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Thread: qpAdm thread

  1. #111
    Veteran Member Zoro's Avatar
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    Quote Originally Posted by Korialstrasz View Post
    @Kaspias

    I am glad that my post helped. Nice to see that you too have managed to run it!

    @Zoro

    Very helpful advices all around. Thanks again.


    ---


    So I made a few more runs (maxmiss=0 and 93k~ snps ) using the 1240K dataset and the following populations. I picked Tepecik for Neolithic Anatolia. Open for suggestions!
    Z is directly proportional to p-value. The higher the p the lower the Z

    Your passing models are generally >0.05. The higher ones such as >0.40 are a little more accurate

    Agree with regards to SE Adygei due to Georgian. If you really need to use both you have to add another pright that's shares more genetic drift with one vs the other.

    Your SE is still acceptable. Your p of 0.68 is very good.

    How many SNPs were used in the f2 run?

  2. #112
    Member Korialstrasz's Avatar
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    Quote Originally Posted by Zoro View Post
    Congrats, looking good.



    Now when I add "Anatolia_N" to extract or pright only the ENF samples with low missingness are used and the rest are ignored.

    You may ask why I don't only use the best 2 ENF samples instead of the best 8. The answer to that is the more samples the more accurate the allele frequencies for the population become. So its a tradeoff between ignoring worse samples and improving allele frequencies.

    So I did this for every population I use, exluded those with very high missing ratios. But some populations like Ganj_Dareh only has a few samples and decided to stick to SNPs in the trade-off you mentioned. (I think I only eliminated those with 0.85+ missing)
    Removed Tepecik and went on with only Turkey_N. Since my right pops cannot distinguish Greek vs Bulgarian, I wanted to use Polish for slavic proxy. (Not sure if this is a good idea). After going with Turkey_N, Adygei never fell below 0.6. This tells me that I am missing something. I´ll read this next: https://www.biorxiv.org/content/10.1...664v1.full.pdf

    Perhaps I should use earlier, let´s say medieval, pops as left references. As I am mostly interested in getting a rough estimation of my admixture.
    Code:
     
    =======================================
      target     left    weight  se     z  
    ---------------------------------------
    1 my_geno Adygei.DG  0.624  0.152 4.103
    2 my_geno Turkmen.SG 0.012  0.044 0.282
    3 my_geno Greek_1.DG 0.069  0.147 0.47 
    4 my_geno Polish.DG  0.294  0.094 3.138
    ---------------------------------------
    
    ======================================================
      f4rank dof  chisq     p   dofdiff chisqdiff p_nested
    ------------------------------------------------------
    1   3     5    0.57   0.989    7     64.579      0    
    2   2    12   65.149    0      9     164.988     0    
    3   1    21  230.138    0     11     893.415     0    
    4   0    32  1123.552   0     NA       NA        NA   
    ------------------------------------------------------


    Quote Originally Posted by Zoro View Post

    How many SNPs were used in the f2 run?
    Those f2 statistics came from the run with 93k~ snps.

    New one with 100k~ SNPs: (you can see the populations I use, moderns left ancients right.)

    Code:
    ===============================================
       pop1          pop2             est     se   
    -----------------------------------------------
    1   me       Bulgarian.DG       0.00071 0.00108
    2   me    Russia_Abkhasian.DG   0.00094 0.00111
    3   me        Georgian.DG       0.00097 0.00111
    4   me        Armenian.DG       0.00109 0.00109
    5   me         Adygei.DG        0.00114 0.00116
    6   me        Turkish.DG        0.00143 0.00113
    7   me        Greek_1.DG        0.00157 0.00112
    8   me  Russia_NorthOssetian.DG 0.00182 0.00114
    9   me        Iranian.DG        0.00219 0.00112
    10  me         Polish.DG        0.0022  0.00146
    11  me        Turkmen.SG        0.00557 0.00136
    12  me         Turkey_N         0.00895 0.00101
    13  me     Iran_GanjDareh_N     0.0279  0.00127
    14  me         Ukraine_N        0.0285  0.00113
    15  me     Russia_Yana_UP.SG    0.03287 0.00161
    16  me  Russia_DevilsCave_N.SG  0.06759 0.00159
    17  me     Georgia_Kotias.SG    0.18128 0.00152
    18  me     Russia_HG_Karelia    0.18468 0.00151
    19  me   Switzerland_Bichon.SG  0.18638 0.00168
    20  me    Russia_Kolyma_M.SG    0.20019 0.00163
    -----------------------------------------------
    bonus:

    possibly historically not accurate, but just felt curious to see what I´d get.

