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Author Topic: KenN's Gen111T Generation Age Calculator  (Read 3447 times)
Mark Jost
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« Reply #25 on: October 27, 2012, 12:11:33 PM »

So you think that I am not capable and that you are more intelligent.


The fact is that the Native Americans ancestors arrived in America 12000 ybp. I dont need a calculator to work that one out.

Run some Native American haplotypes through your calculator and if the TMRCA is not 12,000 ybp then bin it.


I didnt think you would try.

MJost


Oh, no that isn't it at all and I did not state those things you suggest I said or ever inferred. It appears your are using obverse forms for a reply.

My previous statement to you was pointing out that you seem to wish others to prove your theories and not attempt it yourself. You wanted me to test your hypothesis concerning NA's, and I then suggested you do it yourself using my version of the TMRCA estimator and exclude any STR you felt was incorrectly used.

Your statements of various ages of various Haplogroups are, just that, statements that are not accomplied by who, what where and how this data results, you espouse, comes from.

All I really said to you is 'Prove it'.

MJost
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148326
Pos: Z245 L459 L21 DF13**
Neg: DF23 L513 L96 L144 Z255 Z253 DF21 DF41 (Z254 P66 P314.2 M37 M222  L563 L526 L226 L195 L193 L192.1 L159.2 L130 DF63 DF5 DF49)
WTYNeg: L555 L371 (L9/L10 L370 L302/L319.1 L554 L564 L577 P69 L626 L627 L643 L679)
stoneman
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« Reply #26 on: October 27, 2012, 02:25:47 PM »

Dr Alice Roberts says that the ancestors of the American Indians arrived 13500 ybp.If your calculator works then you can check it out.



So you think that I am not capable and that you are more intelligent.


The fact is that the Native Americans ancestors arrived in America 12000 ybp. I dont need a calculator to work that one out.

Run some Native American haplotypes through your calculator and if the TMRCA is not 12,000 ybp then bin it.


I didnt think you would try.

MJost


Oh, no that isn't it at all and I did not state those things you suggest I said or ever inferred. It appears your are using obverse forms for a reply.

My previous statement to you was pointing out that you seem to wish others to prove your theories and not attempt it yourself. You wanted me to test your hypothesis concerning NA's, and I then suggested you do it yourself using my version of the TMRCA estimator and exclude any STR you felt was incorrectly used.

Your statements of various ages of various Haplogroups are, just that, statements that are not accomplied by who, what where and how this data results, you espouse, comes from.

All I really said to you is 'Prove it'.

MJost
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Mark Jost
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« Reply #27 on: October 27, 2012, 04:38:45 PM »

ok....
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148326
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Neg: DF23 L513 L96 L144 Z255 Z253 DF21 DF41 (Z254 P66 P314.2 M37 M222  L563 L526 L226 L195 L193 L192.1 L159.2 L130 DF63 DF5 DF49)
WTYNeg: L555 L371 (L9/L10 L370 L302/L319.1 L554 L564 L577 P69 L626 L627 L643 L679)
Mark Jost
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« Reply #28 on: November 04, 2012, 09:22:44 PM »

My TMRCA Gen111T Age Estimator has been updated to V1.6
In this version I created Macro buttons to run calculations with or without the 17 Multi-copy markers.
 
https://docs.google.com/file/d/0By9Y3jb2fORNX2FjVV85bmVtWWs/edit
 
I loaded the V1.6 with the last dataset of 6200 L21 67 markers into the TMRCA estimator.

https://docs.google.com/open?id=0By9Y3jb2fORNSU9Lbi1rYXl4NUU
 
MJost
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148326
Pos: Z245 L459 L21 DF13**
Neg: DF23 L513 L96 L144 Z255 Z253 DF21 DF41 (Z254 P66 P314.2 M37 M222  L563 L526 L226 L195 L193 L192.1 L159.2 L130 DF63 DF5 DF49)
WTYNeg: L555 L371 (L9/L10 L370 L302/L319.1 L554 L564 L577 P69 L626 L627 L643 L679)
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« Reply #29 on: November 05, 2012, 01:22:08 PM »

My TMRCA Gen111T Age Estimator has been updated to V1.6
In this version I created Macro buttons to run calculations with or without the 17 Multi-copy markers.
 
https://docs.google.com/file/d/0By9Y3jb2fORNX2FjVV85bmVtWWs/edit
 
I loaded the V1.6 with the last dataset of 6200 L21 67 markers into the TMRCA estimator.

