Steppe Ancestry in western Eurasia and the spread of the Germanic Languages

[Orentil]

There were Warini mentioned at the Rhine, too. Check it.

[Dewsloth]

The Z18 and I1 samples plot in the middle of the Häven group on PCA, they do not seem to be outliers on north, northwest or euro settings. 

G25:

Code:

DEU_Haven_200-400AD:HVN001,0.10990361402700001,0.12453465816,0.0 627894307006,0.05215176817900013,0.0383427308844,0 .016404900294699994,-0.001740455004000019,-0.0002167138480000429,0.005390679285999937,-0.00513852113299997,-0.00539601885144,0.0033978041600000084,-0.008416857423000003,-0.002296032078999921,0.016471557031,0.002559941360 000084,-0.009299611295000032,0.0012637804370001261,0.00381 9565805999985,0.00016728210700000477,0.00326855842 3000164,0.0012568647889999243,0.000876606590000002 ,0.012283394073000038,0.00023694323199962078
DEU_Haven_200-400AD:HVN002,0.11888975485600012,0.11684840955,0.0 6454872643779998,0.06362469542200003,0.03497187241 3,0.023642579956539993,0.003094592047000015,0.0057 43314964000101,0.003949829753999899,-0.009187394097000305,-0.00469051139396,0.0036486393579999755,-0.009661576312999999,-0.012450842319999864,0.027196042113000037,0.010309 067680000155,-0.011454477706000086,0.002059779223000102,0.002895 9384650000036,0.003453262115000008,0.0071336125530 00185,0.0021153296130000457,0.0005652457279999804, 0.013886730021999942,0.001763449987999724
DEU_Haven_200-400AD:HVN003,0.11988540071799998,0.108798512756999 99,0.07028789048560004,0.061382675771999726,0.0272 50579715600007,0.02004919215709999,0.0059725944280 00024,0.011027296733000064,0.005698178139999718,-0.0071359062399996495,0.004196979594120001,0.00051 93240549999957,-0.0011761021180000236,-0.03324865219399963,0.01112743029099983,0.00160537 94520000438,-0.007075810915000095,-0.0012092602529999007,-0.007351572866999993,-0.002596312009000003,0.003562883665000016,0.013094 22137899984,-0.004961145419000038,0.009569700263000056,-0.0028174290830001465
DEU_Haven_200-400AD:HVN004,0.11723702177700022,0.119442474108999 98,0.06333712129079998,0.06415555437699974,0.03891 417002200001,0.022051100404059984,0.00230060724700 00147,0.005346456256000012,0.008851213119999923,-0.004795090314000026,-0.007548705709979999,0.004585485696000024,-0.008659786489000003,-0.008582609877999872,0.022736330446000014,0.008055 166853000008,-0.00783358275000002,0.001107550464000042,0.0005360 998699999813,0.004824639134999998,0.00758678425000 0055,0.003781278055999952,-0.0010504854420000254,0.014577585900999973,-0.00010867628800004941
