Version 3.2.6 (13. October 2010)
Migrate estimates population parameters, effective population sizes and migration rates of n populations, using genetic data. It uses a coalescent theory approach taking into account history of mutations and uncertainty of the genealogy. The estimates of the parameter values are achieved by either a Maximum likelihood (ML-approach or Bayesian inference (BI)).
Syntax:
Ind1 02 @
is legal)
enzyme electrophoretic data or microsatellite data would look like this:
<Number of populations> <number of loci> {delimiter between alleles} [project title 0-79] <Number of individuals> <title for population 0-79> <Individual 1 10-10> <data> <Individual 2 10-10> <data> .... <Number of individuals> <title for population 0-79> <Individuum 1 10-10> <data> <Individuum 2 10-10> <data> ....
sequences or SNPs
<Number of populations> <number of loci> [project title 0-79] <number of sites for locus1> <number of sites for locus 2> ... <Number of individuals locus1> <#ind locus 2> ... <#ind loc n> <title for population 0-79> <Individuum 1 10-10> <data locus 1> <Individuum 2 10-10> <data locus 1> .... <Individuum 1 10-10> <data locus 2> <Individuum 2 10-10> <data locus 2> .... <Number of individuals> <#ind locus 2> ... <#ind loc n> <title for population 0-79> <Individuum 1 10-10> <data locus 1> <Individuum 2 10-10> <data locus 1> .... <Individuum 1 10-10> <data locus 2> <Individuum 2 10-10> <data locus 2> ....
<Number of populations> <number of loci> [project title 0-79] <number of sites for locus1> <number of sites for locus 2> ... <Number of individuals locus 1> <#ind locus 2> ... <#ind loc n> <title for population 0-79> <Individual 1 10-10> <data locus 1 part 1> <Individuum 2 10-10> <data locus 1 part 1> .... <data ind1 locus 1 part 2> <data ind2 locus 1 part 2> .... <Individual 1 10-10> <data locus 2> <Individual 2 10-10> <data locus 2> .... <data ind1 locus 2 part 2> <data ind2 locus 2 part 2> ....
SNPs in HapMap format:
<Number of populations> <number of loci> [project title 0-79] <Any Number> <title for population 0-79> <Position on chromosome locus1> <TAB><allele><TAB><number><TAB><allele><TAB><number><TAB><total> <Position on chromosome locus2> <TAB><allele><TAB><number><TAB><allele><TAB><number><TAB><total> .... <Any Number> <title for population 0-79> <Position on chromosome locus1> <TAB><allele><TAB><number><TAB><allele><TAB><number><TAB><total> <Position on chromosome locus2> <TAB><allele><TAB><number><TAB><allele><TAB><number><TAB><total> ....
2 11 Migration rates between two Turkish frog populations 3 Akcapinar (between Marmaris and Adana) PB1058 ee bb ab bb bb aa aa bb ?? cc aa PB1059 ee bb ab bb bb aa aa bb bb cc aa PB1060 ee bb b? bb ab aa aa bb bb cc aa 2 Ezine (between Selcuk and Dardanelles) PB16843 ee bb ab bb aa aa aa cc bb cc aa PB16844 ee bb bb bb ab aa aa cc bb cc aa
/
as separator: 2 11 / Migration rates between two Turkish frog populations 3 Akcapinar (between Marmaris and Adana) PB1058 e/e b/b a/b b/b b/b a/a a/a b/b ?/? c/c Rs/Rf PB1059 e/e b/b a/b b/b b/b a/a a/a b/b b/b c/c Rs/Rs PB1060 e/e b/b b/? b/b a/b a/a a/a b/b b/b c/c Rs/Rs 2 Ezine (between Selcuk and Dardanelles) PB16843 e/e b/b a/b b/b a/a a/a a/a c/c b/b c/c Rf/Rf PB16844 e/e b/b b/b b/b a/b a/a a/a c/c b/b c/c Rf/Rs
