{"id":24797,"date":"2024-01-17T10:04:40","date_gmt":"2024-01-17T02:04:40","guid":{"rendered":"http:\/\/www.biocloudservice.com\/wordpress\/?p=24797"},"modified":"2024-01-17T10:04:42","modified_gmt":"2024-01-17T02:04:42","slug":"%e5%9f%ba%e5%9b%a0%e5%ae%b6%e6%97%8f%e4%bf%9d%e5%a7%86%e7%ba%a7%e5%ae%9e%e6%93%8d%e5%88%86%e6%9e%90%e6%b5%81%e7%a8%8b","status":"publish","type":"post","link":"http:\/\/www.biocloudservice.com\/wordpress\/?p=24797","title":{"rendered":"\u57fa\u56e0\u5bb6\u65cf\u4fdd\u59c6\u7ea7\u5b9e\u64cd\u5206\u6790\u6d41\u7a0b"},"content":{"rendered":"

<\/a>
\n \u57fa\u56e0\u5bb6\u65cf\u4fdd\u59c6\u7ea7\u5b9e\u64cd\u5206\u6790\u6d41\u7a0b<\/p>\n

\u9996\u5148\uff0c\u4ec0\u4e48\u662f\u57fa\u56e0\u5bb6\u65cf\u5462\uff1f\u6240\u8c13\u7684\u57fa\u56e0\u5bb6\u65cf\u5c31\u662f\u4e00\u7c7b\u62e5\u6709\u7c7b\u4f3c\u7ed3\u6784\uff0c\u884c\u4f7f\u76f8\u540c\u529f\u80fd\u7684\u86cb\u767d\u5bb6\u65cf\uff0c\u628a\u8fd9\u4e2a\u7ed3\u8bba\u653e\u5728\u6838\u7b97\u5e8f\u5217\u6216\u8005\u6c28\u57fa\u9178\u5e8f\u5217\u5c42\u9762\u4e0a\uff0c\u5c31\u662f\u53ef\u80fd\u5177\u6709\u6781\u4e3a\u4fdd\u5b88\u7684\u529f\u80fd\u57df\uff0c\u800c\u5bfc\u81f4\u8fd9\u7c7b\u86cb\u767d\u5177\u6709\u7c7b\u4f3c\u7684\u7ed3\u6784\u548c\u884c\u4f7f\u76f8\u540c\u7684\u529f\u80fd\u3002<\/p>\n

\u57fa\u56e0\u5bb6\u65cf\u5206\u6790\u901a\u5e38\u7531\u4ee5\u4e0b4\u4e2a\u6b65\u9aa4\u7ec4\u6210\uff1a<\/strong><\/p>\n

1 \u57fa\u56e0\u5bb6\u65cf\u6210\u5458\u7684\u9274\u5b9a<\/strong><\/p>\n

\uff08\u8fd9\u662f\u6700\u5173\u952e\u3001\u6700\u91cd\u8981\u7684\u4e00\u6b65\uff0c\u4e5f\u662f\u5c0f\u679c\u8ba4\u4e3a\u6700\u6709\u7528\u7684\u4e00\u4e2a\u73af\u8282\uff0c\u9700\u8981\u8c28\u614e\u5206\u6790\uff0c\u8fd9\u4e00\u6b65\u51fa\u73b0\u95ee\u9898\uff0c\u540e\u9762\u7684\u5206\u6790\u4e5f\u4f1a\u6709\u8f83\u5927\u504f\u5dee\u3002\uff09\uff1b<\/p>\n

1.1 \u57fa\u56e0\u7ec4\u6587\u4ef6\uff08dna, cds, protein, gff3 or gtf\u6ce8\u91ca\u6587\u4ef6\uff09\u7684\u83b7\u53d6\uff1b<\/p>\n

\"IMG_256\"<\/p>\n

1.2 \u57fa\u56e0\u5bb6\u65cf\u9690\u9a6c\u5c14\u53ef\u592b\u6a21\u578b\uff08HMM model\uff09\u7684\u83b7\u53d6\uff1b<\/p>\n

\"IMG_256\"<\/p>\n

1.3 \u82e5\u6ca1\u6709\u5bf9\u5e94\u7684HMM model\uff0c\u5219\u9700\u8981\u81ea\u5df1\u6784\u5efa\uff1b<\/p>\n

