1  =============================================
2    Example: Microsatellite data set
3  =============================================
4  MIGRATION RATE AND POPULATION SIZE ESTIMATION
5  using Markov Chain Monte Carlo simulation
6  =============================================
7  Version 3.6.6
8
9  Program started at Tue Jan 20 15:37:10 2015
10         finished at Tue Jan 20 15:37:31 2015
11
12
13
14Options in use:
15---------------
16
17Analysis strategy is BAYESIAN INFERENCE
18
19Proposal distribution:
20Parameter group          Proposal type
21-----------------------  -------------------
22Population size (Theta)       Slice sampling
23Migration rate      (M)       Slice sampling
24
25
26Prior distribution (Proposal-delta will be tuned to acceptance frequence 0.440000):
27Parameter group          Prior type   Minimum    Mean(*)    Maximum    Delta
28-----------------------  ------------ ---------- ---------- ---------- ----------
29Population size (Theta)      Uniform  0.000000  10.000000  20.000000   2.000000
30Migration rate      (M)      Uniform  0.000000  10.000000  20.000000   2.000000
31
32
33
34Datatype: Microsatellite data [Brownian motion]
35Missing data is not included
36
37Inheritance scalers in use for Thetas (specified scalars=1)
381.00 1.00 1.00 1.00 1.00
391.00 1.00 1.00 1.00 1.00
40
41[Each Theta uses the (true) ineritance scalar of the first locus as a reference]
42
43
44Pseudo-random number generator: Mersenne-Twister
45Random number seed (from parmfile)            310705631
46
47Start parameters:
48   First genealogy was started using a UPGMA-tree
49   Theta values were generated  RANDOM start value from U(min,max)
50   M values were generated from the FST-calculation
51
52Migration model: Arbitrary migration matrix model
53[Legend: m = average (average over a group of Thetas or M]
54[s = symmetric M, S = symmetric 4Nm,
55 0 = zero, and not estimated,   ]
56[* = free to vary, Thetas are on diagonal]
57population     * 0
58population     * *
59
60
61
62Mutation rate is constant for all loci
63
64Markov chain settings:
65   Long chains (long-chains):                              1
66      Steps sampled (inc*samples*rep):                 10000
67      Steps recorded (sample*rep):                     10000
68   Combining over replicates:                              2
69   Static heating scheme
70      4 chains with  temperatures
71       1.00, 1.50, 3.00,1000000.00
72      Swapping interval is 1
73   Burn-in per replicate (samples*inc):                10000
74
75Print options:
76   Data file:                                    infile.msat
77   Output file (ASCII text):                   outfile-bayes
78   Output file (PDF):                      outfile-bayes.pdf
79   Posterior distribution:                         bayesfile
80   Print data:                                            No
81   Print genealogies:                                     No
82   Plot data: No
83
84Summary of data:
85Title:                      Example: Microsatellite data set
86Data file:                                       infile.msat
87Datatype:                                Microsatellite data
88[Data was used as repeat-length information]
89Number of loci:                                           10
90
91Population                   Locus   Gene copies
92                                     ---------------
93                                     data  (missing)
94----------------------------------------------------
95  1 population_number___0        1     50 (0)
96  1                              2     50 (0)
97  1                              3     50 (0)
98  1                              4     50 (0)
99  1                              5     50 (0)
100  1                              6     50 (0)
101  1                              7     50 (0)
102  1                              8     50 (0)
103  1                              9     50 (0)
104  1                             10     50 (0)
105  2 population_number___1        1     42 (0)
106  2                              2     42 (0)
107  2                              3     42 (0)
108  2                              4     42 (0)
109  2                              5     42 (0)
110  2                              6     42 (0)
111  2                              7     42 (0)