    Code:
    ==========================================
        target      left    weight  se     z  
    ------------------------------------------
    1 Turkish.DG Greek_1.DG 0.504  0.09  5.619
    2 Turkish.DG Turkmen.SG 0.113  0.037 3.066
    3 Turkish.DG Iranian.DG 0.383  0.115 3.33 
    ------------------------------------------
    
    ======================================================
      f4rank dof  chisq     p   dofdiff chisqdiff p_nested
    ------------------------------------------------------
    1   2     6   10.737  0.097    8     98.977      0    
    2   1    14  109.714    0     10     911.517     0    
    3   0    24  1021.231   0     NA       NA        NA   
    ------------------------------------------------------
    Thank you a lot again, Zoro.
    50% Turkish_Deliorman + 50% Adygei @ 4,879

  3. #113
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    Quote Originally Posted by Zoro View Post
    It looks like you're getting much closer. Your p-value is now passing at 6.98e- 1 which is basically 0.698 !

    Your standard errors are not good though especially for Avar 1 Kaspias Hungary_Avar_5 0.0528 0.234 0.225 because it's saying 5.28% Avar +/-23.4%

    All this means is your pright are not sufficient to distinguish the genetic difference between Hungary-Avar and Bulgaria-IA. Add a pright that you think is much genetically closer to Avar than Bulgaria-IA OR visa versa
    I'm having hard time while interpreting these tbh:

    F2s
    Code:
      pop1             pop2               est       se
                                    
      1 Kaspias      Adygei.DG        0.361 0.00114 
      2 Kaspias      Albanian.DG      0.359 0.00128 
      3 Kaspias      Bashkir.SG       0.363 0.00114 
      4 Kaspias      Bulgarian.DG     0.360 0.00114 
      5 Kaspias      Cretan.DG        0.360 0.00118 
      6 Kaspias      French.DG        0.360 0.00113 
      7 Kaspias      Greek_1.DG       0.360 0.00121 
      8 Kaspias      Greek_2.DG       0.359 0.00122 
      9 Kaspias      Iranian.DG       0.362 0.00115 
     10 Kaspias      Italian_North.DG 0.360 0.00129 
     11 Kaspias      Jordanian.DG     0.365 0.00107 
     12 Kaspias      Mansi.DG         0.365 0.00111 
     13 Kaspias      Polish.DG        0.360 0.00121 
     14 Kaspias      Russian.DG       0.361 0.00113 
     15 Kaspias      Tatar_Tomsk.SG   0.366 0.00108 
     16 Kaspias      Turkish.DG       0.362 0.00112 
     17 Kaspias      Turkmen.SG       0.364 0.00113 
     18 Kaspias      Tuscan_1.DG      0.360 0.00115 
     19 Kaspias      Uzbek.SG         0.366 0.00109
    Fst:

    Code:
     pop1             pop2                    est      se
                                        
      1 Kaspias      Adygei.DG         0.134     0.00284
      2 Kaspias      Albanian.DG       0.137     0.00395
      3 Kaspias      Bashkir.SG        0.137     0.00296
      4 Kaspias      Bulgarian.DG      0.130     0.00288
      5 Kaspias      Cretan.DG         0.131     0.00294
      6 Kaspias      French.DG         0.134     0.00272
      7 Kaspias      Greek_1.DG        0.131     0.00337
      8 Kaspias      Greek_2.DG        0.129     0.00364
      9 Kaspias      Iranian.DG        0.133     0.00293
     10 Kaspias      Italian_North.DG  0.132     0.00346
     11 Kaspias      Jordanian.DG      0.141     0.00278
     12 Kaspias      Mansi.DG          0.156     0.00281
     13 Kaspias      Polish.DG         0.135     0.00352
     14 Kaspias      Russian.DG        0.134     0.00292
     15 Kaspias      Tatar_Tomsk.SG    0.142     0.00293
     16 Kaspias      Turkish.DG        0.133     0.00275
     17 Kaspias      Turkmen.SG        0.135     0.00298
     18 Kaspias      Tuscan_1.DG       0.134     0.00295
     19 Kaspias      Uzbek.SG          0.140     0.00270
    But I should add, the overlapping SNP number is ~610K now when used the 1240K dataset.