1.4 \u901a\u8fc7HMM model\u5728\u57fa\u56e0\u7ec4\u6587\u4ef6\u4e2d\u641c\u5bfb \u5019\u9009\u57fa\u56e0\u5bb6\u65cf\u6210\u5458\uff1b<\/p>\n

1.5 \u901a\u8fc7\u672c\u5730blast+\u83b7\u53d6\u53c2\u8003\u57fa\u56e0\u5bb6\u65cf\u7684\u540c\u6e90\u5e8f\u5217 \uff08\u5019\u9009\u57fa\u56e0\u5bb6\u65cf\u6210\u5458\uff09\uff1b<\/p>\n

1.6 \u83b7\u53d6\u5019\u9009\u57fa\u56e0\u5bb6\u65cf\u6210\u5458\u7684\u5e8f\u5217\u4fe1\u606f\uff1b<\/p>\n

1.7 \u7ed3\u5408\u7cfb\u7edf\u53d1\u80b2\u6811\u3001\u4fdd\u5b88\u7ed3\u6784\u57df\u548c\u4fdd\u5b88\u57fa\u5e8f\uff08motif\uff09\u7b49\u786e\u5b9a\u6700\u7ec8\u7684\u57fa\u56e0\u5bb6\u65cf\u6210\u5458\uff1b<\/p>\n

1.8 \u68c0\u67e5\u6ce8\u91ca\u6587\u4ef6\u662f\u5426\u6b63\u786e\u3002<\/p>\n

2 \u57fa\u56e0\u5bb6\u65cf\u6210\u5458\u5e8f\u5217\u57fa\u672c\u4fe1\u606f\u7684\u83b7\u53d6<\/strong><\/p>\n

\uff08\u7b80\u5355\u64cd\u4f5c\uff0c\u5b9e\u9645\u4e0a\u5f88\u591a\u7ed3\u679c\u53ef\u80fd\u7528\u4e0d\u5230\uff0c\u4f1a\u5728\u5b9e\u9a8c\u8bbe\u8ba1\u8fc7\u7a0b\u4e2d\u8d77\u5230\u4e00\u5b9a\u7684\u53c2\u8003\u3002\uff09<\/p>\n

2.1 \u57fa\u56e0\u5bb6\u65cf\u6210\u5458\u86cb\u767d\u7684\u7406\u5316\u6027\u8d28\uff1b<\/p>\n

2.2 \u8de8\u819c\u7ed3\u6784\u57df\u3001\u4fe1\u53f7\u80bd\u3001\u4e9a\u7ec6\u80de\u5b9a\u4f4d\u7b49\uff1b<\/p>\n

<\/p>\n

3 \u6784\u5efa\u7cfb\u7edf\u53d1\u80b2\u6811<\/strong><\/p>\n

\uff08\u7cfb\u7edf\u53d1\u80b2\u6811\u662f\u4e00\u4e2a\u8f83\u5927\u7684\u7248\u5757\uff0c\u9700\u8981\u638c\u63e1\u7684\u5185\u5bb9\u8fd8\u662f\u86ee\u591a\u7684\u3002\u5355\u5c31\u6784\u5efa\u7cfb\u7edf\u53d1\u80b2\u6811\u6765\u8bf4\uff0c\u76f8\u5bf9\u7b80\u5355\uff0c\u4e00\u822c\u4e5f\u5bb9\u6613\u64cd\u4f5c\u3002\u4f46\u5728\u6811\u7684\u53ef\u89c6\u5316\u53ca\u7f8e\u5316\u7f16\u8f91\u8fc7\u7a0b\u4e2d\u5f80\u5f80\u5e76\u4e0d\u90a3\u4e48\u5bb9\u6613\uff0c\u56e0\u4e3a\u6811\u53ef\u4ee5\u5448\u73b0\u7684\u5185\u5bb9\u53ef\u4ee5\u975e\u5e38\u4e30\u5bcc\uff0c\u81f3\u4e8e\u5982\u4f55\u5c55\u793a\uff0c\u771f\u7684\u5168\u5728\u4e2a\u4eba\u3002\u8fd9\u91cc\u5148\u4e0d\u5c55\u5f00\u3002\uff09<\/p>\n

