fa4\u6837\u672c\uff1a\u5f02\u5e38\u6837\u672c\u7684\u5b58\u5728\uff0c\u4f1a\u4e25\u91cd\u5f71\u54cd\u6d4b\u5e8f\u7ed3\u679c\u7684\u51c6\u786e\u6027\uff0c\u901a\u8fc7\u540e\u7eed\u4fe1\u606f\u5206\u6790\u53ef\u4ee5\u53d1\u73b0\u5f02\u5e38\u6837\u672c\uff0c\u5c06\u5176\u6392\u9664\u3002<\/p>\n
2\uff09\u589e\u5f3a\u7ed3\u679c\u7684\u53ef\u9760\u6027\u3002\u6d4b\u5e8f\u7684\u6837\u672c\u8d8a\u591a\uff0c\u8d8a\u80fd\u591f\u964d\u4f4e\u80cc\u666f\u5dee\u5f02\uff0c\u4ece\u800c\u589e\u52a0\u7ed3\u679c\u53ef\u4fe1\u5ea6\uff1b<\/p>\n
\u4e00\u822c\u60c5\u51b5\u4e0b\uff0c\u4e2a\u4f53\u4e4b\u95f4\u5dee\u522b\u8f83\u5c0f\u7684\u6a21\u5f0f\u52a8\u7269\uff08\u6bd4\u5982\u5927\u9f20\uff0c\u5c0f\u9f20\u3001\u9e21\u7b49\uff09\u5efa\u8bae\u6bcf\u7ec4\u81f3\u5c115\u4e2a\u751f\u7269\u5b66\u91cd\u590d\uff0c\u4e00\u822c\u63a8\u835010\u4e2a\u751f\u7269\u5b66\u91cd\u590d\u3002<\/p>\n
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\u4e00\u822c\u5efa\u8bae\u591a\u505a\u51e0\u4e2a\u751f\u7269\u5b66\u91cd\u590d\uff0c\u82e5\u662f\u9047\u5230\u4e2a\u4f53\u4e4b\u95f4\u5dee\u522b\u8f83\u5927\u6216\u8005\u6837\u54c1\u5904\u7406\u4e2d\u51fa\u73b0\u610f\u5916\u7b49\u60c5\u51b5\u53ef\u4ee5\u9009\u62e9\u5254\u9664\u4e2a\u522b\u6837\u672c\uff0c\u907f\u514d\u540e\u671f\u6837\u672c\u6570\u91cf\u4e0d\u591f\uff0c\u5982\u679c\u8865\u9001\u5219\u803d\u8bef\u65f6\u95f4\uff0c\u800c\u4e14\u4e0d\u662f\u540c\u4e00\u6279\u7684\u6570\u636e\u4f1a\u5bfc\u81f4\u91cd\u590d\u6027\u4e0d\u597d\u7684\u60c5\u51b5\u53d1\u751f\u3002<\/p>\n
\u6587\u732e\u4e2d\u5b58\u572816S rRNA\u57fa\u56e0\u6d4b\u5e8f\u548c16S rDNA\u6d4b\u5e8f\u4e24\u79cd\u8bf4\u6cd5\uff0c\u5b9e\u9645\u4e0a\u8fd9\u4e24\u79cd\u8bf4\u6cd5\u90fd\u53ef\u4ee5\u3002<\/p>\n
16S\u4e2d\u7684’S’\u662f\u4e00\u4e2a\u6c89\u964d\u7cfb\u6570\uff0c\u4ea6\u5373\u53cd\u6620\u751f\u7269\u5927\u5206\u5b50\u5728\u79bb\u5fc3\u573a\u4e2d\u5411\u4e0b\u6c89\u964d\u901f\u5ea6\u7684\u4e00\u4e2a\u6307\u6807\uff0c\u503c\u8d8a\u9ad8\uff0c\u8bf4\u660e\u5206\u5b50\u8d8a\u5927\u3002rDNA \u548crRNA\u4e2d\u7684\u5c0f\u5199\u5b57\u6bcd’r’\u662fribosome\uff08\u6838\u7cd6\u4f53\uff09\u7684\u7f29\u5199\u3002<\/p>\n
rDNA\u6307\u7684\u662f\u57fa\u56e0\u7ec4\u4e2d\u7f16\u7801\u6838\u7cd6\u4f53RNA\uff08rRNA\uff09\u5206\u5b50\u7684\u5bf9\u5e94\u7684DNA\u5e8f\u5217\uff0c\u4e5f\u5c31\u662f\u7f16\u780116S rRNA\u7684\u57fa\u56e0\u3002<\/p>\n
rRNA\u6307\u7684\u662frDNA\u7684\u8f6c\u5f55\u4ea7\u7269\uff0c\u5b83\u662f\u6784\u6210\u6838\u7cd6\u4f53\u7684\u91cd\u8981\u6210\u5206\uff0c\u6838\u7cd6\u4f53\u7531\u8bb8\u591a\u5c0f\u7684rRNA\u5206\u5b50\u7ec4\u88c5\u800c\u6210\uff0c16S rRNA\u662f\u5176\u4e2d\u4e00\u4e2a\u5143\u4ef6\u3002<\/p>\n
\u6240\u4ee5\u6211\u4eec\u7814\u7a7616S\u83cc\u7fa4\u6d4b\u5e8f\u7684\u5bf9\u8c61\u90fd\u662fDNA\uff0c\u800c\u4e0d\u662fRNA\u3002<\/p>\n
