内容发布更新时间 : 2024/12/29 17:10:25星期一 下面是文章的全部内容请认真阅读。
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附录1.最大简约法分析批处理文件
1.
begin PAUP;
log file=hsearch1.log; set autoclose=yes;
set maxtrees=100 increase=auto;
hsearch start=stepwise addseq=random nreps=1000 randomize=addseq
rstatus=yes
hold=1
swap=tbr
nchuck=200 chuckscore=1;
savetrees file=hsearch1.all.tre brlens=yes; filter best=yes permdel=yes; savetrees file=hsearch1.best.tre; gettrees file=hsearch1.best.tre;
contree all/majrule=yes treefile=contree.tre; log stop; end; 2.
begin PAUP;
log file=hsearch1.log; set autoclose=yes;
set maxtrees=100 increase=auto;
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savereps=yes multrees=yes
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hsearch start=stepwise addseq=random nreps=1000 savereps=yes randomize=addseq rstatus=yes hold=1 swap=tbr multrees=yes; savetrees file=hsearch1.all.tre brlens=yes; filter best=yes permdel=yes; savetrees file=hsearch1.best.tre; gettrees file=hsearch1.best.tre;
contree all/majrule=yes treefile=contree.tre; log stop; end;
2的策略较好，是hsearch中首选，而如果此程序运算时间太长则用上面一个程序。
本实用方法只提供hsearch，而branch and bound和exhaustive方法省略。 附录1*
export format=nexus interleaved=no file=temp.txt （此为生成noninterleave文件命令）
附录 2. ILD分析
;
endblock;
charpartition dna=ITS:1-848,trnLF:849-3051; begin paup;
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set criterion=parsimony; log file=iscap.hom;
hompart part=dna nreps=100/addseq=random; hsearch swap=tbr; endblock;
附录 3. Bayes分析
1. 单一模型 begin mrbayes;
lset nst=6 rates=gamma;
mcmcp ngen=2000000 printfreq=1000 samplefreq=100 savebrlens=yes filename=P_combined; mcmc;
sumt filename=P_combined.t burnin=2000; end;
Begin mrbayes;
2. 多模型 begin mrbayes; charset its=1-622; charset trnlf=623-1696; charset matk=1697-3221;
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charset chs=3222-4406; charset psbm2trnd=4407-5506; charset psbm=5507-6279; charset gpd=6280-6972; charset LFY=6973-8426;
partition Names = 8: its, trnlf, matk, chs, psbm2trnd, psbm, gpd, LFY; end;
begin mrbayes;
[The following lines set up a model in which all four genes have their
unique GTR + gamma
+ propinv model] set partition=Names; prset ratepr=variable;
lset applyto=(1,2,3,4,5,6,7) nst=6;
lset applyto=(8) nst=2 rates=gamma;
unlink shape=(all) pinvar=(all);
end;
begin mrbayes;
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mcmcp ngen=100000 printfreq=1000 samplefreq=100 nchains=4 savebrlens=yes filename=solms8mys; mcmc;
sumt filename=solms8.t burnin=3000; end;
3. 带支长contree的运算batch begin mrbayes;
log start filename=cp.log;
mcmc filename=cp ngen=2000000 samplefreq=100; sump
burnin=5000
filename=cp
outputname=cp.sump;
sumt burnin=5000 filename=cp contype=allcompat; log stop; end;
附录4. bootstrap分析
begin paup;
log file=bootstrap.log;
set maxtrees=100 increase=auto; set criterion=parsimony; set root=outgroup;
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printtofile=yes