112  2                              8     42 (0)
113  2                              9     42 (0)
114  2                             10     42 (0)
115    Total of all populations     1     92 (0)
116                                 2     92 (0)
117                                 3     92 (0)
118                                 4     92 (0)
119                                 5     92 (0)
120                                 6     92 (0)
121                                 7     92 (0)
122                                 8     92 (0)
123                                 9     92 (0)
124                                10     92 (0)
125
126Allele frequency spectra
127========================
128
129Locus 1
130Allele      Pop1   Pop2   All
131--------------------------------
13216          0.220  0.167  0.196
13319          0.040  0.071  0.054
13418          0.060  0.119  0.087
13515          0.220  0.024  0.130
13621          0.020  0.167  0.087
13723          0.020  0.119  0.065
13817          0.280  0.095  0.196
13922          0.060  0.119  0.087
14025          0.060  0.024  0.043
14124          0.020    -    0.011
14226            -    0.024  0.011
14327            -    0.048  0.022
14429            -    0.024  0.011
145Alleles        10     12     13
146Samplesize     50     42     92
147H_exp       0.811  0.883  0.874
148
149Locus 2
150Allele      Pop1   Pop2   All
151--------------------------------
15216          0.520  0.571  0.543
15319          0.040    -    0.022
15418          0.220  0.119  0.174
15517          0.160  0.167  0.163
15615          0.020    -    0.011
15721          0.020  0.071  0.043
15820          0.020  0.024  0.022
15922            -    0.048  0.022
160Alleles         7      6      8
161Samplesize     50     42     92
162H_exp       0.653  0.624  0.644
163
164Locus 3
165Allele      Pop1   Pop2   All
166--------------------------------
16719          0.240  0.262  0.250
16820          0.280  0.476  0.370
16918          0.080  0.095  0.087
17021          0.280  0.119  0.207
17122          0.120  0.048  0.087
172Alleles         5      5      5
173Samplesize     50     42     92
174H_exp       0.765  0.679  0.743
175
176Locus 4
177Allele      Pop1   Pop2   All
178--------------------------------
17916          0.080  0.071  0.076
18024          0.180  0.024  0.109
18115          0.020  0.048  0.033
18225          0.160  0.167  0.163
18314          0.020  0.048  0.033
18419          0.100  0.143  0.120
18512          0.060    -    0.033
18620          0.080  0.190  0.130
18723          0.060  0.119  0.087
18828          0.020    -    0.011
18922          0.060  0.024  0.043
19021          0.160  0.119  0.141
19113            -    0.024  0.011
19226            -    0.024  0.011
193Alleles        12     12     14
194Samplesize     50     42     92
195H_exp       0.882  0.875  0.892
196
197Locus 5
198Allele      Pop1   Pop2   All
199--------------------------------
20020          0.400  0.524  0.457
20121          0.420  0.357  0.391
20219          0.180  0.119  0.152
203Alleles         3      3      3
204Samplesize     50     42     92
205H_exp       0.631  0.584  0.615
206
207Locus 6
208Allele      Pop1   Pop2   All
209--------------------------------
21019          0.060    -    0.033
21120          0.100  0.024  0.065
21218          0.300  0.214  0.261
21322          0.200  0.119  0.163
21421          0.120  0.476  0.283
21516          0.060    -    0.033
21624          0.160  0.048  0.109
21717            -    0.119  0.054
218Alleles         7      6      8
219Samplesize     50     42     92
220H_exp       0.813  0.696  0.804
221
222Locus 7
223Allele      Pop1   Pop2   All
224--------------------------------
22523          0.040  0.238  0.130
22620          0.660  0.143  0.424
22722          0.180  0.190  0.185
22821          0.100  0.333  0.207
22919          0.020  0.095  0.054
230Alleles         5      5      5
231Samplesize     50     42     92
232H_exp       0.520  0.766  0.724
233
234Locus 8
235Allele      Pop1   Pop2   All
236--------------------------------
23719          0.520  0.524  0.522
23817          0.040  0.048  0.043
23918          0.100  0.071  0.087
24020          0.140  0.190  0.163
24116          0.080    -    0.043
24222          0.100  0.048  0.076
24315          0.020  0.048  0.033
