Respectfully, I have analyzed two different molecular data and also the concatenated dataset in order to find the best K (optimum number of genetic groups) using the STRUCTURE HARVESTER (a web based program).
I upload the Result zip file generated from STRUCTURE into the STRUCTURE HARVESTER, and the out put was interesting! K was not the same for each marker and even the concatenated data.
I am really confused!
How I must explain? Which of them I can trust? Is sth wrong with the analyses in STRUCTURE. I did them as follow: The analysis with the admixture model and correlated allele frequency, was run with the length of 10000 burnin period and MCMC replications each set at 50000. We also set a K value ranging from 1 to 10 with five independent iterations.
In my eyes one of the K is more wise because it separate species groups, but the remaining were strange! How I can persuade myself to accept only two groups for very different species!
I will appreciate anyone who can help me.
Regards
Dear Atena,
I cannot see your results in your post.
I would say that your runs are a bit short in terms of number of generations. If you can provide the results and also explain what molecular markers maybe I can help.
Hi Rosalía Piñeiro
First of all thank you for the answer. They are IRAP, SSR and also the combination of IRAP+ SSR dataset. I tested more generations too, but the results were not changed.
Would you please let me know why the K is not the same in analyses?
Regards
Hi Rosalía Piñeiro
You cannot see the results, Because I did not post them here.
I have problem with K results.
For one genetic marker, it is 9 and with the other I received 2 using STRUCTURE HARVESTER.
I am looking forward to the reasons! Why they are not the same?
Best Regards
Dear Atena,
first of all, the reasoning might be simply because of the markers used. If you are running structure, this is basically a POPULATION GENETICS approach. Of couse, you can play around with diffferent combinations of admixture and no admixture (with the second option more close to "species-level" studies), but also correlated and uncorrelated allele frequencies are compensating for the first option in one or the other direction.
IRAP is not really a marker system following necessarily "mendelian segregation" and it is difficult to find any reasonable selection of priors. Wjhat is about the breeding system of your target species?
However, I would expect that the K=9 structure of data is simply a further splitting of the major K=2 cluster? If this is NOT the case, then your combimed data do not follow principles of population genetics - this means use other methods to analyse your data, e.g. simple PCO of unbiased/unconstraint measures of your raw data.
I hope this helps,
Marcus
@Prof. Dr. Marcus Koch
So many thanks for the perfect answer. You are completely right.
We are speaking about bands, and their population structures, not the sequences.
Once, I think it is better to obtain the concatenated data in genetic markers (e.g., SSR, AFLP, etc), and analyze the combined data, but I think it is not an efficient way to explore genetic diversity and population structure of studied species among and within populations.
Regards
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