    Code:
    	target	left	weight	se	z
    1	Kaspias	Bulgarian.DG	0.75	0.041	18.11
    2	Kaspias	Uzbek.SG	0.25	0.041	6.05
    
    
    	f4rank	dof	chisq	p.value	dofdiff	chisqdiff	p_nested
    1	1	5	5.81	0.32551	7	735.49	1.5e-154
    2	0	12	741.3	< 2e-16
    Last edited by Kaspias; 03-05-2021 at 10:16 AM.

  4. #114
    Veteran Member Zoro's Avatar
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    Quote Originally Posted by Korialstrasz View Post
    So I did this for every population I use, exluded those with very high missing ratios. But some populations like Ganj_Dareh only has a few samples and decided to stick to SNPs in the trade-off you mentioned. (I think I only eliminated those with 0.85+ missing)
    Removed Tepecik and went on with only Turkey_N. Since my right pops cannot distinguish Greek vs Bulgarian, I wanted to use Polish for slavic proxy. (Not sure if this is a good idea). After going with Turkey_N, Adygei never fell below 0.6. This tells me that I am missing something. I´ll read this next: https://www.biorxiv.org/content/10.1...664v1.full.pdf

    Perhaps I should use earlier, let´s say medieval, pops as left references. As I am mostly interested in getting a rough estimation of my admixture.
    Code:
     
    =======================================
      target     left    weight  se     z  
    ---------------------------------------
    1 my_geno Adygei.DG  0.624  0.152 4.103
    2 my_geno Turkmen.SG 0.012  0.044 0.282
    3 my_geno Greek_1.DG 0.069  0.147 0.47 
    4 my_geno Polish.DG  0.294  0.094 3.138
    ---------------------------------------
    
    ======================================================
      f4rank dof  chisq     p   dofdiff chisqdiff p_nested
    ------------------------------------------------------
    1   3     5    0.57   0.989    7     64.579      0    
    2   2    12   65.149    0      9     164.988     0    
    3   1    21  230.138    0     11     893.415     0    
    4   0    32  1123.552   0     NA       NA        NA   
    ------------------------------------------------------




    Those f2 statistics came from the run with 93k~ snps.

    New one with 100k~ SNPs: (you can see the populations I use, moderns left ancients right.)

    Code:
    ===============================================
       pop1          pop2             est     se   
    -----------------------------------------------
    1   me       Bulgarian.DG       0.00071 0.00108
    2   me    Russia_Abkhasian.DG   0.00094 0.00111
    3   me        Georgian.DG       0.00097 0.00111
    4   me        Armenian.DG       0.00109 0.00109
    5   me         Adygei.DG        0.00114 0.00116
    6   me        Turkish.DG        0.00143 0.00113
    7   me        Greek_1.DG        0.00157 0.00112
    8   me  Russia_NorthOssetian.DG 0.00182 0.00114
    9   me        Iranian.DG        0.00219 0.00112
    10  me         Polish.DG        0.0022  0.00146
    11  me        Turkmen.SG        0.00557 0.00136
    12  me         Turkey_N         0.00895 0.00101
    13  me     Iran_GanjDareh_N     0.0279  0.00127
    14  me         Ukraine_N        0.0285  0.00113
    15  me     Russia_Yana_UP.SG    0.03287 0.00161
    16  me  Russia_DevilsCave_N.SG  0.06759 0.00159
    17  me     Georgia_Kotias.SG    0.18128 0.00152
    18  me     Russia_HG_Karelia    0.18468 0.00151
    19  me   Switzerland_Bichon.SG  0.18638 0.00168
    20  me    Russia_Kolyma_M.SG    0.20019 0.00163
    -----------------------------------------------
    bonus:

    possibly historically not accurate, but just felt curious to see what I´d get.

