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MIGRATE(1)		    General Commands Manual		    MIGRATE(1)

NAME
       MIGRATE - estimate population parameters: migration rate	and population
       size

SYNOPSIS
       migrate-n

DESCRIPTION
       Migrate	estimates population parameters	(effective population size and
       migration rates)	 using	genetic	 data  (Electrophoretic	 markers,  mi-
       crosatellite markers, sequence data, and	single nucleotide polymorphism
       data).  It  is a	maximum	likelihood estimator or	Bayesian estimator and
       uses a coalescent theory	approach taking	into account history of	 muta-
       tions and uncertainty of	the genealogy.

       or   get	  a  copy  of  the  manual  in	PDF  format  from  http://pop-
       gen.scs.fsu.edu

OPTIONS
       there are no options on the commandline,	but you	can  specify  the  op-
       tions in	a parmfile or in the menu

PARMFILE OPTIONS
       The parmfile options are	split into Datatype, Input/Output, Start para-
       meters, Search strategy

DATATYPE
       datatype=<Allele	| Microsatellites | Brownian | Sequences | Nucleotide-
       polymorphisms | Panel-SNP | Genealogies >
	      specifies	 the  datatype	used for the analyses, needless	to say
	      that if you have the wrong data for the chosen type the  program
	      will  crash.   Allele: infinite allele model, suitable for elec-
	      trophoretic markers, perhaps the	"best"	guess  for  codominant
	      markers of which we do not know the mutation model.  Microsatel-
	      lite:  a	simple	electrophoretic	 ladder	 model is used for the
	      change along the branches	in genealogy.	Brownian:  a  Brownian
	      motion  approximation  to	 the  stepwise	mutation model for mi-
	      crosatellites us used (this is MUCH faster than exact model, but
	      is not a good approximation if population	sizes are  small  (say
	      below 10).  Sequences: Data are DNA or RNA sequences and the mu-
	      tation  model used is F84, first used by Felsenstein 1984	(actu-
	      ally the same as in dnaml	(Phylip	version	3.5), a	description of
	      this model can be	found in Swofford et  al.  1996.   Nucleotide-
	      polymorphism:  [SNP]  the	 data likelihood is corrected for sam-
	      pling only variable sites. We assume that	the data was  used  to
	      find  the	 SNP.  Panel-SNP: the data likelihood is corrected for
	      using a panel of SNP sites, that were polymorphic. The panel has
	      to be population 1.  Genealogies:	Reads the sumfile of a	previ-
	      ous  run,	with this options the genealogy	sampling step will not
	      be done and the genealogies provided in  the  sumfile  are  ana-
	      lyzed. This datatype makes it easy to rerun the program for dif-
	      ferent  likelihood ratio test or different settings for the pro-
	      file likelihood printouts.

Sequence data specific options
       freq-from-data=<	Yes | No:freqA freqG freqC freqT>

       ttratio=< r1 r2 .....>

       interleaved=<Yes	| No >

       categories=<Yes | No>
	      If you specify Yes you need a file named catfile
	       in  the	same  directory	 with  the  following  Syntax:	  num-
	      ber_of_categories	 cat1 cat2 cat3	.. categorylabel_for_each_site
	      for each locus, a	# in the first column can be used to  start  a
	      comment-line.  Example is	for a data set with 2 loci and 20 base
	      pairs each
		 # Example catfile for two loci
		 # in migrate you can use # as comments
		 2 1 10		 11111111112222222222
		 5 0.1 2 5 23 3	11111122223333445555

       rates=< n : r1 r2 r3 ..rn>

       prob-rates=< n :	p1 p2 p3 ... pn>

       autocorrelation=<Yes:value | No>

       weights=<Yes | No>
	      If  you  specify Yes you need a file weightfile with weights for
	      each site, the weights can be the	following numbers 0-9 and let-
	      ters A-Z,	so you have 35 possible	weights	available.
		   # Example weightfile	for two	loci
		   11111111112222222222
		   1111112222AAAA445XXXX5

       distfile=<Yes | No>
	      You can supply a distance	file for each locus (using PHYLIP syn-
	      tax).  The sequence of indiviudals must be same as  in  the  in-
	      file.  This option appears in the	menu when you choose

	      0	Start genealogy	is estimated using a UPGMA topology

	      The  distance  file  is then used	to create an UPGMA tree	with a
	      minimal number of	migration events. For large trees this is  op-
	      tions help to get	better starting	trees than the automatic tree
		   generation  which  uses  a  rather unsophisticated distance
	      method (differences).

       usertree=<Yes | No>
	      If you specify Yes you need a file intree. In this file you have
	      starting trees for each locus. BUT these trees need to have  mi-
	      gration events in	them!

Microsatellite data
       micro-threshold=value
	      specifies	the window in which probabilities of change are	calcu-
	      lated  if	 we have allele	34 then	only probabilities of a	change
	      from 34 to 35-44 and 24-34 are considered, the higher this value
	      is the longer you	wait for your
		    result, choosing it	too small will produce wrong  results.
	      Default is micro-threshold=10

Electrophoretic	data
       No special variables.

Nucleotide polymorphism
       Similar to sequence data.

