G25 coords for each chromosome

[Beowulf]

I hate to repost but I'm pretty certain you can only compare chromosome coordinates with other chromosome coordinates. So a calculator would have to be made using only chromosome coordinates. What it looks like we are doing here is comparing our chromosome coordinates to calculators made from autosomal coordinates. Which will give pretty meaningless (fake) results.

I've didn't thought about that...

[ScandinavianCelt]

I hate to repost but I'm pretty certain you can only compare chromosome coordinates with other chromosome coordinates.

Why would that be true? They are simulated, but still standard format G25.

So a calculator would have to be made using only chromosome coordinates.

I don't think so. The results are simply specific to the chromosome(s) tested.

What it looks like we are doing here is comparing our chromosome coordinates to calculators made from autosomal coordinates.

The calculators are merely giving the autosomal results for any specific one chromosome. It's not different from GEDmatch breaking down each chromosome to see individual chromosome admixtures. It isn't telling you that is the overall breakdown you have for all 22 chromosomes.


Which will give pretty meaningless (fake) results.


If analyzing your DNA by individual chromosome is meaningless then why would analyzing all 22 chromosomes have any meaning at all?

[ScandinavianCelt]

I've didn't thought about that...

I misquoted someone else on page two-- it was meant for you. Please see my question on pg 2.

[Beowulf]

I misquoted someone else on page two-- it was meant for you. Please see my question on pg 2.

No problem

i used this one:

https://www.exploreyourdna.com/calcu...lator-k105.htm

[ScandinavianCelt]

No problem

i used this one:

https://www.exploreyourdna.com/calcu...lator-k105.htm

Try 1st C BC calc. and Globe 58 Scaled Individuals. It's fun experimenting.

A cool thing would be to map them individually on that G25 map tool you posted, then compare. That test uses official mod and ancient pop averages scaled, plus mod scaled.

Look at how my official is distanced from each chromosome:

Distance to: ScandinavianCelt

0.01813218 brad.k36.chr1
0.02247258 brad.k36.chr2
0.02599507 brad.k36.chr10
0.02644244 brad.k36.chr4
0.02813252 brad.k36.chr8
0.02945215 brad.k36.chr3
0.03588381 brad.k36.chr20
0.03633834 brad.k36.chr6
0.03817431 brad.k36.chr13
0.04037110 brad.k36.chr15
0.04223108 brad.k36.chr9
0.04232654 brad.k36.chr16
0.04320193 Brad.k36.chr11
0.04481404 Brad.k36.chr17
0.04693985 brad.k36.chr7
0.04827311 brad.k36.chr5
0.04884948 brad.k36.chr12
0.04989116 brad.k36.chr19
0.05119827 brad.k36.chr18
0.05399238 brad.k36.chr22
0.06069976 brad.k36.chr21
0.06221550 brad.k36.chr14

[Beowulf]

Try 1st C BC calc. and Globe 58 Scaled Individuals. It's fun experimenting.

A cool thing would be to map them individually on that G25 map tool you posted, then compare. That test uses official mod and ancient pop averages scaled, plus mod scaled.

Look at how my official is distanced from each chromosome:

Distance to: ScandinavianCelt

0.01813218 brad.k36.chr1
0.02247258 brad.k36.chr2
0.02599507 brad.k36.chr10
0.02644244 brad.k36.chr4
0.02813252 brad.k36.chr8
0.02945215 brad.k36.chr3
0.03588381 brad.k36.chr20
0.03633834 brad.k36.chr6
0.03817431 brad.k36.chr13
0.04037110 brad.k36.chr15
0.04223108 brad.k36.chr9
0.04232654 brad.k36.chr16
0.04320193 Brad.k36.chr11
0.04481404 Brad.k36.chr17
0.04693985 brad.k36.chr7
0.04827311 brad.k36.chr5
0.04884948 brad.k36.chr12
0.04989116 brad.k36.chr19
0.05119827 brad.k36.chr18
0.05399238 brad.k36.chr22
0.06069976 brad.k36.chr21
0.06221550 brad.k36.chr14

I always use that one when i want to do experiments with some samples, i think is a very good calculator

[Far_away]

Did not do them all but just wanted to see on 7 chr because i had huge % Italian

0.01488046 North_Macedonia
0.01753206 Albania
0.02384561 Bulgaria
0.02706463 Romania
0.03712400 Montenegro
0.03797667 Serbia
0.04098910 Italy
0.04299940 Greece
0.05024438 Switzerland
0.05057094 Bosnia
0.05342135 Moldova
0.06218576 Croatia
0.06331201 Slovenia
0.06588647 Hungary
0.06652234 Austria
0.06686618 Israel
0.06932325 France
0.07018591 Portugal
0.07085317 Spain
0.07234683 Belgium
0.07857430 Czech_Republic
0.07946175 Ukraine
0.07967805 Germany
0.08923758 Holland
0.08982427 Slovakia


on 6 had huge Iberian% and also Italian

0.03634036 Switzerland
0.03797427 Italy
0.03925540 Albania
0.03952861 Bulgaria
0.04010507 North_Macedonia
0.04057179 Romania
0.04477017 Portugal
0.04543020 Spain
0.04955437 France
0.05076102 Montenegro
0.05223151 Serbia
0.05798782 Greece
0.06029283 Belgium
0.06355568 Bosnia
0.06409974 Moldova
0.06570287 Austria
0.06867874 Israel
0.06900710 Croatia
0.06955489 Hungary
0.07035152 Slovenia
0.07707963 Germany
0.08029183 Holland
0.08040643 Wales
0.08132504 Czech_Republic
0.08174826 England