DEU_Haven_200-400AD:HVN005,0.13268343987200015,0.129930678434000 02,0.0701496152346,0.05723021177199977,0.040703520 879000005,0.021568735485299993,0.00229100938600003 4,0.0038937801280000683,0.004391650136000014,-0.003029867500000172,-0.0057818953259,0.0036230321259999865,-0.009222788595999988,-0.008103209379999754,0.022716520806000007,0.007808 651912000031,-0.009104464468000062,0.002219253095999879,0.003069 327908000012,0.004458088221999997,0.00550387783199 9904,0.002366415934000138,0.0013089528719999813,0. 01559037349200007,0.0003673756799997263
DEU_Haven_200-400AD:HVN006,0.1252687865670001,0.122508567536,0.0 6810866728360002,0.05999353570899969,0.03370160092 1000004,0.023017574169359997,0.00338204194400005,0 .0022591317890000087,-0.0009010048940003221,-0.012136344278999964,-0.006207524058352002,0.0033655294169999857,-0.008661159479000008,-0.008354800364999953,0.025143075572999975,0.007829 454094999983,-0.007337535674000007,0.003061370954999892,0.001903 8012669999975,0.00647093244399999,0.00596577240600 0101,0.0034126699979999133,0.001849128226999984,0. 018103271210999958,-0.0003624655150001057
DEU_Haven_200-400AD:HVN007,0.12594778796300024,0.131223159927,0. 0639846448218,0.05217685949500019,0.04182159768800 001,0.01666414181518,0.005409915519999966,0.007276 982762000243,0.005507489966999905,-0.0019772778449997303,-0.005555183471079999,0.003216124780999982,-0.008056901458999984,-0.006832459808999611,0.018718726128000025,0.007834 745995999964,-0.005094416196999995,0.0016745559309999953,0.00270 24602410000405,0.005064884613799987,0.005077461520 000147,0.0008576602909998636,0.0018840991499999265 ,0.011843825369999988,0.0013531249539998468
DEU_Haven_200-400AD:HVN008,0.1253982141650001,0.1039075476629999 9,0.0539648795988,0.053683096779000065,0.038067775 415000005,0.016789448925300002,0.00032902312400005 275,-0.0005472765359999694,-0.0005798783679999628,-0.0034508394980000013,-0.007383230133879999,0.005971777421000064,-0.010418333903999996,-0.01658582966399999,0.0235704281769998,0.007413009 505000166,-0.008577444030000086,0.0022902711330001664,0.00093 15454409999865,0.00171273254699999,0.0053830484540 001704,0.006152236554000003,0.0007703222570000241, 0.019584362006000007,-0.002287958745999826
DEU_Haven_200-400AD:HVN010,0.12095293711399993,0.122311868814,0. 06144392617620003,0.0588649172740001,0.03539027018 799999,0.023972466635419985,0.0049183448409999804, 0.006961356421000143,0.0021655190500000296,-0.007963407506999899,-0.006220761019392,0.00478708700300003,-0.009417260598999999,-0.010122292543999808,0.02640059121300025,0.0087402 20029000184,-0.010884387823,0.0018922904530000208,0.00239853636 99999887,0.004296973611200007,0.007630741891000031 ,0.0023837681969999906,0.0008981193589999957,0.011 723641354999963,0.0016142274050000086

