授業/H17/系統学特論/PAUPブロック

＜このページは未完成です＞ PAUP*をWindowsで使うときに便利なPAUPブロックまとめました。NEXUSファイルにコピーペーストして使ってください。

目次

Maximum Parsimony †

Parsimony 一般 †

Begin PAUP;
set autoclose=yes warnreset=no increase=auto; [This turns off all user-prompts.]
set criterion = parsimony; [This specifies the parsimony method]
HSearch ;[BandBやAllTreesが使える]
SaveTrees BrLens=yes File=MyFile.tre replace = yes;  [Saves the trees including branch lengths to the file named MyFile.tre]
End;

Heuristic Search †

begin PAUP;
log file=Hsearch.log;
set autoclose=yes;
hsearch start=stepwise addseq=random nreps=100 savereps=yes randomize=addseq rstatus=yes hold=1 swap=tbr multrees=yes;
savetrees file=Hsearch_all.tre;
filter best=yes permdel=yes;
savetrees file=Hsearch_best.tre;
log stop;
end;

Bootstrap Search by Heuristic †

begin PAUP;
log start = yes file = MyBoot.log replace = yes;
Bootstrap search = heuristic  nreps = 100 conLevel = 50;
saveTrees from = 1 to=1 file=MyBoot.tre saveBootP=nodeLabels maxDecimals=1 replace=yes;
log stop;
end;

　別にセーブしたTreeFileから読み込んで使うなら、このブロックと次のブロック。

begin paup;
gettrees allblocks=yes duptrees=keep storetreewts=yes mode=7 file=Bootstrap.tre;
end;

　次に

begin paup;
log file=bootstrapconsensus.log;
contree /majrule=yes strict=no le50=yes usetreewts=yes showtree=yes treefile=Final_bootstrap.tre grpfreq=yes;
log stop;
end;

ILD Test (Partition Homogeneity Test) †

Begin PAUP;
log file=ILDtest.log;
hompart partition=[name] nreps=100 / start=stepwise addseq=random nreps=10 savereps=no randomize=addseq rstatus=no hold=1 swap=tbr multrees=yes;
log stop;
end ;

Maximum Likelihood †

ML for Coding region †

begin paup;
set autoclose=yes warnreset=no increase=auto;
charset first = 1-.\3; [￥はPAUP上では＼（バックスラッシュ）]
charset second = 2-.\3;
charset third = 3-.\3;
charpartition by_codon = 1:first,2:second,3:third;
set criterion=parsimony; 
hsearch;
set criterion=likelihood;
lset nst=6 rmatrix=estimate basefreq=estimate rates=sitespec siterates=partition:by_codon;
lscores 1;
lset rmatrix=prev basefreq=prev rates = sitespec   siterates = prev;
  hsearch start=1;
savetrees brlens=yes maxDecimals=4 file=ML_out.tre replace=yes;
end;

ML for Coding region Modeltest用（但し簡便法） †

begin paup;
set autoclose=yes warnreset=no increase=auto;
charset first = 1-.\3; 
charset second = 2-.\3;
charset third = 3-.\3;
charpartition by_codon = 1:first,2:second,3:third;
set criterion=parsimony; 
hsearch;
set criterion=likelihood;
[ここにModeltestの結果のLsetから始まる行をはりつけるが、その行に
rates=sitespec siterates=partition:by_codonを追加する。Modeltestの
結果にratesとsiteratesがあれば削除。]
 hsearch start=1;
savetrees brlens=yes maxDecimals=4 file=ML_out.tre replace=yes;
end;

ML for Non Coding region †

begin paup;
set autoclose=yes warnreset=no increase=auto;
set criterion=parsimony; 
hsearch;
set criterion=likelihood;
lset nst=6 rmatrix=estimate basefreq=estimate rates=gamma shape = estimate;
lscores 1;
lset rmatrix=prev basefreq=prev rates = prev   shape = prev;
hsearch start=1;
savetrees brlens=yes maxDecimals=4 file=ML_out.tre replace=yes;
end;

ML for Non Coding region Modeltest 用 †

begin paup;
set autoclose=yes warnreset=no increase=auto;
set criterion=parsimony; 
hsearch;
set criterion=likelihood;
[ここにModeltestの結果のLsetから始まる行を挿入]
hsearch start=1;
savetrees brlens=yes maxDecimals=4 file=ML_out.tre replace=yes;
end;

NJ †

NJでBootstrap †

Begin PAUP;
log start = yes file = MyFile.log replace = yes;
set criterion=distance;
Bootstrap search = NJ  nreps = 100 conLevel = 50;
saveTrees from = 1 to=1 file=NJ_boot.tre saveBootP=nodeLabels maxDecimals=1 replace=yes;
end;