[Boudin]

The calculators are merely giving the autosomal results for any specific one chromosome. It's not different from GEDmatch breaking down each chromosome to see individual chromosome admixtures. It isn't telling you that is the overall breakdown you have for all 22 chromosomes.

It would be valid if you compared your Chr13 GEDmatch result with the Chr13 GEDmatch results of (for instance) a Frenchman and an Italian to see whether your Chr13 is more French or more Italian.

But it would not be valid to compare your Chr13 GEDmatch result with anyone's full autosomal results, because it's apples and oranges. The PCAs do not correspond. I will try to come up with a simplified analogy to illustrate:

Imagine there is a test called G3 that gives you 3 coordinates describing the principal components of your physical appearance that are most relevant for estimating your ancestry. PC1 is eye color (0 = brown, 0.5 = hazel, 1 = blue), PC2 is hair color (0 = black, 0.5 = blonde, 1 = red), and PC3 is skin color (0 = black, 0.5 = tan, 1 = white). Your hypothetical G3 coordinates are 1,0.5,1.

You can compare your results with someone from Nigeria (native_nigerian,0,0,0) to see there is a large distance between you and them.

You can also compare your results with a redhead from Ireland (native_irishman,1,1,1) to see there is a very tiny distance between you and them.

All good so far, but imagine you have another set of G3 coordinates just for one part of your body, let's say it's your left arm Your coordinates are ScandinavianCelt_left_arm,0.75,0,1.

Maybe PC2 and PC3 (describing the hair and skin color of your left arm) make a bit of sense, but they aren't comparable to full-body coordinates because hair color on head isn't the same as hair color on arm.

And what in the world is PC1 (0.75) supposed to represent? Your left arm doesn't have eyes. Well, mine doesn't anyway.

Hopefully it is obvious now why you can't compare ScandinavianCelt_left_arm,0.75,0,1 with ScandinavianCelt_full_phenotype,1,0.5,1.

[JayH]

If analyzing your DNA by individual chromosome is meaningless then why would analyzing all 22 chromosomes have any meaning at all?

Not any sense, but less reliable especially for small chromosomes.
The allelic frequency differences are really very small.
The results become reliable by comparing a large number of markers.
The problem of cutting by chromosome makes the results less reliable and especially for very small chromosomes as 19,20,21 and 22

However, I did the test by putting only the first 3 closest populations per chromosome.
I also made a mapwith the position of each chromosome on the first population.
Unsurprisingly, chromosomes 20, 21 and 22 are eccentric.
Otherwise, the results are not so bad...

Chr1
0.03432536 Belgian
0.03447861 French_Brittany
0.03551665 French_Paris

Chr2
0.03297263 French_Alsace
0.03416346 Austrian
0.03563290 Swiss_German

Chr3
0.01366340 French_Auvergne
0.01470834 French_Occitanie
0.01496434 Swiss_German

Chr4
0.01758216 French_Alsace
0.01808302 Austrian
0.01918191 French_Nord

Chr5
0.03095307 Italian_Northeast
0.03127852 French_Auvergne
0.03173034 French_Alsace

Chr6
0.03334108 French_Provence
0.03407286 Italian_Northeast
0.03549771 Swiss_Italian

Chr7
0.02723377 Slovenian
0.02740236 Croatian
0.03066680 Austrian

Chr8
0.02347017 French_Alsace
0.02641038 Swiss_German
0.02744089 Italian_Northeast

Chr9
0.02581736 French_Pas-de-Calais
0.02602277 French_Nord
0.02682502 French_Paris

Chr10
0.01719253 French_Occitanie
0.02110291 French_Auvergne
0.02419532 French_Paris

Chr11
0.01953014 French_Alsace
0.02123561 French_Nord
0.02145494 Swiss_German

Chr12
0.02428751 German_East
0.02463505 Czech
0.02919253 Swedish

Chr13
0.02595124 French_Alsace
0.02669326 French_Nord
0.02677162 Belgian

Chr14
0.01886654 French_Brittany
0.02199038 English_Cornwall
0.02263183 Welsh

Chr15
0.01980151 French_Brittany
0.02034198 Belgian
0.02238225 French_Nord

Chr16
0.01697223 French_Nord
0.01804286 Swiss_German
0.01846269 French_Alsace

Chr17
0.02550564 French_Paris
0.02583008 French_Nord
0.02585147 French_Alsace

Chr18
0.02406160 French_Brittany
0.02514925 Belgian
0.02531592 French_Paris

Chr19
0.02854892 French_Provence
0.02949809 Spanish_Mallorca
0.03085201 Spanish_Eivissa