    Code:
    ==========================================
        target      left    weight  se     z  
    ------------------------------------------
    1 Turkish.DG Greek_1.DG 0.504  0.09  5.619
    2 Turkish.DG Turkmen.SG 0.113  0.037 3.066
    3 Turkish.DG Iranian.DG 0.383  0.115 3.33 
    ------------------------------------------
    
    ======================================================
      f4rank dof  chisq     p   dofdiff chisqdiff p_nested
    ------------------------------------------------------
    1   2     6   10.737  0.097    8     98.977      0    
    2   1    14  109.714    0     10     911.517     0    
    3   0    24  1021.231   0     NA       NA        NA   
    ------------------------------------------------------
    Thank you a lot again, Zoro.


    I'm glad your getting the hang of it. Keep at it and you'll slowly get better !

    Yes, it's best to use ancients to model yourself and others since they are the ones ancestral and not moderns allthough moderns can be used to see how one is shifted compared to neighboring moderns.

    It's always good to get a few passing p-value models with decent SE and then pick the one you think is most accurate based on historical.

    The model you show for the Kayseri Turks is close to what I had but I didn't use Iranians. I used Armenians, Bulgarians and Turkmen and got about 16% Turkmen with equal portions of Armenian and Bulgarian

  5. #115
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    Quote Originally Posted by Kaspias View Post
    I'm having hard time while interpreting these tbh:

    F2s
    Code:
      pop1             pop2               est       se
                                    
      1 Kaspias      Adygei.DG        0.361 0.00114 
      2 Kaspias      Albanian.DG      0.359 0.00128 
      3 Kaspias      Bashkir.SG       0.363 0.00114 
      4 Kaspias      Bulgarian.DG     0.360 0.00114 
      5 Kaspias      Cretan.DG        0.360 0.00118 
      6 Kaspias      French.DG        0.360 0.00113 
      7 Kaspias      Greek_1.DG       0.360 0.00121 
      8 Kaspias      Greek_2.DG       0.359 0.00122 
      9 Kaspias      Iranian.DG       0.362 0.00115 
     10 Kaspias      Italian_North.DG 0.360 0.00129 
     11 Kaspias      Jordanian.DG     0.365 0.00107 
     12 Kaspias      Mansi.DG         0.365 0.00111 
     13 Kaspias      Polish.DG        0.360 0.00121 
     14 Kaspias      Russian.DG       0.361 0.00113 
     15 Kaspias      Tatar_Tomsk.SG   0.366 0.00108 
     16 Kaspias      Turkish.DG       0.362 0.00112 
     17 Kaspias      Turkmen.SG       0.364 0.00113 
     18 Kaspias      Tuscan_1.DG      0.360 0.00115 
     19 Kaspias      Uzbek.SG         0.366 0.00109
    Fst:

    Code:
     pop1             pop2                    est      se
                                        
      1 Kaspias      Adygei.DG         0.134     0.00284
      2 Kaspias      Albanian.DG       0.137     0.00395
      3 Kaspias      Bashkir.SG        0.137     0.00296
      4 Kaspias      Bulgarian.DG      0.130     0.00288
      5 Kaspias      Cretan.DG         0.131     0.00294
      6 Kaspias      French.DG         0.134     0.00272
      7 Kaspias      Greek_1.DG        0.131     0.00337
      8 Kaspias      Greek_2.DG        0.129     0.00364
      9 Kaspias      Iranian.DG        0.133     0.00293
     10 Kaspias      Italian_North.DG  0.132     0.00346
     11 Kaspias      Jordanian.DG      0.141     0.00278
     12 Kaspias      Mansi.DG          0.156     0.00281
     13 Kaspias      Polish.DG         0.135     0.00352
     14 Kaspias      Russian.DG        0.134     0.00292
     15 Kaspias      Tatar_Tomsk.SG    0.142     0.00293
     16 Kaspias      Turkish.DG        0.133     0.00275
     17 Kaspias      Turkmen.SG        0.135     0.00298
     18 Kaspias      Tuscan_1.DG       0.134     0.00295
     19 Kaspias      Uzbek.SG          0.140     0.00270
    But I should add, the overlapping SNP number is ~610K now when used the 1240K dataset.