24423            -    0.071  0.033
245Alleles         7      7      8
246Samplesize     50     42     92
247H_exp       0.682  0.672  0.682
248
249Locus 9
250Allele      Pop1   Pop2   All
251--------------------------------
25224          0.080  0.024  0.054
25319          0.300  0.429  0.359
25420          0.300  0.167  0.239
25523          0.180  0.143  0.163
25622          0.080  0.024  0.054
25718          0.020  0.071  0.043
25821          0.040  0.095  0.065
25925            -    0.048  0.022
260Alleles         7      8      8
261Samplesize     50     42     92
262H_exp       0.773  0.751  0.775
263
264Locus 10
265Allele      Pop1   Pop2   All
266--------------------------------
26722          0.100  0.214  0.152
26820          0.440  0.214  0.337
26923          0.080  0.167  0.120
27024          0.020    -    0.011
27119          0.160  0.167  0.163
27221          0.060  0.048  0.054
27318          0.080    -    0.043
27415          0.020  0.071  0.043
27517          0.040  0.048  0.043
27625            -    0.071  0.033
277Alleles         9      8     10
278Samplesize     50     42     92
279H_exp       0.752  0.838  0.813
280
281Average expected heterozygosity
282Pop1   Pop2   All
283---------------------
2840.728  0.737  0.757
285
286
287
288
289Bayesian estimates
290==================
291
292Locus Parameter        2.5%      25.0%    mode     75.0%   97.5%     median   mean
293-----------------------------------------------------------------------------------
294    1  Theta_1         1.08000  1.36000  1.86000  2.36000  2.76000  3.02000  3.71518
295    1  Theta_2         0.68000  0.96000  1.46000  2.60000  6.52000  2.46000  3.00004
296    1  M_1->2             2.08     3.12     4.22     4.84     7.12     4.34     4.44
297    2  Theta_1         3.80000  4.76000  5.82000  6.56000  9.12000  6.06000  6.23930
298    2  Theta_2         1.92000  2.72000  3.74000  6.76000 15.64000  6.70000  7.90481
299    2  M_1->2             2.52     4.64     5.10     6.96     9.28     5.90     5.92
300    3  Theta_1         4.16000  6.68000  7.90000  9.24000 11.08000  7.90000  7.84903
301    3  Theta_2        10.36000 14.20000 15.86000 19.36000 20.00000 13.98000 12.94539
302    3  M_1->2             0.48     0.72     1.30     1.96     4.32     1.82     2.13
303    4  Theta_1         1.60000  1.96000  2.54000  3.08000  3.64000 15.62000 10.55422
304    4  Theta_2         1.60000  1.84000  3.10000  4.32000  5.12000  6.10000  9.17295
305    4  M_1->2             1.04     1.32     1.98     2.56     6.88     3.30     3.62
306    5  Theta_1         2.24000  2.52000  3.22000  4.12000  8.20000  4.22000  4.85088
307    5  Theta_2         2.48000  9.04000 10.14000 12.80000 15.36000 10.42000 10.58751
308    5  M_1->2             5.80     7.96     8.30     8.72    18.08    11.46    11.75
309    6  Theta_1         2.08000  2.68000  3.14000  3.80000  9.96000  4.78000  5.25820
310    6  Theta_2         0.00000  0.08000  0.54000  0.92000  1.08000  1.38000  1.98602
311    6  M_1->2             1.56     2.04     3.18     5.72    14.80     5.54     7.50
312    7  Theta_1         1.48000  2.20000  2.78000  3.20000  4.56000  2.90000  2.95964
313    7  Theta_2         2.24000  3.60000  5.82000  6.72000 13.44000  6.98000  7.44128
314    7  M_1->2             0.08     0.48     0.74     1.00     1.96     0.86     0.91
315    8  Theta_1         3.12000  4.16000  5.14000  7.04000  8.16000  8.46000  9.63487
316    8  Theta_2         0.72000  0.92000  1.66000  2.60000  3.16000  3.46000  6.61854
317    8  M_1->2             0.44     0.64     1.38     2.20     7.04     2.46     3.36
318    9  Theta_1         3.84000  4.16000  5.58000  6.72000 12.24000  6.86000  7.52431
319    9  Theta_2         1.64000  2.12000  3.02000  4.92000 13.16000  6.30000  6.80907
320    9  M_1->2             1.32     1.92     2.30     3.48     5.80     3.14     3.30
321   10  Theta_1         2.56000  2.80000  3.82000  5.16000  5.60000  7.42000  8.05189
322   10  Theta_2         5.24000  6.64000  7.38000  9.76000 15.16000  9.34000  9.72418
323   10  M_1->2             0.00     0.32     0.58     0.88     1.56     0.74     0.75
324  All  Theta_1         4.16000  4.60000  4.90000  5.20000  5.88000  5.02000  5.11582
325  All  Theta_2         1.76000  2.72000  3.02000  3.28000  4.24000  3.02000  3.04385