https://docs.google.com/open?id=0By9Y3jb2fORNSU9Lbi1rYXl4NUU
 
MJost

Mark,

You need to check your mutation rates m(i) in line 14 of the calculations sheet. It looks like you have pasted them wrongly, duplicating some values and omitting others. You can see by cross-checking with lines 24 and 25 that the values are nonesense.
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Mark Jost
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« Reply #30 on: November 05, 2012, 02:28:46 PM »

Thanks for the catch. I caught it too. I just uploaded fixed copies using the correct Marko Rates... I had several older spreadsheets open so I must have copied the wrong rates when I was testing.... dag nabbit.

Version 1.7 is the corrected spreadsheets.

https://docs.google.com/file/d/0By9Y3jb2fORNX2FjVV85bmVtWWs/edit
 
L21 loaded.
https://docs.google.com/open?id=0By9Y3jb2fORNSU9Lbi1rYXl4NUU
 
MJost
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148326
Pos: Z245 L459 L21 DF13**
Neg: DF23 L513 L96 L144 Z255 Z253 DF21 DF41 (Z254 P66 P314.2 M37 M222  L563 L526 L226 L195 L193 L192.1 L159.2 L130 DF63 DF5 DF49)
WTYNeg: L555 L371 (L9/L10 L370 L302/L319.1 L554 L564 L577 P69 L626 L627 L643 L679)
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« Reply #31 on: November 06, 2012, 02:32:27 PM »

Thanks for the catch. I caught it too. I just uploaded fixed copies using the correct Marko Rates... I had several older spreadsheets open so I must have copied the wrong rates when I was testing.... dag nabbit.

Version 1.7 is the corrected spreadsheets.

https://docs.google.com/file/d/0By9Y3jb2fORNX2FjVV85bmVtWWs/edit
 
L21 loaded.
https://docs.google.com/open?id=0By9Y3jb2fORNSU9Lbi1rYXl4NU   
 
MJost

Mark,

In your version of the generation calculator, you have dispensed with Ken N's method of calculating the value of the variance of each individual allele in favour of the EXCEL function VAR. Use of the EXCEL function may simplify your calculation but is fudamentally different to Ken's method and will usually produces a different result.

Ken's Model measures variance in relation to the haplogroup Modal using the MODE function which assigns to the cell the value with the highest frequency of the allele.

This is logical since the Modal is the ''assumed'' ancestral value for the haplogroup from which mutations have assumed to have occured. It is also an integer and mutations occur in integer steps from the Modal.

The EXCEL function VAR on the other hand measures variance from the AVERAGE value of the Haplogroup allele values. The average value will normaly be a none-integer number, different to the Modal, particularly when the mutations are none-symetric about the Modal in which case the difference may be significant.

The way that the Variance function works is likely to result in your Model's final generation count being under-estimated compared to Ken's Model.   
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Mark Jost
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« Reply #32 on: November 06, 2012, 06:48:36 PM »

I have to make mention that the Modal vs Mean, in most compared sets of Hts are identical but I notice that once in a while on one or two STRs this might not be the case. Check Rows 43 to 50 in the CalcGen111T worksheet for the 'Diff' results in row 47 & 48 after you filter one subclade.

Ken also mentioned that the ages appear younger with my mod and here is what I explained how it was done.

In Ken's posted Gen111T version, I ran the same set of 401 haplotypes into both clades (A and B) and in my modified version, removing the extra Multicopy's YCA, 395 and 413 in both versions. I changed DYS389ii to ii-i and used Marko's 389ii-i mutation rate.
 
I get these results.

Ken's Gen111T
GA and GB coal= 113.6
GA and GB = 122.3

Intraclade Results for MJost Mod
GA and GB coal= 113.6
GA and GB = 113.9

Interclade results for Ken's Gen111T:
GAB= 119.4   
 
Interclade results forMJost Mod using Pooled SD:
GAB= 113.8

I used Excel VarP (Whole Population) Variance result matched Ken's Coalescence variance calculation exactly. The use of Excel's Var function is used for a true variance-based TMRCA estimates using a sample population for a set of haplotype.

Interclade variance between two clades which are in the same clade haplogroup on the Tree.

I am combining the two clades (A and B) standard deviations which is valid when the mean of the two samples is roughly the same. The pooled variance is the variance between the samples added to the variance within the samples.