<\/p>\n

\u597d\u5427\uff0c\u5e9f\u8bdd\u5230\u6b64\u4e3a\u6b62\u3002<\/p>\n

\u4e0b\u9762\u7cfb\u7edf\u7684\u6574\u7406\u4e00\u4e0b\u5c0f\u679c\u5728\u57fa\u56e0\u5bb6\u65cf\u5206\u6790\u6d41\u7a0b\u4e2d\u7684\u5168\u90e8\u7684\u5b9e\u64cd\u6d41\u7a0b\u53ca\u4e00\u4e9b\u601d\u8003\u3002<\/p>\n

\u4e00\u3001\u57fa\u56e0\u5bb6\u65cf\u6210\u5458\u7684\u9274\u5b9a<\/strong><\/p>\n

#step1 \u5728Pfam\u6570\u636e\u5e93\u4e2d\u4e0b\u8f7d\u57fa\u56e0\u5bb6\u65cf\u86cb\u767d\u4fdd\u5b88\u7ed3\u6784\u57df\u7684\u9690\u9a6c\u5c14\u53ef\u592b\u6a21\u578b\uff08.hmm\uff09<\/p>\n

#step2 \u5728ensembl\u6570\u636e\u5e93\u4e2d\u4e0b\u8f7d\u7269\u79cd\u7684\u57fa\u56e0\u7ec4\u5e8f\u5217\u6587\u4ef6\uff0cCDS\u5e8f\u5217\u6587\u4ef6\uff0cgtf\u57fa\u56e0\u7ec4\u6ce8\u91ca\u6587\u4ef6\uff0cpep\u86cb\u767d\u8d28\u5e8f\u5217\u6587\u4ef6<\/p>\n

Homo_sapiens.GRCh38.dna.toplevel.fa.gz<\/p>\n

Homo_sapiens.GRCh38.cds.all.fa.gz<\/p>\n

Homo_sapiens.GRCh38.pep.all.fa.gz<\/p>\n

Homo_sapiens.GRCh38.98.gtf.gz<\/p>\n

gata.hmm<\/p>\n

#step3 \u5229\u7528HMMER\u8f6f\u4ef6\u521d\u6b65\u9274\u5b9a\u57fa\u56e0\u5bb6\u65cf\u6210\u5458\uff08\u4e00\u822c\u5229\u7528 –cut\u2014\u2014tc\u7b97\u6cd5\uff09<\/p>\n

cd \/home\/GeneFamily\/DATA\/human (\u6b64\u8def\u5f84\u5c31\u662f\u4e0a\u8ff0\u6570\u636e\u4e0b\u8f7d\u4f4d\u7f6e)<\/p>\n

\/home\/GeneFamily\/TOOLS\/hmmer\/binaries\/hmmsearch –cut_tc –domtblout gata.out \/gata.hmm Homo_sapiens.GRCh38.pep.all.fa<\/p>\n

\u6b64\u6b65\u4f1a\u751f\u6210\u521d\u6b65\u7684\u7ed3\u679cgata.out\u6587\u4ef6<\/p>\n

<\/p>\n

#step4 \u5bf9gata.out\u6587\u4ef6\u521d\u6b65\u8d28\u63a7\uff0c\u7b5b\u9009e\u503c\u5c0f\u4e8e1*10^-20\u7684\u7ed3\u679c<\/p>\n

grep -v “#” gata.out|awk ‘($7 + 0) < 1E-20’|cut -f1 -d ” “|sort -u > gata_id.txt<\/p>\n

#step5 \u5229\u7528Samtools\u8f6f\u4ef6\u628a\u7b5b\u9009\u540e\u7684\u86cb\u767d\u8d28\u5e8f\u5217\u6311\u51fa\u6765<\/p>\n

\u9996\u5148\u5229\u7528samtools\u8f6f\u4ef6\u5bf9pep\u6587\u4ef6\u751f\u6210\u7d22\u5f15\u6587\u4ef6<\/p>\n

\/home\/NGS\/tools\/samtools\/samtools faidx Homo_sapiens.GRCh38.pep.all.fa<\/p>\n

\u4f1a\u751f\u6210\u4e00\u4e2a\u540d\u4e3aHomo_sapiens.GRCh38.pep.all.fa.fai \u7684\u6587\u4ef6<\/p>\n

