Issue with parameter estimation when more than 1 scenario present?

[mariaemilyd]

Hi,

There seems to be an issue with parameter estimation when more than one scenarios are compared. Parameter estimates from a model specified as "scenario 2" in the header file always result in some strange estimates outside the range of the priors. If I put the same evolutionary model under "scenario 1" in the header file in a different DIYABC-RF run, it produces normal parameter estimates.

I am estimating population sizes and divergence times. The issue seems to be with the divergence times only.

N.B I am sharing one set of model output. I have different runs for slightly different models and datasets as well, where I had the same issue, and could upload those for comparison if needed.

I could not attach the reftable.bin file as it was not a supported file type - I can email if needed? The scenario pictures have crossed lines because of the way the image was compiled in my browser (too narrow).

Thank you very much for your help,

Maria

diyabc_seed_init_call.log
first_records_of_the_reference_table_0.txt
headerRF.txt
r_tarandus_sval_model_4_genepop_new_2022_11_15.txt
reftable.log
statobsRF.txt
abcranger_call.log
diyabc_run_call.log

[fradav]

Hi Maria,

Which divergence time in the second scenario are you trying to infer ?

[mariaemilyd]

Hi,

I'm trying to estimate all 4 in scenario 2; t1, t2, t3, t4. In this case, I got:
t1 median = 936 ( 95% CI 347-1515.05)
t2 median = 5.76233e-07 (2.39614e-07-9.0605e-07)
t3 median = 10.3592 (1.60856-19.2461)
t4 median = 8035.76(3814.96-13584.1)

So t2 and t3 are strange.

In a different ABC run, I put the evo model (that is listed under scenario 2 in this DIYABC run) in scenario 1 in the header file. Then I got these parameter estimates:
t1 median = 1129 ( 95% CI 414-1529.91)
t2 median = 3140 (2888-3379)
t3 median = 6166.08 (3335-12122.9)
t4 median = 9419 (4429.93-13870)

And in that DIYABC run, the other scenario (which is scenario 1 in the current model, scenario 2 in the other model) has strange estimates for t5:
t5 median: 9.83701 (1.13867-19.1695)
t6 median: 4184.66 (1267-11174.6)
t7 median: 8821.6 (3124.2-13884.3)

Thanks

[fradav]

I am able to reproduce the bogus values for t2 in param. estim.
Investigating…

[mariaemilyd]

Hello, any luck looking into the cause of this? Any more files I can provide? Thanks!

[fradav]

Yes it has been pinpointed to an error from my part in indexing the mutational parameters (instead of t2 you were estimating μseq_1)
fixed release is coming.

[mariaemilyd]

Hi, that's great news! Thank you for looking into this so quickly. Do you have a rough idea of when the new release would come? Only because the models form part of my results for my PhD which is ending soon, and so rerunning the models with the new release would be much needed. Thanks!

[fradav]

This evening or tomorrow for the cli binaries, once I fix something stuck in the CI pipeline. For the windows gui release it will be a tad longer as I have to ask the diyabcGUI maintainer. What's your system?

[mariaemilyd]

Oh that's fast! I'm running windows gui unfortunately, but if it's within the timeframe of weeks and not months, it should be okay.

[fradav]

Latest release fixed (cli binary only). Thanks you anyway for reporting this bug and taking the time to get on us again, you were very constructive.

Btw, is your PhD in population genetics?

[mariaemilyd]

Thanks! When you find out when the GUI will be released, please let me know. Glad to hear it was helpful!

Yes, it's looking at the effect of postglacial climate changes on the population histories of two Arctic species, and how the genetic legacy from that may impact response to future climate changes.

[mariaemilyd]

Hi, just to let you know I have been using the command line diyabc RF and abcranger and they are working great, the time parameter estimation looks good. Quick question about estimating mutation rate parameters though - netiher MEANMU (as in the header file) or µseq_1 (as in the GUI) seem to be recongised as parameter names? Thanks!