If the size, mean, and standard deviation of two overlapping samples are known for the samples as well as their intersection, then the standard deviation of the aggregated sample can still be calculated.

Pooling the two clades Standard deviation and then calculating the true variance from the Pooled SD is the true Interclade TMRCA.

Using VarP and Var calculates a Mean, the sum of a variables values divided by the total number of values, variance based TRMCA. Modal's may not represent the correct answer either.

And remember I am not a math guy. I am just using basic statistics on numbers.


MJost


Mark,

In your version of the generation calculator, you have dispensed with Ken N's method of calculating the value of the variance of each individual allele in favour of the EXCEL function VAR. Use of the EXCEL function may simplify your calculation but is fudamentally different to Ken's method and will usually produces a different result.

Ken's Model measures variance in relation to the haplogroup Modal using the MODE function which assigns to the cell the value with the highest frequency of the allele.

This is logical since the Modal is the ''assumed'' ancestral value for the haplogroup from which mutations have assumed to have occured. It is also an integer and mutations occur in integer steps from the Modal.

The EXCEL function VAR on the other hand measures variance from the AVERAGE value of the Haplogroup allele values. The average value will normaly be a none-integer number, different to the Modal, particularly when the mutations are none-symetric about the Modal in which case the difference may be significant.

The way that the Variance function works is likely to result in your Model's final generation count being under-estimated compared to Ken's Model.   
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148326
Pos: Z245 L459 L21 DF13**
Neg: DF23 L513 L96 L144 Z255 Z253 DF21 DF41 (Z254 P66 P314.2 M37 M222  L563 L526 L226 L195 L193 L192.1 L159.2 L130 DF63 DF5 DF49)
WTYNeg: L555 L371 (L9/L10 L370 L302/L319.1 L554 L564 L577 P69 L626 L627 L643 L679)
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« Reply #33 on: November 08, 2012, 05:57:46 AM »

I have to make mention that the Modal vs Mean, in most compared sets of Hts are identical but I notice that once in a while on one or two STRs this might not be the case. Check Rows 43 to 50 in the CalcGen111T worksheet for the 'Diff' results in row 47 & 48 after you filter one subclade.


Using VarP and Var calculates a Mean, the sum of a variables values divided by the total number of values, variance based TRMCA. Modal's may not represent the correct answer either.

And remember I am not a math guy. I am just using basic statistics on numbers.


MJost


Modal and Mean are most certainly not the same, unless your filtering has modified their values, and the differences are significant in a number of cases. If you add a line in your calculations using the AVERAGE function on your Haplogroup you will see the difference. In any event, if you are measuring variance from the Modal Value of the Haplogroup it is logical to base your calculations on the Modal Value not the Mean or Average Value of the Haplogroup.

I do not disagree that using the Modal may produce the wrong answer, in fact it is doubtful that Variance is a suitable function for counting mutations, particularly in fast-mutating alleles, over the the timescale of the Haplotypes you are attempting to measure when the rate of "apparent" mutations becomes none-linear during the second and subsequent mutation step resulting from the increased probability of reverse or back mutation.

Regarding your test using the R-L1 Haplogroup, it is clear from the results of the predicted Generation count for the individual markers shown in your calculation sheet that there is a serious mismatch in the predicted ages. This suggests that either the mutation rates that you are using are not representative of the sample set of Haplotypes, or Variance is not a suitable function for modelling the behaviour of the individual alleles over the time period concerned, (or both).

Either way, the results do not stand up to scrutiny.
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Mike Walsh
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« Reply #34 on: November 08, 2012, 11:38:57 AM »

...
Ken's Model measures variance in relation to the haplogroup Modal using the MODE function which assigns to the cell the value with the highest frequency of the allele.

This is logical since the Modal is the ''assumed'' ancestral value for the haplogroup from which mutations have assumed to have occured. It is also an integer and mutations occur in integer steps from the Modal.

The EXCEL function VAR on the other hand measures variance from the AVERAGE value of the Haplogroup allele values. The average value will normaly be a none-integer number, different to the Modal, particularly when the mutations are none-symetric about the Modal in which case the difference may be significant.

The way that the Variance function works is likely to result in your Model's final generation count being under-estimated compared to Ken's Model.