\u7136\u540e\u5229\u7528samtools\u8f6f\u4ef6\u6311\u51fa\u5e8f\u5217<\/p>\n

xargs \/home\/NGS\/tools\/samtools\/samtools faidx Homo_sapiens.GRCh38.pep.all.fa < gata_id.txt > gata_protein.fasta<\/p>\n

\u4f46\u662f\u751f\u6210\u7684fasta\u6587\u4ef6\u662f\u542b\u6709\u56de\u8f66\u7b26\u7684\u6240\u4ee5\u5229\u7528\u4e00\u4e2a\u89c1\u5f97perl\u547d\u4ee4\u6d88\u9664\u56de\u8f66\u7b26<\/p>\n

perl -pe ‘\/^>\/ ? print “\\n” : chomp’ gata_protein.fasta | tail -n+2 > gata_protein_1.fasta<\/p>\n

#step6 \u5229\u7528clustalX\u8f6f\u4ef6\u5bf9\u751f\u6210\u7684fasta\u6587\u4ef6\u591a\u91cd\u5e8f\u5217\u6bd4\u5bf9\uff0c\u7ed3\u679c\u4f1a\u751f\u6210gata_protein_1.aln\u6587\u4ef6<\/p>\n

#step7 \u5229\u7528hmmbuild\u547d\u4ee4\u5bf9\u7f6e\u4fe1\u5e8f\u5217\u8fdb\u884c\u9690\u9a6c\u5c14\u53ef\u592b\u6a21\u578b\u7684\u6784\u5efa\uff0c\u7cbe\u51c6\u9884\u6d4b\u6240\u6709\u57fa\u56e0\u5bb6\u65cf\u6210\u5458<\/p>\n

\/home\/GeneFamily\/TOOLS\/hmmer\/binaries\/hmmbuild gata_build.hmm gata_protein_1.aln<\/p>\n

\u4f1a\u751f\u6210\u4e00\u4e2agata_build.hmm\u6587\u4ef6\u5907\u7528<\/p>\n

\u7136\u540e\u5229\u7528hmmsearch\u547d\u4ee4\u7cbe\u51c6\u9884\u6d4b<\/p>\n

\/home\/GeneFamily\/TOOLS\/hmmer\/binaries\/hmmsearch –cut_tc –domtblout gata_second.out gata_build.hmm Homo_sapiens.GRCh38.pep.all.fa<\/p>\n

\u4f1a\u751f\u6210\u4e00\u4e2agata_second.out\u6587\u4ef6<\/p>\n

#step8 \u6700\u540e\u518d\u6b21\u5229\u7528e\u503c\u8fdb\u884c\u8fc7\u6ee4<\/p>\n

grep -v “#” gata_second.out|awk ‘($7 + 0) < 1E-3’|cut -f1 -d ” “|sort -u > gata_fina_id.txt<\/p>\n

xargs \/home\/NGS\/tools\/samtools\/samtools faidx Homo_sapiens.GRCh38.pep.all.fa < gata_fina_id.txt > gata_fina_protein.fasta<\/p>\n

\u4e8c\u3001\u5229\u7528PhyML\u5bf9\u4e0a\u8ff0\u5f97\u5230\u7684\u6210\u5458\u7684\u5e8f\u5217\u8fdb\u884c\u6781\u5927\u4f3c\u7136\u6811\u7684\u6784\u5efa<\/strong><\/p>\n

#step1 \u5229\u7528prottese\u8f6f\u4ef6\u9009\u62e9\u5efa\u6811\u7684\u6700\u4f73\u8fdb\u5316\u6a21\u578b<\/p>\n

java -jar prottest.jar -i gata_protein_1.phy -o gata_good_model.txt -S 1 -AIC -I -G -IG -F -ncat 8 -all<\/p>\n

\u5176\u4e2d-i\uff1a\u8f93\u5165\u6587\u4ef6\uff08.phy\u683c\u5f0f\uff09\uff0c-o\uff1a\u8f93\u5165\u7684\u6700\u4f73\u6a21\u578b\u7684\u7ed3\u679c\u6587\u4ef6<\/p>\n