Chr20
0.02340968 Scottish
0.02345103 Orcadian
0.02394447 Dutch

Chr21
0.02708714 Italian_Veneto
0.02763060 Greek_Central_Macedonia
0.02773902 Italian_Piedmont

Chr22
0.02507897 Spanish_Mallorca
0.02550205 Spanish_Galicia
0.02642332 Spanish_Castilla_Y_Leon

[ScandinavianCelt]

Not any sense, but less reliable especially for small chromosomes.
The allelic frequency differences are really very small.
The results become reliable by comparing a large number of markers.
The problem of cutting by chromosome makes the results less reliable and especially for very small chromosomes as 19,20,21 and 22

However, I did the test by putting only the first 3 closest populations per chromosome.
I also made a mapwith the position of each chromosome on the first population.
Unsurprisingly, chromosomes 20, 21 and 22 are eccentric.
Otherwise, the results are not so bad...

Chr1
0.03432536 Belgian
0.03447861 French_Brittany
0.03551665 French_Paris

Chr2
0.03297263 French_Alsace
0.03416346 Austrian
0.03563290 Swiss_German

Chr3
0.01366340 French_Auvergne
0.01470834 French_Occitanie
0.01496434 Swiss_German

Chr4
0.01758216 French_Alsace
0.01808302 Austrian
0.01918191 French_Nord

Chr5
0.03095307 Italian_Northeast
0.03127852 French_Auvergne
0.03173034 French_Alsace

Chr6
0.03334108 French_Provence
0.03407286 Italian_Northeast
0.03549771 Swiss_Italian

Chr7
0.02723377 Slovenian
0.02740236 Croatian
0.03066680 Austrian

Chr8
0.02347017 French_Alsace
0.02641038 Swiss_German
0.02744089 Italian_Northeast

Chr9
0.02581736 French_Pas-de-Calais
0.02602277 French_Nord
0.02682502 French_Paris

Chr10
0.01719253 French_Occitanie
0.02110291 French_Auvergne
0.02419532 French_Paris

Chr11
0.01953014 French_Alsace
0.02123561 French_Nord
0.02145494 Swiss_German

Chr12
0.02428751 German_East
0.02463505 Czech
0.02919253 Swedish

Chr13
0.02595124 French_Alsace
0.02669326 French_Nord
0.02677162 Belgian

Chr14
0.01886654 French_Brittany
0.02199038 English_Cornwall
0.02263183 Welsh

Chr15
0.01980151 French_Brittany
0.02034198 Belgian
0.02238225 French_Nord

Chr16
0.01697223 French_Nord
0.01804286 Swiss_German
0.01846269 French_Alsace

Chr17
0.02550564 French_Paris
0.02583008 French_Nord
0.02585147 French_Alsace

Chr18
0.02406160 French_Brittany
0.02514925 Belgian
0.02531592 French_Paris

Chr19
0.02854892 French_Provence
0.02949809 Spanish_Mallorca
0.03085201 Spanish_Eivissa

Chr20
0.02340968 Scottish
0.02345103 Orcadian
0.02394447 Dutch

Chr21
0.02708714 Italian_Veneto
0.02763060 Greek_Central_Macedonia
0.02773902 Italian_Piedmont

Chr22
0.02507897 Spanish_Mallorca
0.02550205 Spanish_Galicia
0.02642332 Spanish_Castilla_Y_Leon

Have you targeted your official coordinates against a source of your 22 chromosomes individually simulated to see the distances between you and all the chromosomes? I did that and some interesting results emerged you might want to try it out your distance is look very good on your highest or I should say shortest actual chromosomes at least on this test but if you measure the actual distance of your official to each of the simulated 22 coordinates representing each chromosome you have you'll probably see some interesting results you can post it here or you could message me directly I can show you what I get:


Distance to: ScandinavianCelt

0.01813218 brad.k36.chr1
0.02247258 brad.k36.chr2
0.02599507 brad.k36.chr10
0.02644244 brad.k36.chr4
0.02813252 brad.k36.chr8
0.02945215 brad.k36.chr3
0.03588381 brad.k36.chr20
0.03633834 brad.k36.chr6
0.03817431 brad.k36.chr13
0.04037110 brad.k36.chr15
0.04223108 brad.k36.chr9
0.04232654 brad.k36.chr16
0.04320193 Brad.k36.chr11
0.04481404 Brad.k36.chr17
0.04693985 brad.k36.chr7
0.04827311 brad.k36.chr5
0.04884948 brad.k36.chr12
0.04989116 brad.k36.chr19
0.05119827 brad.k36.chr18
0.05399238 brad.k36.chr22
0.06069976 brad.k36.chr21
0.06221550 brad.k36.chr14