2 3 . Rana lessonae: Seeruecken versus Tal 2 Riedtli near Guendelhart-Hoerhausen 0 42.45 37.31 18.18 0 42.45 37.33 18.16 4 Tal near Steckborn 1 43.46 33.37 18.18 1 44.46 33.35 19.18 1 44.46 35.? 18.18 1 43.42 35.31 20.18
#M
2 3 . Rana lessonae: Seeruecken versus Tal #M 2 2 2 2 Riedtli near Guendelhart-Hoerhausen 0 25.27 137.131 218.218 0 27.27 218.216 2 Tal near Steckborn 1 23.25 135.? 218.218 1 23.23 135.131 220.218
Symbol | Meaning |
---|---|
A | Adenine |
G | Guanine |
C | Cytosine |
T | Thymine |
U | Uracil |
Y | pYrimidine (C or T) |
R | puRine (A or G) |
W | ”Weak” (A or T) |
S | ”Strong” (C or G) |
K | ”Keto” (T or G) |
M | ”aMino” (C or A) |
B | not A (C or G or T) |
D | not C (A or G or T) |
H | not G (A or C or T) |
V | not T (A or C or G) |
X,N,? | unknown (A or C or G or T) |
O | deletion |
- | deletion |
examples:
2 1 Make believe data set using simulated data (1 locus) 50 3 Tallahassee (Mars) Peter ACACCCAACACGGCCCGCGGACAGGGGCTCGAGGGATCACTGACTGGCAC Donald ACACAAAACACGGCCCGCGGACAGGGGCTCGAGGGGTCACTGAGTGGCAC Christian ATACCCAGCACGGCCGGCGGACAGGGGCTCGAGGGAGCACTGAGTGGAAC 3 St. Marks Lucrezia ACACCCAACACGGCCCGCGGACAGGGGCTCGAGGGATCACTGACTGGCAC Isabel ACACAAAACACGGCCCGCGGACAGGGGCTCGAGGGGTCACTGAGTGGCAC Yasmine ATACCCAGCACGGCCGGCGGACAGGGGCTCGAGGGAGCACTGAGTGGAAC
2 2 Make believe data set using simulated data (2 loci) 50 46 3 3 pop1 eis ACACCCAACACGGCCCGCGGACAGGGGCTCGAGGGATCACTGACTGGCAC zwo ACACAAAACACGGCCCGCGGACAGGGGCTCGAGGGGTCACTGAGTGGCAC drue ATACCCAGCACGGCCGGCGGACAGGGGCTCGAGGGAGCACTGAGTGGAAC eis ACGCGGCGCGCGAACGAAGACCAAATCTTCTTGATCCCCAAGTGTC zwo ACGCGGCGCGAGAACGAAGACCAAATCTTCTTGATCCCCAAGTGTC drue ACGCGGCGCGAGAACGAAGACCAAATCTTCTTGATCCCCAAGTGTC 2 pop2 vier CAGCGCGCGTATCGCCCCATGTGGTTCGGCCAAAGAATGGTAGAGCGGAG fuef CAGCGCGAGTCTCGCCCCATGGGGTTAGGCCAAATAATGTTAGAGCGGCA vier TCGACTAGATCTGCAGCACATACGAGGGTCATGCGTCCCAGATGTG fuefLoc2 TCGACTAGATATGCAGCAAATACGAGGGGCATGCGTCCCAGATGTG
2 2 Make believe data set using simulated data (2 loci, interleaved) 50 46 3 2 pop1 eis ACACCCAACACGGCCCGCGGACA zwo ACACAAAACACGGCCCGCGGACA drue ATACCCAGCACGGCCGGCGGACA GGGGCTCGAGGGATCACTGACTGGCAC GGGGCTCGAGGGGTCACTGAGTGGCAC GGGGCTCGAGGGAGCACTGAGTGGAAC eis ACGCGGCGCGCGAACGAAGACCA zwo ACGCGGCGCGAGAACGAAGACCA AATCTTCTTGATCCCCAAGTGTC AATCTTCTTGATCCCCAAGTGTC 2 2 pop2 vier CAGCGCGCGTATCGCCCCATGTGGTTCGGCCAAAGAATG fuef CAGCGCGAGTCTCGCCCCATGGGGTTAGGCCAAATAATG GTAGAGCGGAG TTAGAGCGGCA TCGACTAGATCTG CAGCACATAC TCGACTAGATATG CAGCAAATAC GAGGGTCATGCGTCCCAGATGTG GAGGGGCATGCGTCCCAGATGTG
N
: nucleotide format N 2 2 Make believe data set using simulated data (2 population and 2 loci) 1 4 3 3 pop1 ind1 A ind2 A ind3 A ind1 ACAC ind2 ACAC ind3 ACGC 2 pop2 ind4 C ind5 C ind4 TGGA ind5 TCGA
H
: HapMap format # using the HapMap data format, but does produce the same result (yet) as the dataset above H 2 2 Make believe data set using simulated data (2 population and 2 loci) 3 pop1 1 A 3 C 0 3 1000 A 3 T 0 3 1010 C 3 G 0 3 1011 A 2 G 1 3 1015 C 3 A 0 3 2 pop2 1 A 0 C 2 2 1000 A 0 T 2 2 1010 C 1 G 1 2 1011 A 0 G 2 2 1015 C 0 A 2 2
Beerli, P. (2009) How to use migrate or why are markov chain monte carlo programs dicult to use? In G. Bertorelle, M. W. Bruford, H. C. Haue, A. Rizzoli, and C. Vernesi, editors, Population Genetics for Animal Conservation, volume 17 of Conservation Biology, pages 42-79. Cambridge University Press, Cambridge UK, 2009.