[Rodoorn]

The Z18 and I1 samples plot in the middle of the Häven group on PCA, they do not seem to be outliers on north, northwest or euro settings. 

G25:

Code:

DEU_Haven_200-400AD:HVN001,0.10990361402700001,0.12453465816,0.0 627894307006,0.05215176817900013,0.0383427308844,0 .016404900294699994,-0.001740455004000019,-0.0002167138480000429,0.005390679285999937,-0.00513852113299997,-0.00539601885144,0.0033978041600000084,-0.008416857423000003,-0.002296032078999921,0.016471557031,0.002559941360 000084,-0.009299611295000032,0.0012637804370001261,0.00381 9565805999985,0.00016728210700000477,0.00326855842 3000164,0.0012568647889999243,0.000876606590000002 ,0.012283394073000038,0.00023694323199962078
DEU_Haven_200-400AD:HVN002,0.11888975485600012,0.11684840955,0.0 6454872643779998,0.06362469542200003,0.03497187241 3,0.023642579956539993,0.003094592047000015,0.0057 43314964000101,0.003949829753999899,-0.009187394097000305,-0.00469051139396,0.0036486393579999755,-0.009661576312999999,-0.012450842319999864,0.027196042113000037,0.010309 067680000155,-0.011454477706000086,0.002059779223000102,0.002895 9384650000036,0.003453262115000008,0.0071336125530 00185,0.0021153296130000457,0.0005652457279999804, 0.013886730021999942,0.001763449987999724
DEU_Haven_200-400AD:HVN003,0.11988540071799998,0.108798512756999 99,0.07028789048560004,0.061382675771999726,0.0272 50579715600007,0.02004919215709999,0.0059725944280 00024,0.011027296733000064,0.005698178139999718,-0.0071359062399996495,0.004196979594120001,0.00051 93240549999957,-0.0011761021180000236,-0.03324865219399963,0.01112743029099983,0.00160537 94520000438,-0.007075810915000095,-0.0012092602529999007,-0.007351572866999993,-0.002596312009000003,0.003562883665000016,0.013094 22137899984,-0.004961145419000038,0.009569700263000056,-0.0028174290830001465
DEU_Haven_200-400AD:HVN004,0.11723702177700022,0.119442474108999 98,0.06333712129079998,0.06415555437699974,0.03891 417002200001,0.022051100404059984,0.00230060724700 00147,0.005346456256000012,0.008851213119999923,-0.004795090314000026,-0.007548705709979999,0.004585485696000024,-0.008659786489000003,-0.008582609877999872,0.022736330446000014,0.008055 166853000008,-0.00783358275000002,0.001107550464000042,0.0005360 998699999813,0.004824639134999998,0.00758678425000 0055,0.003781278055999952,-0.0010504854420000254,0.014577585900999973,-0.00010867628800004941
DEU_Haven_200-400AD:HVN005,0.13268343987200015,0.129930678434000 02,0.0701496152346,0.05723021177199977,0.040703520 879000005,0.021568735485299993,0.00229100938600003 4,0.0038937801280000683,0.004391650136000014,-0.003029867500000172,-0.0057818953259,0.0036230321259999865,-0.009222788595999988,-0.008103209379999754,0.022716520806000007,0.007808 651912000031,-0.009104464468000062,0.002219253095999879,0.003069 327908000012,0.004458088221999997,0.00550387783199 9904,0.002366415934000138,0.0013089528719999813,0. 01559037349200007,0.0003673756799997263
DEU_Haven_200-400AD:HVN006,0.1252687865670001,0.122508567536,0.0 6810866728360002,0.05999353570899969,0.03370160092 1000004,0.023017574169359997,0.00338204194400005,0 .0022591317890000087,-0.0009010048940003221,-0.012136344278999964,-0.006207524058352002,0.0033655294169999857,-0.008661159479000008,-0.008354800364999953,0.025143075572999975,0.007829 454094999983,-0.007337535674000007,0.003061370954999892,0.001903 8012669999975,0.00647093244399999,0.00596577240600 0101,0.0034126699979999133,0.001849128226999984,0. 018103271210999958,-0.0003624655150001057
DEU_Haven_200-400AD:HVN007,0.12594778796300024,0.131223159927,0. 0639846448218,0.05217685949500019,0.04182159768800 001,0.01666414181518,0.005409915519999966,0.007276 982762000243,0.005507489966999905,-0.0019772778449997303,-0.005555183471079999,0.003216124780999982,-0.008056901458999984,-0.006832459808999611,0.018718726128000025,0.007834 745995999964,-0.005094416196999995,0.0016745559309999953,0.00270 24602410000405,0.005064884613799987,0.005077461520 000147,0.0008576602909998636,0.0018840991499999265 ,0.011843825369999988,0.0013531249539998468
DEU_Haven_200-400AD:HVN008,0.1253982141650001,0.1039075476629999 9,0.0539648795988,0.053683096779000065,0.038067775 415000005,0.016789448925300002,0.00032902312400005 275,-0.0005472765359999694,-0.0005798783679999628,-0.0034508394980000013,-0.007383230133879999,0.005971777421000064,-0.010418333903999996,-0.01658582966399999,0.0235704281769998,0.007413009 505000166,-0.008577444030000086,0.0022902711330001664,0.00093 15454409999865,0.00171273254699999,0.0053830484540 001704,0.006152236554000003,0.0007703222570000241, 0.019584362006000007,-0.002287958745999826
DEU_Haven_200-400AD:HVN010,0.12095293711399993,0.122311868814,0. 06144392617620003,0.0588649172740001,0.03539027018 799999,0.023972466635419985,0.0049183448409999804, 0.006961356421000143,0.0021655190500000296,-0.007963407506999899,-0.006220761019392,0.00478708700300003,-0.009417260598999999,-0.010122292543999808,0.02640059121300025,0.0087402 20029000184,-0.010884387823,0.0018922904530000208,0.00239853636 99999887,0.004296973611200007,0.007630741891000031 ,0.0023837681969999906,0.0008981193589999957,0.011 723641354999963,0.0016142274050000086