-S\uff1a\u8fd0\u7b97\u7684\u7b56\u7565\uff0cfast\u4e3a0\uff0cslow\u4e3a1\uff0c\u4f46\u662fslow\u4f1a\u66f4\u7cbe\u51c6\u4e00\u4e9b<\/p>\n

-AIC\uff1a\u7528\u4e8e\u6392\u5e8f\u7684framework \u9664\u4e86AIC\u4e4b\u5916\u8fd8\u6709AICc BIC DT \u7b49\u7b49<\/p>\n

-G -I -IG -F:\u4e3a\u51e0\u79cd\u6784\u5efa\u6a21\u578b\u7684\u7b56\u7565\uff0c\u5728\u505amodel\u7684\u65f6\u5019\uff0c\u5168\u9009\u4e0a<\/p>\n

-ncat 8\u6307\u7684\u662f8\u4e2arate category\uff0c phyML\u5efa\u6811\u65f6\u4e5f\u4f1a\u8bbe\u7f6e\u8fd9\u4e2a\u53c2\u6570\uff0c\u5728\u4e00\u5b9a\u8303\u56f4\u5185\u8d8a\u5927\u8d8a\u597d\uff0c\u4f46\u662f\u4e0d\u80fd\u592a\u5927<\/p>\n

-all \u6c47\u603b\u5404\u4e2aframwork\u7684\u6392\u5e8f\u7ed3\u679c<\/p>\n

\u8fd9\u4e00\u6b65\u4f1a\u751f\u6210\u4e00\u4e2a.txt\u7684\u7ed3\u679c\u6587\u4ef6\uff0cdeltaAIC\u503c\u4e3a0\u6216\u8005\u6700\u5c0f\u7684\u65f6\u5019\uff0c\u8be5\u6a21\u578b\u662f\u6700\u4f73\u6a21\u578b\uff0c\u5982\u4e0b\uff1a<\/p>\n

***************************************************************************<\/p>\n

Best model according to AIC: JTT+I+G+F<\/p>\n

Confidence Interval: 100.0<\/p>\n

***************************************************************************<\/p>\n

Model deltaAIC AIC AICw -lnL<\/p>\n

—————————————————————————<\/p>\n

JTT+I+G+F 0.00 12690.92 1.00 6285.46<\/p>\n

VT+I+G+F 18.27 12709.19 0.00 6294.59<\/p>\n

JTT+G+F 30.07 12720.99 0.00 6301.50<\/p>\n

\u7136\u540e\u5728\u6587\u4ef6\u7684\u4e0a\u65b9\u627e\u5230\u8fd9\u4e2a\u6a21\u578b\u548c\u5b83\u7684\u6240\u6709\u53c2\u6570\u3002\u5982\u4e0b<\/p>\n

Model………………………….. : JTT+I+G+F<\/p>\n

Number of parameters…………… : 60 (21 + 39 branch length estimates)<\/p>\n

gamma shape (8 rate categories).. = 2.298<\/p>\n

proportion of invariable sites… = 0.139<\/p>\n

aminoacid frequencies………… = observed (see above)<\/p>\n

-lnL………………………….. = 6285.46<\/p>\n

(seconds))<\/p>\n

\u5176\u4e2dgamma shape (8 rate categories).. = 2.298<\/p>\n

proportion of invariable sites… = 0.139\u8fd9\u4e24\u4e2a\u53c2\u6570\u5728\u4e4b\u540e\u7684phyml\u8f6f\u4ef6\u5efa\u6811\u7684\u6784\u6210\u4e2d\u9700\u8981\u7528\u5230\u3002<\/p>\n

\u5230\u8fd9\u6700\u4f73\u6a21\u578b\u7684\u9009\u62e9\u5c31\u5b8c\u6210\u4e86\uff0c\u52a0\u4e0b\u6765\u5229\u7528PhyML\u8fdb\u884c\u6781\u5927\u4f3c\u7136\u6811\u7684\u6784\u5efa<\/p>\n

#step2 \u5229\u7528phyml\u6784\u5efa\u6781\u5927\u4f3c\u7136\u6811<\/p>\n

\u6b64\u6b65\u89c1\uff08PhyML\u5229\u7528\u6c28\u57fa\u9178\u5e8f\u5217\u5efa\u6811.pdf\uff09\u6587\u4ef6<\/p>\n

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