326  All  M_1->2             2.44     2.84     3.18     3.48     3.76     3.14     3.22
327-----------------------------------------------------------------------------------
328
329
330
331Log-Probability of the data given the model (marginal likelihood = log(P(D|thisModel))
332--------------------------------------------------------------------
333[Use this value for Bayes factor calculations:
334BF = Exp[log(P(D|thisModel) - log(P(D|otherModel)]
335shows the support for thisModel]
336
337
338
339Locus      Raw Thermodynamic score(1a)  Bezier approximated score(1b)     Harmonic mean(2)
340------------------------------------------------------------------------------------------
341      1             -16501.65                      -2750.99                 -62.75
342      2               -901.94                       -231.19                 -65.87
343      3               -443.23                       -172.83                 -98.74
344      4              -5182.96                       -949.44                -113.33
345      5               -658.82                       -180.93                 -54.92
346      6              -2602.87                       -513.16                 -53.67
347      7               -340.80                       -144.57                 -60.91
348      8              -3309.11                       -634.56                -102.97
349      9               -973.06                       -261.24                 -82.72
350     10              -1895.79                       -426.97                -101.19
351---------------------------------------------------------------------------------------
352  All               -32800.06                      -6255.75                -786.94
353[Scaling factor = 10.139731]
354MCMC run characteristics
355========================
356
357
358
359
360Acceptance ratios for all parameters and the genealogies
361---------------------------------------------------------------------
362
363Parameter           Accepted changes               Ratio
364Theta_1                  16446/16446             1.00000
365Theta_2                  16684/16684             1.00000
366M_1->2                   16656/16656             1.00000
367Genealogies              15970/50214             0.31804
368Autocorrelation and Effective sample size
369-------------------------------------------------------------------
370
371  Parameter         Autocorrelation(*)   Effective Sample size
372  ---------         ---------------      ---------------------
373  Theta_1                0.93347              3458.04
374  Theta_2                0.91976              4198.60
375  M_1->2                 0.91389              4517.46
376  Ln[Prob(D|P)]          0.99554               223.86
377  (*) averaged over loci.
378
379
380POTENTIAL PROBLEMS
381------------------------------------------------------------------------------------------
382This section reports potential problems with your run, but such reporting is often not
383very accurate. Whith many parameters in a multilocus analysis, it is very common that
384some parameters for some loci will not be very informative, triggering suggestions (for
385example to increase the prior range) that are not sensible. This suggestion tool will
386improve with time, therefore do not blindly follow its suggestions. If some parameters
387are flagged, inspect the tables carefully and judge wether an action is required. For
388example, if you run a Bayesian inference with sequence data, for macroscopic species
389there is rarely the need to increase the prior for Theta beyond 0.1; but if you use
390microsatellites it is rather common that your prior distribution for Theta should have a
391range from 0.0 to 100 or more. With many populations (>3) it is also very common that
392some migration routes are estimated poorly because the data contains little or no
393information for that route. Increasing the range will not help in such situations,
394reducing number of parameters may help in such situations.
395------------------------------------------------------------------------------------------
396Param 2 (Locus 3): Upper prior boundary seems too low!
397------------------------------------------------------------------------------------------
398