Mark, I haven't read the basics on Excel's VAR and VARP for a while, but I think we want to use the true MODE rather than a MEAN. The statistical MEAN will lead us more toward an average age of coalescence rather than a true Most Recent Common Ancestor (individual) age. I don't know how significant this is, but for a potential wave surfing population (i.e. R1b in W. Europe) I would suspect it would be more important to use the MODE.
« Last Edit: November 08, 2012, 11:40:41 AM by Mikewww » Logged

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Mark Jost
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« Reply #35 on: November 08, 2012, 12:55:48 PM »

Autochthon>Either way, the results do not stand up to scrutiny.

Who’s???

The numerical value of the mode is the same as that of the mean and median in a normal distribution, and it may be very different in highly skewed distributions. Many skewed distributions are best described by their mean. Noting that the mean and the mode coincide if the variants are normally distributed. The mode is not necessarily unique, since the probability mass function or probability density function may take the same maximum value at several points, the dataset may be said to be bimodal. Variance, like the average (Mean), is an index sensitive to extreme scores. Again, using variance which is a mean value is satisfactory unless there are some high level skewing occurring in certain STRs in a set of haplotypes. I will modify my spreadsheet Results tab to show Differences in the two clades Modal, Mean and Median as a tool to discover possible pieces of data that could skew the results. I also show the color coded range of the individual mutation rates.

I am sure you can agree with me that we could adjust certain haplotype that have a outlying variance with in a STR. Removing Multi-copy markers, which in themselves, have an inherently stronger skewing effects reduces the overall variance and thus more correctly defines generation age.

Autochthon>This suggests that either the mutation rates that you are using are not representative of the sample set of Haplotypes, or Variance is not a suitable function for modeling the behavior of the individual alleles over the time period concerned, (or both).

As for Mutations rates be a factor, yes, of course, they could affect the results. But I have a very high confidence in Marko's understanding and his calibrated mutation rates results.

Time Scale can be affected by faster mutations or those STRs which have a higher allele values which appear to have a higher mutation rate. Removing any Markers would seem to have an sense of cherry picking those which would perform in ways the person desired, as in how the original markers were chosen in the lesser number marker panels.

I can remove certain STRs to end run that issue but which ones to remove is the basic question. MarkoH has a list of the 67 marker panel which shows each with a linear 10% error but only to assumed ancestral allele values. He can address any issues you have with his rate calculations. The 68 and higher STRs were not studied as to Linear error rates.

Maybe utilizing logarithmic methods could show that the variance between all of the STRs allele values in the data set are or not essentially correct. But we are working within known subclade groups of haplotypes.

MJost
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148326
Pos: Z245 L459 L21 DF13**
Neg: DF23 L513 L96 L144 Z255 Z253 DF21 DF41 (Z254 P66 P314.2 M37 M222  L563 L526 L226 L195 L193 L192.1 L159.2 L130 DF63 DF5 DF49)
WTYNeg: L555 L371 (L9/L10 L370 L302/L319.1 L554 L564 L577 P69 L626 L627 L643 L679)
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« Reply #36 on: November 08, 2012, 03:43:55 PM »

Autochthon>Either way, the results do not stand up to scrutiny.

Who’s???

Anyone who examines the results of Lines 24 and 25 of your R-L21 TMRCA calculation sheet. They show the Generation age of Haplogroup R-L21 as predicted by the individual markers (Variance/Mutation rate). If the mutation rates are representative of the Haplogroup they shoud be equal within reasonable limits.
The results are sorted by value and reproduced as follows:

Age in Generations of R-L21 as predicted by individual markers
20
35
35
48
49
52
53
60
61
62
66
71
73
74
79
81
81
85
86
93
95
95
96
99
99
100
100
101
102
104
106
115
119
120
121
138
147
150
150
170
173
188
234
254
261
342
431
473
499
565

Would you consider these values to be equal within reasonable limits?



Autochthon>This suggests that either the mutation rates that you are using are not representative of the sample set of Haplotypes, or Variance is not a suitable function for modeling the behavior of the individual alleles over the time period concerned, (or both).

As for Mutations rates be a factor, yes, of course, they could affect the results. But I have a very high confidence in Marko's understanding and his calibrated mutation rates results.
MJost

Then how do you account for the variations in the above Predicted Generation ages?

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Mark Jost
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« Reply #37 on: November 08, 2012, 04:23:55 PM »

Anyone who examines the results of Lines 24 and 25 of your R-L21 TMRCA calculation sheet. They show the Generation age of Haplogroup R-L21 as predicted by the individual markers (Variance/Mutation rate). If the mutation rates are representative of the Haplogroup they shoud be equal within reasonable limits.