    Code:
    	target	left	weight	se	z
    1	Kaspias	Bulgarian.DG	0.75	0.041	18.11
    2	Kaspias	Uzbek.SG	0.25	0.041	6.05
    
    
    	f4rank	dof	chisq	p.value	dofdiff	chisqdiff	p_nested
    1	1	5	5.81	0.32551	7	735.49	1.5e-154
    2	0	12	741.3	< 2e-16

    I'm glad your getting the hang of it. Keep at it and you'll slowly get better ! Good to see that you were able to use the 1240K set.

    I like your FST results better than F2s and I think you should use that more than F2s in the future for distances.

    I see that Greek-2 and Bulgarians are closest to you but it looks like you split Greeks into individual samples whereas with Bulgarians it was the average of both Simons samples.

    Can you split the Bulgarians and others into individual samples and repost for kicks


    Your qpAdm model looks good ! but I'm interested to know how many SNPs in the extract and which pright you used

    You're showing 25% Usbek -/+4% which is higher than what I got for the Iraqi Kurds and Kayseri Turks. The Iraqi Kurds were something like ~80% Armenian + ~20% Bashkir or Turkmen.

    I like to model with moderns sometimes because it gives me an idea how shifted compared to their neighbors a population is

    For ex Iraqi Kurds consistently get Iranian or Georgian or Armenian + 10% Estonian or some percentage Tatar or Bashkir. It doesn't mean that they have Estonian ancestry bu this tells me that a significant proportion of their ancestors came from NE of Armenia or Iran

    How many SNPs did you end up with when you did your extract ?

  6. #116
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    Quote Originally Posted by Zoro View Post
    I'm glad your getting the hang of it. Keep at it and you'll slowly get better !

    Yes, it's best to use ancients to model yourself and others since they are the ones ancestral and not moderns allthough moderns can be used to see how one is shifted compared to neighboring moderns.

    It's always good to get a few passing p-value models with decent SE and then pick the one you think is most accurate based on historical.

    The model you show for the Kayseri Turks is close to what I had but I didn't use Iranians. I used Armenians, Bulgarians and Turkmen and got about 16% Turkmen with equal portions of Armenian and Bulgarian
    btw, I read on the supplement to the performance assessment paper that the choice of the top right population matters. Is that still the case? As far as I know, it was necessary to put the target population on top of the left populations before. It seems to have changed on R.

    Right Population File

    This is alist of reference populations to be included in the qpAdm model. The number of reference populations must be greater than the number of left (i.e. target and source) populations. One population should be listed per line. The first population in the list will be used as a base for all f4-statistics calculated. Population order after the first population does not matter.
    I also played around with the allsnps = TRUE feature, and I can say that the results change A LOT.
    Last edited by Korialstrasz; 03-05-2021 at 06:09 PM.
    50% Turkish_Deliorman + 50% Adygei @ 4,879

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    Quote Originally Posted by Zoro View Post
    I'm glad your getting the hang of it. Keep at it and you'll slowly get better ! Good to see that you were able to use the 1240K set.

    I like your FST results better than F2s and I think you should use that more than F2s in the future for distances.

    I see that Greek-2 and Bulgarians are closest to you but it looks like you split Greeks into individual samples whereas with Bulgarians it was the average of both Simons samples.

    Can you split the Bulgarians and others into individual samples and repost for kicks

    Fst, Bulgarian and Turkish also separated:

    Code:
       pop1             pop2                    est      se
                                        
      1 Kaspias      Adygei.DG         0.134     0.00285
      2 Kaspias      Albanian.DG       0.137     0.00395
      3 Kaspias      Bashkir.SG        0.136     0.00300
      4 Kaspias      Bulgarian_1.DG    0.126     0.00347
      5 Kaspias      Bulgarian_2.DG    0.130     0.00358
      6 Kaspias      Cretan.DG         0.131     0.00294
      7 Kaspias      French.DG         0.134     0.00274
      8 Kaspias      Greek_1.DG        0.130     0.00339
      9 Kaspias      Greek_2.DG        0.129     0.00364
     10 Kaspias      Iranian.DG        0.133     0.00292
     11 Kaspias      Italian_North.DG  0.132     0.00351
     12 Kaspias      Jordanian.DG      0.141     0.00279
     13 Kaspias      Mansi.DG          0.156     0.00283
     14 Kaspias      Polish.DG         0.135     0.00354
     15 Kaspias      Russian.DG        0.134     0.00293
     16 Kaspias      Tatar_Tomsk.SG    0.142     0.00294
     17 Kaspias      Turkish_1.DG      0.145     0.00381
     18 Kaspias      Turkish_2.DG      0.132     0.00348
     19 Kaspias      Turkmen.SG        0.135     0.00297
     20 Kaspias      Tuscan_1.DG       0.134     0.00296
     21 Kaspias      Uzbek.SG          0.140     0.00272
    I do not get, how can I be closer to French and Adygei than Albanians? The rest seems ok though.


