FTDNATiP, Y-Matches, setup

[JC399]

It would probably help if you were to clarify you mean by "differential", I think. But I'll try to explain it anyway.

Using more markers in a TMRCA calculation will change the TMRCA estimate produced by the calculation, even if there are no mutations in the additional markers tested.

And unless two different calculators use the same mutation rate estimate for the additional markers, each will change the TMRCA estimate by a different amount when the additional markers are added.

The TMRCA estimate is a non-linear function of the mutation rate and the number of mutations per marker. A change of zero is informative and impacts the estimate produced by the model described by Walsh.

The process of actually building a calculator is highly informative, and will allow you to see how the inputs interact. The whole excercise become much more intuitive once you expend the energy to understand it.

I think it's pretty clear we are talking about something altogether different. By differential I mean what's causing a difference in TMRCA time going from one individual to the next. Yes, the actual values are affected by the upper markers, but the difference between each individual is being caused by the lower markers because those are the ones that are different. If the lower markers were the same too there would be no difference. That's all I meant.

[JC399]

FTDNATiP has as inputs: 1) some algorithm for calculating genetic distance (that takes into account RecLOH events at the multi-copy markers); and 2) 38 mutation rate estimates (one each for the first 37 markers and a single estimate for the final panel).

The GD algorithm would be easiest to crack, I think, but in order to reverse engineer the FTDNATiP mutation rate estimates you would need access to at least to 39 haplotypes which varied from each other at exactly one marker each. Leaving aside the problem that these 39 haplotypes don't exist, you still have to hope that there is a single solution to the problem of trying to simultaneously solve for the 38 mutation rate estimates.

Good luck.

I really don't want to get into all that. I was planning on focusing more on r1b1 since it applies to me personally and there is more data on that than perhaps any of the others. If I can get closer to FTDNATiP than using the public calculators, I'll be very happy.