Equal within reasonable limits? These are random mutations.

These two lines are the AltAge (as always stated in the spreadsheet that this was an alternate) which is based on Variance Per Marker divided by that STR's mutation rate and is the Generation per Marker which is NOT the proper method used to show Generations, as I said, this was an Alternate method for comparison purposes and is not shown in the Results tab. Ken N. doesnt use this method Alternate method either. It is the SUM of variance divided by the sum of the mutation rates that is shown.

Your specific use of my Alternate Age Calculation is not working to justify your belief of that variance should not be used in calculating any age. Anyone can see this.

MJost
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148326
Pos: Z245 L459 L21 DF13**
Neg: DF23 L513 L96 L144 Z255 Z253 DF21 DF41 (Z254 P66 P314.2 M37 M222  L563 L526 L226 L195 L193 L192.1 L159.2 L130 DF63 DF5 DF49)
WTYNeg: L555 L371 (L9/L10 L370 L302/L319.1 L554 L564 L577 P69 L626 L627 L643 L679)
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« Reply #38 on: November 08, 2012, 04:35:29 PM »

Since the discussion of Mean vs Modal and where the numerical value of the mode is the same as that of the mean and median in a normal distribution, I added several items to show Mean, Mode, Median and if there is any differences between the two clades that needs to be investigated. I show Mean as a rounded Up or Down for the difference check.  I also added the Marker Mutation Rates with Color Scaling.

Version 1.7b TMRCA Estimate Age spreadsheet.

https://docs.google.com/file/d/0By9Y3jb2fORNX2FjVV85bmVtWWs/edit

MJost
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148326
Pos: Z245 L459 L21 DF13**
Neg: DF23 L513 L96 L144 Z255 Z253 DF21 DF41 (Z254 P66 P314.2 M37 M222  L563 L526 L226 L195 L193 L192.1 L159.2 L130 DF63 DF5 DF49)
WTYNeg: L555 L371 (L9/L10 L370 L302/L319.1 L554 L564 L577 P69 L626 L627 L643 L679)
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« Reply #39 on: November 10, 2012, 03:59:25 AM »


Mark, I haven't read the basics on Excel's VAR and VARP for a while, but I think we want to use the true MODE rather than a MEAN. The statistical MEAN will lead us more toward an average age of coalescence rather than a true Most Recent Common Ancestor (individual) age. I don't know how significant this is, but for a potential wave surfing population (i.e. R1b in W. Europe) I would suspect it would be more important to use the MODE.

Ok, I looked at the issue of using pooled SD using Modal variance instead of Mean variance of that data set of two clades and I think I got it figured out and tested most cases. I identified the Var 'Mean; Founder version and added 'Modal' Founder version in the Dash Board on the Results tab. along with an Interclade for the Modal as well.

When thinking about it, the Var (mean) is similar to fractionizing Allele values so it could be just considered that Var Mean as a sample population that could represent the Node of a MRCA Coalesence point of an unknown Founder. Coalesence as originally used, is variance age as the whole population. The Mean Variance Founder presents the unknow haplotypes needed to get to a MRCA node. Ken's Modal should be the MRCA Founder of the this clade. Interclade further defines this Modal Founder's age.

So please try it out.

I am releasing my TRMCA Estimator v2.0 empty and a new L21 load one.

https://docs.google.com/file/d/0By9Y3jb2fORNX2FjVV85bmVtWWs/edit
 
L21 loaded.
https://docs.google.com/open?id=0By9Y3jb2fORNSU9Lbi1rYXl4NU   
 
MJost

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148326
Pos: Z245 L459 L21 DF13**
Neg: DF23 L513 L96 L144 Z255 Z253 DF21 DF41 (Z254 P66 P314.2 M37 M222  L563 L526 L226 L195 L193 L192.1 L159.2 L130 DF63 DF5 DF49)
WTYNeg: L555 L371 (L9/L10 L370 L302/L319.1 L554 L564 L577 P69 L626 L627 L643 L679)
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« Reply #40 on: November 10, 2012, 03:00:23 PM »

When thinking about it, the Var (mean) is similar to fractionizing Allele values so it could be just considered that Var Mean as a sample population that could represent the Node of a MRCA Coalesence point of an unknown Founder. Coalesence as originally used, is variance age as the whole population. The Mean Variance Founder presents the unknow haplotypes needed to get to a MRCA node. Ken's Modal should be the MRCA Founder of the this clade. Interclade further defines this Modal Founder's  age.