\u76ee\u524d\u768416S rRNA\u6269\u589e\u2f26\u6d4b\u5e8f\u53ea\u80fd\u68c0\u6d4b\u5fae\u751f\u7269\u7fa4\u843d\u7684\u76f8\u5bf9\u4e30\u5ea6\uff0c\uf967\u80fd\u5f97\u5230\u7edd\u5bf9\u7684\u4e30\u5ea6\u3002<\/p>\n
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\u57fa\u4e8e\u6b64\u95ee\u9898\uff0c\u6709\u65b9\u6cd5\u662f\u5728DNA\u63d0\u53d6\u6b65\u9aa4\u4e4b\u524d\u52a0\u2f0a\u4e00\u79cd\u7fa4\u843d\u4e2d\uf967\u5b58\u5728\u7684\u7ec6\u83cc\u4f5c\u4e3a\u5185\u6807 \uff0c\u7136\u540e\u5229\u7528\u5185\u6807\u7684\u7edd\u5bf9\u548c\u76f8\u5bf9\u4e30\u5ea6\u8ba1\u7b97\u5176\u4ed6\u7269\u79cd\u7684\u7edd\u5bf9\u4e30\u5ea6\u3002\u6216\u662f\u5411\u6837\u54c1\u4e2d\u52a0\u5165\u5408\u6210\u7684\u5d4c\u5408\u4f53DNA\u4f5c\u4e3a\u5185\u53c2\uff0c\u53ef\u5b9a\u91cf\u8ba1\u7b97\u73af\u5883\u6837\u54c1\u4e2d\u5fae\u751f\u7269\u7684\u7edd\u5bf9\u4e30\u5ea6\uff0c\u5e76\u5728\u4e0d\u540c\u6765\u6e90\u6837\u54c1\u95f4\u8fdb\u884c\u6bd4\u5bf9\u3002<\/p>\n
\u7531\u4e8e\u4e0d\u540c\u7684\u7edf\u8ba1\u5206\u6790\u8f6f\u4ef6\u6240\u4f7f\u7528\u7684\u7edf\u8ba1\u68c0\u9a8c\u7684\u65b9\u6cd5\u6709\u6240\u4e0d\u540c\uff0c\u56e0\u6b64\u5f97\u51fa\u7684\u7ed3\u679c\u4e5f\u4f1a\u5b58\u5728\u5dee\u5f02\u3002\u4f8b\u5982LEfSe\u4f7f\u7528\u4e86\u79e9\u548c\u68c0\u9a8c\u548c\u7ebf\u6027\u5224\u522b\u5206\u6790\uff08LDA\uff09\uff0c\u5982\u679c\u67d0\u4e2a\u83cc\u7684\u4e30\u5ea6\u901a\u8fc7Metastats\u7b97\u51fa\u6765\u6709\u5dee\u5f02\uff0c\u800cLEfSe\u7b97\u51fa\u6765\u6ca1\u6709\u5dee\u5f02\uff0c\u8fd9\u65f6\u53ef\u4ee5\u6839\u636e\u81ea\u5df1\u7684\u7814\u7a76\u80cc\u666f\u9009\u62e9\u6700\u4e3a\u7b26\u5408\u9884\u671f\u7684\u5206\u6790\u7ed3\u679c\uff0c\u8fd9\u4e9b\u7edf\u8ba1\u5206\u6790\u65b9\u6cd5\u7b5b\u9009\u7ed3\u679c\u90fd\u662f\u53ef\u4fe1\u7684\u3002<\/p>\n
\u6ce8\u91ca\u6570\u636e\u5e93\u4e3b\u8981\u6709SILVA\u3001RDP\u3001Greengenes\u3002<\/p>\n
\u56e0\u4e3aSILVA\u6570\u636e\u5e93\u66f4\u65b0\u6bd4\u8f83\u53ca\u65f6\uff0c\u56e0\u6b64\u662f\u76ee\u524drRNA\u57fa\u56e0\u9ad8\u901a\u91cf\u6d4b\u5e8f\u540e\u6700\u5e38\u9009\u7528\u7684\u53c2\u8003\u6570\u636e\u5e93\u4e4b\u4e00\u3002\u6b64\u5916\uff0cSILVA\u4e5f\u53ef\u88ab\u7528\u4e8e\u5e73\u65f6\u83cc\u79cd\u9274\u5b9a\u65f6\uff0c\u5bf9rRNA\u57fa\u56e0sanger\u6d4b\u5e8f\u540e\u7684\u7269\u79cd\u8fdb\u884c\u5206\u7c7b\u9274\u5b9a\uff0c\u6b64\u65f6\u4e3b\u8981\u7528\u5176SINA Alignment Service\u529f\u80fd\uff08https:\/\/www.\/aligner\/\uff09\uff0c\u53ef\u975e\u5e38\u65b9\u4fbf\u5730\u786e\u5b9a\u67d0\u6761rRNA\u57fa\u56e0\u5e8f\u5217\u4ece\u95e8\u5230\u5c5e\/\u79cd\u6c34\u5e73\u7684\u5206\u7c7b\u4fe1\u606f\u5e76\u7ed9\u51fa\u5404\u5206\u7c7b\u6c34\u5e73\u76f8\u5e94\u7684\u7f6e\u4fe1\u5ea6\u3002<\/p>\n