Indeed my quest is Dewsloth, if HVN  was the only source population for the Saxons around the North Sea. Or played the Zealand IA ancestry also a part. Last one is denied by the paper.

In G25 I get mixed results.

For Midlum/ Friesland



And for Groningen


Mark that for Groningen this is partly way beyond migration time. And these are graves from along the Martini tower in the center of the city, elite graves.

But anyhow very mixed results!

[Anglesqueville]

Rodoorn, after a lot of trial and error I arrived at a model (for your dad) that closely resembles the one you propose in your post #340:
Transversions + transitions

left pops:
finndad
Denmark_IA.imputed_Allentoft_VK582
Schleswig-Holstein

right pops:
Russia_Ust_Ishim.DG
Cameroon_SMA.DG
Italy_North_Villabruna_HG
Czech_Vestonice16
Belgium_UP_GoyetQ116_1
Russia_MA1_HG.SG
Iran_GanjDareh_N
Russia_Kostenki14.SG
Indian_GreatAndaman_100BP.SG
Israel_PPNB
Georgia_Kotias.SG
Turkey_N_I0707
Ukraine_Yamnaya


best coefficients: 0.495 0.505
totmean: 0.495 0.505
boot mean: 0.492 0.508
std. errors: 0.486 0.486


fixed pat wt dof chisq tail prob
00 0 11 6.173 0.861572 0.495 0.505
01 1 12 11.864 0.456686 1.000 0.000
10 1 12 14.987 0.242128 0.000 1.000
best pat: 00 0.861572 - -
best pat: 01 0.456686 chi(nested): 5.691 p-value for nested model: 0.0170554

As it is good policy when the target is modern and the sources ancient to keep only the transversions, when possible, here is the corresponding model without the transitions:

best coefficients: 0.698 0.302
totmean: 0.698 0.302
boot mean: 0.911 0.089
std. errors: 5.816 5.816


fixed pat wt dof chisq tail prob
00 0 11 5.354 0.912793 0.698 0.302
01 1 12 5.914 0.920333 1.000 0.000
10 1 12 11.402 0.494846 0.000 1.000
best pat: 00 0.912793 - -
best pat: 01 0.920333 chi(nested): 0.560 p-value for nested model: 0.454269

The optimists will say "wow, it's the same coefficients as G25!" I will tell them to look at the standard errors.

edit: in the model with transversions only the nested model (as "pure" VK582) passes with an excellent p-value. But not in the model with all SNPs. Why? Not the same SNPs panel > not necessarily the same stats. That's life.

[Dewsloth]

Speaking of Saxons and the North Sea, FWIW the two DF19s are about an even 50/50 split while the two U106s lean more Haven. 
Might be a total coincidence:

Target: Germany_Hiddestorf_Saxon_EMedieval:HID001.A_noUDG
Distance: 2.0099% / 0.02009871
50.8 DEU_Haven_200-400AD
49.2 Denmark_IA.SG

Target: Germany_Hiddestorf_Saxon_EMedieval:HID002.A_noUDG
Distance: 2.5127% / 0.02512696
50.4 Denmark_IA.SG
49.6 DEU_Haven_200-400AD