INPUT/OUTPUT
       infile=filename
	      Default is infile

       random-seed=<Auto | Noauto | Own:seedvalue>
	      The  random  number seed guarantees that you can reproduce a run
	      exactly.	Good random number seeds are (values * 4) + 1.	If you
	      do not specify the random	number seed ( seed=Auto	) the  program
	      will  use	the system clock. With seed=Noauto the program expects
	      to find a	file named seedfile with the random number seed.  With
	      random-seed=Own:seedvalue	 you can specify the seed value	in the
	      parmfile (or in the menu).

       title=titletext

       progress=<Yes|No|Verbose>
	      The default is progress=Yes

       outfile=filename
	      The default is obviously outfile=outfile

       print-data=<Yes|No>
	      Print the	data in	the outfile. Default is	print-data=No.

       print-fst=<Yes|No>
	      Print a table of an FST  estimate	 for  comparison  (Beerli  and
	      Felsenstein 1999,	Beerli 1998) [not recommended].

       plot=<No	| Yes>[:<Outfile|Both>[:<std|log>:{mig-axis-start,mig-axis-
       end,theta-axis-start,theta-axis-end}<:printpos<M	| Nm>>]]
	      If  plot=No  then	no plot	of the parameter space is shown	in the
	      outfile, if Yes then you can specify whether you	want  to  have
	      the  accurate  numbers  in  a  separate  file ( mathfile ) using
	      printpos
	       "pixel" in each direction,or only the  ASCII-graphics  plot  in
	      the  outfile.   The last option (	M or N )let you	define whether
	      you want the plot	in M=m/mu or (default) 4Nm units.  Default  is
	      plot=Yes:Outfile.	  Example  of  a  more	complicated statement:
	      plot=Yes:Both:std:0,10,0,0.025:100N For syntax in	 mathfile  see
	      documentation

       profile=<No|Yes<:<Fast|Percentile|Spline|Discrete|Quick >><:M | Nm >
		   Print  profile  likelihood.	See  section  Likelihood ratio
	      tests and	profile	likelihood. Default
		   is profile=Yes:Fast:N.

       l-ratio=<None | <Mean|Loci>:testparam> (N-POP)
		    Likelihood ratio tests. See	section	Likelihood ratio tests
	      and profile likelihood. Default is l-ratio=None.

       print-trees=<All	| None | Last |	Best>
	      Default is print-trees=None

       mathfile=filename

       sumfile=<No | Yes | Yes:filename	>
	      Intermediate results of the genealogy sampling process are  save
	      into  a file named sumfile or into the file for that you specify
	      the filename.  You can use this sumfile to rerun the program for
	      further analysis,	 e.g.  calculating likelihood ratios  or  pro-
	      file likelihoods,	 see datatype=Genealogy.

START VALUES FOR THE PARAMETERS
       theta=<Fst | Own:{value1,value2 ,...}>
	      With  Fst	 the programs tries to use an FST  based measure (May-
	      nard Smith 1970, Nei and Feldman 1972) Own:  {  value1,  value2,
	      ... }
	       defines arbitrary start values.

       migration=<Fst|Own:Migration matrix > (N-POP)
	      The  migration  matrix  is a n by	n table	with - on the diagonal
	      and can look like	this for four  populations  migration=OWN:{  -
	      1.0  1.1 1.2 0.9 - 0.8 0.7 2.1 2.2 - 2.3 1.4 1.5 1.6 - } or like
	      this
		  migration=OWN:{ -    1.0 1.1 1.2
				  0.9 -	   0.8 0.7
				  2.1 2.2 -    2.3
				  1.4 1.5 1.6 -	   }

       mutation=<Gamma | NoGamma>
	      The default is mutation=Nogamma

       fst-type=<Theta | Migration >

       custom-migration=< NONE|migration - matrix >
	      The migration matrix contains the	migration rates	from j to i on
	      row i, and the are on the	diagonal.  The	migration  matrix  can
	      consist of connections that are *: no restriction

	      0: not estimated

	      m: mean value of either 4Nm or M.

	      s: symmetric migration [only for M]

	      c: constant value	(together with migration=OWN.. or theta=OWN..)

	      The  values  can	be spaced by blanks, newlines.	A few examples
	      for 4 populations:

	      Full model: custom-migration={**** **** **** ****}

	      N-island model: custom-migration={m m m m	mm mm m	mmm mmmm}

	      Stepping Stone  model:  with  symmetric  migrations,  and	 unre-
	      stricted	estimates: custom-migration={*s00 s*s0 0s*s 00s*}

	      Source-Sink: (the	first population is the	source): custom-migra-
	      tion={*000**000**0*000}

SEARCH STRATEGY
       Please  read  the  documentation	,these settings	are important and will
       influence the accuracy of your results.

       short-chains=value
	      Default is 10.

       short-inc=value
	      Default is 20.

       short-sample=value
	      Default is 500.

       long-chains=value
	      Default is 2.

       long-inc=value
	      Default is 20.

       long-sample=value
	      Default is 5000.

       burn-in=value
	      Default is 10000.

       replicate=<NO | YES<:LONGCHAINS | number>>

       heating=<NO | YES<:{1,1.1,1.2,1.3}>>

       Obscure options
	      see documentation

BUGS
       This man	page is	not up to date and misses the Bayesian inference  sec-
       tion, but see documentation.

MAIN DISTRIBUTION WEBSITE
       http://popgen.csit.fsu.edu

SEE ALSO
       coalesce,  fluctuate,  recombine,  lamarc  (the program)	available from
       http://evolution.gs.washington.edu/lamarc.html

AUTHOR
       Peter Beerli <beerli@csit.fsu.edu>

       [if you use this	man page, please let me	know]

4.2 Berkeley Distribution	 July 20 2006			    MIGRATE(1)

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