    Your qpAdm model looks good ! but I'm interested to know how many SNPs in the extract and which pright you used

    You're showing 25% Usbek -/+4% which is higher than what I got for the Iraqi Kurds and Kayseri Turks. The Iraqi Kurds were something like ~80% Armenian + ~20% Bashkir or Turkmen.

    I like to model with moderns sometimes because it gives me an idea how shifted compared to their neighbors a population is

    For ex Iraqi Kurds consistently get Iranian or Georgian or Armenian + 10% Estonian or some percentage Tatar or Bashkir. It doesn't mean that they have Estonian ancestry bu this tells me that a significant proportion of their ancestors came from NE of Armenia or Iran

    How many SNPs did you end up with when you did your extract
    Code:
    √ 1578508 SNPs read in total
    ! 565741 SNPs remain after filtering. 540537 are polymorphic.
    Let me show you all the models:

    Right(Adygei, Cretan, Iranian, Mansi, Polish, Jordanian, Tatar_Tomsk, Italian_North, Albanian, French) -all the of Simeon's-

    Code:
    	target	left	weight	se	z
    1	Kaspias	Bulgarian_1.DG	0.78	0.044	17.51
    2	Kaspias	Turkmen.SG	0.22	0.044	4.98
    
    
    	f4rank	dof	chisq	p.value	dofdiff	chisqdiff	p_nested
    1	1	8	5.96	0.65119	10	553.51	1.6e-112
    2	0	18	559.48	< 2e-16

    Code:
    	target	left	weight	se	z
    1	Kaspias	Bulgarian_1.DG	0.76	0.048	15.89
    2	Kaspias	Bashkir.SG	0.24	0.048	4.89
    
    
    	f4rank	dof	chisq	p.value	dofdiff	chisqdiff	p_nested
    1	1	8	6.44	0.59806	10	478.01	2.2e-96
    2	0	18	484.45	< 2e-16
    Code:
    	target	left	weight	se	z
    1	Kaspias	Bulgarian_1.DG	0.8	0.039	20.51
    2	Kaspias	Uzbek.SG	0.2	0.039	5.13
    
    
    
    	f4rank	dof	chisq	p.value	dofdiff	chisqdiff	p_nested
    1	1	8	4.4	0.81917	10	796.21	1.3e-164
    2	0	18	800.62	< 2e-16
    Code:
    	target	left	weight	se	z
    1	Kaspias	Bulgarian_1.DG	0.82	0.044	18.83
    2	Kaspias	Tatar_Tomsk.SG	0.18	0.044	4.15
    
    
    	f4rank	dof	chisq	p.value	dofdiff	chisqdiff	p_nested
    1	1	8	6.16	0.62951	10	628.79	1.2e-128
    2	0	18	634.94	< 2e-16
    I get negative scores when used Turkish samples to model my Turkic part, which might mean Turkic ancestors of Balkan Turks were not Anatolian Turkish-like.

    Code:
    	target	left	weight	se	z
    1	Kaspias	Bulgarian_1.DG	1.04	5.3	0.2
    2	Kaspias	Turkish_1.DG	-0.04	5.3	-0.01
    
    
    	f4rank	dof	chisq	p.value	dofdiff	chisqdiff	p_nested
    1	1	8	28.18	0.00044187	10	36.1	0.000081
    2	0	18	64.28	4.09e-07
    Code:
    	target	left	weight	se	z
    1	Kaspias	Bulgarian_1.DG	11.44	364.26	0.031
    2	Kaspias	Turkish_2.DG	-10.44	364.26	-0.029
    
    
    	f4rank	dof	chisq	p.value	dofdiff	chisqdiff	p_nested
    1	1	8	29.87	0.00022259	10	30.66	0.00067
    2	0	18	60.54	1.6747e-06

  8. #118
    Veteran Member Zoro's Avatar
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    Quote Originally Posted by Korialstrasz View Post
    btw, I read on the supplement to the performance assessment paper that the choice of the top right population matters. Is that still the case? As far as I know, it was necessary to put the target population on top of the left populations before. It seems to have changed on R.