RDP\u6570\u636e\u5e93\u5168\u79f0\u201cRibosomalDatabase Project\u201d\uff0c\u8be5\u6570\u636e\u5e93\u63d0\u4f9b\u8d28\u63a7\u3001\u6bd4\u5bf9\u3001\u6ce8\u91ca\u7684\u7ec6\u83cc\u3001\u53e4\u83cc16S rRNA\u57fa\u56e0\u548c\u771f\u83cc28S rRNA\u57fa\u56e0\u5e8f\u5217\u3002\u4e3b\u8981\u7528\u5176Classifier\u529f\u80fd\uff08http:\/\/rdp.cme.\/classifier\/classifier.jsp\uff09\uff0c\u53ef\u975e\u5e38\u65b9\u4fbf\u5730\u786e\u5b9a\u67d0\u6761rRNA\u57fa\u56e0\u5e8f\u5217\u4ece\u95e8\u5230\u5c5e\/\u79cd\u6c34\u5e73\u7684\u5206\u7c7b\u4fe1\u606f\u5e76\u7ed9\u51fa\u5404\u6c34\u5e73\u76f8\u5e94\u7684\u7f6e\u4fe1\u5ea6\u3002<\/p>\n
Greengenes\u662f\u6570\u636e\u5e93\u76ee\u524d\u6ca1\u6709\u66f4\u65b0\uff0c\u505c\u7559\u57282013\u5e745\u6708\u66f4\u65b0\u7684gg_13_5\u7248\u672c\uff0c\u800c\u9884\u6d4b\u5fae\u751f\u7269\u7fa4\u843d\u529f\u80fd\u7684\u5206\u6790\u8f6f\u4ef6PICRUST\uff0c\u662f\u57fa\u4e8egg_13_5\u6570\u636e\u5e93\u5f00\u53d1\u7684\uff0c\u56e0\u6b64\uff0c\u60f3\u505aPICRUST\u5206\u6790\u4e5f\u5fc5\u987b\u4f9d\u6258Greengenes\u7684gg_13_5\u6570\u636e\u5e93\u8fdb\u884c\u6bd4\u5bf9\u3002<\/p>\n
[1] Tanja Mago\u010d, Steven L. Salzberg. (2011).FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics (2011) 27 (21): 2957-2963.<\/p>\n
[2] Caporaso, J. G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F. D., et al. (2010). QIIME allows analysis of high-throughput community sequencing data. NatureMethods, 7: 335\u2013336.<\/p>\n
[3] Edgar RC1, Haas BJ, Clemente JC, Quince C, Knight R. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics, 2011 Aug 15;27(16):2194-200.<\/p>\n
[4] Edgar, R.C. (2010) Search and clustering orders of magnitude faster than BLAST, Bioinformatics, 26, 2460\u20132461.<\/p>\n
[5]Wang, Q., Garrity, G. M., Tiedje, J. M., Cole, J. R. (2007). Na\u00efve bayesian classifier for rapid assignment of rrnasequences into the new bacterial taxonomy. Applied and environmental microbiology, 73:5261-5267.<\/p>\n
[6] Ondov BD, Bergman NH, and Phillippy AM. Interactive metagenomic visualization in a Web browser. BMC Bioinformatics. 2011 Sep 30; 12(1):385.<\/p>\n
[7] Chao, A. 1984. Non-parametric estimation of the number of classes in a population. Scandinavian Journal of Statistics 11, 265-270.<\/p>\n
[8] Shannon, C. E. and Weaver W. (1948) A mathematical theory of communication. The Bell System Technical Journal, 27, 379\u2013423 and 623\u2013656.<\/p>\n
[9] Simpson, E. H. (1949). ‘Measurement of diversity’. Nature 163: 688.<\/p>\n
[10] Lozupone, C., Knight, R.(2005).UniFrac: a new phylogenetic method for comparing microbial communities. Applied and environmental microbiology, 71:8228-8235.<\/p>\n","protected":false},"excerpt":{"rendered":"
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