Right, that's getting to what we want if we are looking for the founder.  We really want the ancestral haplotype, not even the modal. It's just that the modal, more so than the mean, is our best shot at assigning the ancestral haplotype.

In reality, although I can't think of the statistical justification/method, we can make "manual" adjustments to the modal haplotype to get our best probability at the ancestral haplotype.

To do this, we need to look at modal haplotypes for parent clades, brother clades, etc. For instance, it is my opinion that the ancestral haplotype value for DYS390 for all of U106 is 24, even though the modal and mean are both 23.
« Last Edit: November 10, 2012, 03:00:53 PM by Mikewww » Logged

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« Reply #41 on: November 10, 2012, 05:33:16 PM »

In reality, although I can't think of the statistical justification/method, we can make "manual" adjustments to the modal haplotype to get our best probability at the ancestral haplotype.

To do this, we need to look at modal haplotypes for parent clades, brother clades, etc. For instance, it is my opinion that the ancestral haplotype value for DYS390 for all of U106 is 24, even though the modal and mean are both 23.

I havent ever looked for that in U106, but you seem to be referring to this situation as possible bimodal as I mentioned five or so posts back. If one were to show the STR values in a Histogram of the Mean, it would become plain to see.

U106 390 shows:
Bin   Frequency
23   1243
24   783
25   188
22   57
More   13
21   2

The suggestion is that there are two peaks in the mixture density only if the distance between the means is greater than two standard deviations.

Question is how can that be measured?

I had setup a TTest function in the spreadsheet but havent experiemented with it yet.

MJost
« Last Edit: November 10, 2012, 05:33:41 PM by Mark Jost » Logged

148326
Pos: Z245 L459 L21 DF13**
Neg: DF23 L513 L96 L144 Z255 Z253 DF21 DF41 (Z254 P66 P314.2 M37 M222  L563 L526 L226 L195 L193 L192.1 L159.2 L130 DF63 DF5 DF49)
WTYNeg: L555 L371 (L9/L10 L370 L302/L319.1 L554 L564 L577 P69 L626 L627 L643 L679)
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« Reply #42 on: November 13, 2012, 11:47:43 AM »

TRMCA Variance Estimator V2.1a is released.
Redefined Results categories. Added slowest 3rd marker calculations.

Empty Version:
http://tinyurl.com/TMRCA-Gen111T-Estimator

L21 Loaded version:
http://tinyurl.com/TMRCA-Gen111T-Estimator-L21

MJost
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148326
Pos: Z245 L459 L21 DF13**
Neg: DF23 L513 L96 L144 Z255 Z253 DF21 DF41 (Z254 P66 P314.2 M37 M222  L563 L526 L226 L195 L193 L192.1 L159.2 L130 DF63 DF5 DF49)
WTYNeg: L555 L371 (L9/L10 L370 L302/L319.1 L554 L564 L577 P69 L626 L627 L643 L679)
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« Reply #43 on: November 22, 2012, 09:38:25 PM »


TRMCA Variance Estimator V2.1b is released.

(MikeW's R1b-Early 67 marker Haplotypes Loaded) Version:
http://tinyurl.com/TMRCA-Gen111T-Estimator

MJost
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148326
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Neg: DF23 L513 L96 L144 Z255 Z253 DF21 DF41 (Z254 P66 P314.2 M37 M222  L563 L526 L226 L195 L193 L192.1 L159.2 L130 DF63 DF5 DF49)
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« Reply #44 on: December 28, 2012, 06:25:05 PM »



TRMCA Variance Estimator V2.2 is released.

(MikeW's 12/27/12 - L21 67 marker Haplotypes are Loaded):

https://docs.google.com/file/d/0By9Y3jb2fORNSU9Lbi1rYXl4NUU/edit

MJost
Logged

148326
Pos: Z245 L459 L21 DF13**
Neg: DF23 L513 L96 L144 Z255 Z253 DF21 DF41 (Z254 P66 P314.2 M37 M222  L563 L526 L226 L195 L193 L192.1 L159.2 L130 DF63 DF5 DF49)
WTYNeg: L555 L371 (L9/L10 L370 L302/L319.1 L554 L564 L577 P69 L626 L627 L643 L679)
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