    I also played around with the allsnps = TRUE feature, and I can say that the results change A LOT.

    qpAdm requires your target and sources for target in pleft and references in pright

    I think that is referring to qpWave not qpAdm

    I don't trust the calculations when allsnps=TRUE because you're not using SNPs that overlap all your pops

  9. #119
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    Quote Originally Posted by Kaspias View Post
    Fst, Bulgarian and Turkish also separated:

    Code:
       pop1             pop2                    est      se
                                        
      1 Kaspias      Adygei.DG         0.134     0.00285
      2 Kaspias      Albanian.DG       0.137     0.00395
      3 Kaspias      Bashkir.SG        0.136     0.00300
      4 Kaspias      Bulgarian_1.DG    0.126     0.00347
      5 Kaspias      Bulgarian_2.DG    0.130     0.00358
      6 Kaspias      Cretan.DG         0.131     0.00294
      7 Kaspias      French.DG         0.134     0.00274
      8 Kaspias      Greek_1.DG        0.130     0.00339
      9 Kaspias      Greek_2.DG        0.129     0.00364
     10 Kaspias      Iranian.DG        0.133     0.00292
     11 Kaspias      Italian_North.DG  0.132     0.00351
     12 Kaspias      Jordanian.DG      0.141     0.00279
     13 Kaspias      Mansi.DG          0.156     0.00283
     14 Kaspias      Polish.DG         0.135     0.00354
     15 Kaspias      Russian.DG        0.134     0.00293
     16 Kaspias      Tatar_Tomsk.SG    0.142     0.00294
     17 Kaspias      Turkish_1.DG      0.145     0.00381
     18 Kaspias      Turkish_2.DG      0.132     0.00348
     19 Kaspias      Turkmen.SG        0.135     0.00297
     20 Kaspias      Tuscan_1.DG       0.134     0.00296
     21 Kaspias      Uzbek.SG          0.140     0.00272
    I do not get, how can I be closer to French and Adygei than Albanians? The rest seems ok though.


    Problem with modern people who identify as French is they may have recent N. African or other European ancestors. That aside since the default in Admixtools is to use common and less common alleles in calculations ENF in Europeans and W. Asians confounds results because it was so successful and Europeans and W. Asians have alot of it.

    I have found that when I exclude very common alleles from analysis you have less of those sorts of problems due to ENF in Italians and French. Default in Admixtools is to use all alleles subject to maxmiss meaning that if an allele has a MAF of 0.50 it is still used. MAF 0.50 means that minor or ALT allele is found in all your pops in the analysis whether African, Asian or European meaning if "T" is the minor allele at that position then all Africans and Eurasians in your analysis are "T" at that position.

    If you want to exclude these very ancient common alleles from your analysis set maxmaf=0.4 or 0.3 and then rerun. I'm pretty sure you wont get French or British or whatever having a small distance to you because of shared ENF or EHG.

  10. #120
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    Quote Originally Posted by Kaspias View Post

    I get negative scores when used Turkish samples to model my Turkic part, which might mean Turkic ancestors of Balkan Turks were not Anatolian Turkish-like.

    Code:
    	target	left	weight	se	z
    1	Kaspias	Bulgarian_1.DG	1.04	5.3	0.2
    2	Kaspias	Turkish_1.DG	-0.04	5.3	-0.01
    
    
    	f4rank	dof	chisq	p.value	dofdiff	chisqdiff	p_nested
    1	1	8	28.18	0.00044187	10	36.1	0.000081
    2	0	18	64.28	4.09e-07
    [CODE]

    target left weight se z
    1 Kaspias Bulgarian_1.DG 11.44 364.26 0.031
    2 Kaspias Turkish_2.DG -10.44 364.26 -0.029
    Yes, so basically its saying that Bulgarians already have alot of the Turkish type admixture you don't need additional Turkish to model yourself. Besides your SE get huge like with you at 1000% if you use 2 similar pops like that

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