Target: Germany_Hiddestorf_Saxon_EMedieval:HID003_noUDG
Distance: 3.1336% / 0.03133638
98.6 DEU_Haven_200-400AD
1.4 Denmark_IA.SG

Target: Germany_Hiddestorf_Saxon_EMedieval:HID004_noUDG
Distance: 2.6021% / 0.02602121
76.6 DEU_Haven_200-400AD
23.4 Denmark_IA.SG

Edit - Here is unaggregated:

Show Content

Spoiler
Target: Germany_Hiddestorf_Saxon_EMedieval:HID001.A_noUDG
Distance: 2.0099% / 0.02009871
45.0 DEU_Haven_200-400AD:HVN007
38.4 Denmark_IA.SG:VK521_noUDG.SG
10.8 Denmark_IA.SG:VK532_noUDG.SG
4.0 DEU_Haven_200-400AD:HVN005
1.8 DEU_Haven_200-400AD:HVN003

Target: Germany_Hiddestorf_Saxon_EMedieval:HID002.A_noUDG
Distance: 2.5127% / 0.02512696
50.4 Denmark_IA.SG:VK521_noUDG.SG
32.2 DEU_Haven_200-400AD:HVN010
12.8 DEU_Haven_200-400AD:HVN006
4.6 DEU_Haven_200-400AD:HVN001

Target: Germany_Hiddestorf_Saxon_EMedieval:HID003_noUDG
Distance: 3.1336% / 0.03133638
62.8 DEU_Haven_200-400AD:HVN006
35.6 DEU_Haven_200-400AD:HVN005
1.4 Denmark_IA.SG:VK521_noUDG.SG
0.2 DEU_Haven_200-400AD:HVN003

Target: Germany_Hiddestorf_Saxon_EMedieval:HID004_noUDG
Distance: 2.6021% / 0.02602121
29.4 DEU_Haven_200-400AD:HVN005
23.4 Denmark_IA.SG:VK532_noUDG.SG
20.6 DEU_Haven_200-400AD:HVN007
19.2 DEU_Haven_200-400AD:HVN003
7.4 DEU_Haven_200-400AD:HVN004

[NewEnglander]

The Z18 and I1 samples plot in the middle of the Häven group on PCA, they do not seem to be outliers on north, northwest or euro settings. 

G25:

Code:

DEU_Haven_200-400AD:HVN001,0.10990361402700001,0.12453465816,0.0 627894307006,0.05215176817900013,0.0383427308844,0 .016404900294699994,-0.001740455004000019,-0.0002167138480000429,0.005390679285999937,-0.00513852113299997,-0.00539601885144,0.0033978041600000084,-0.008416857423000003,-0.002296032078999921,0.016471557031,0.002559941360 000084,-0.009299611295000032,0.0012637804370001261,0.00381 9565805999985,0.00016728210700000477,0.00326855842 3000164,0.0012568647889999243,0.000876606590000002 ,0.012283394073000038,0.00023694323199962078
DEU_Haven_200-400AD:HVN002,0.11888975485600012,0.11684840955,0.0 6454872643779998,0.06362469542200003,0.03497187241 3,0.023642579956539993,0.003094592047000015,0.0057 43314964000101,0.003949829753999899,-0.009187394097000305,-0.00469051139396,0.0036486393579999755,-0.009661576312999999,-0.012450842319999864,0.027196042113000037,0.010309 067680000155,-0.011454477706000086,0.002059779223000102,0.002895 9384650000036,0.003453262115000008,0.0071336125530 00185,0.0021153296130000457,0.0005652457279999804, 0.013886730021999942,0.001763449987999724
DEU_Haven_200-400AD:HVN003,0.11988540071799998,0.108798512756999 99,0.07028789048560004,0.061382675771999726,0.0272 50579715600007,0.02004919215709999,0.0059725944280 00024,0.011027296733000064,0.005698178139999718,-0.0071359062399996495,0.004196979594120001,0.00051 93240549999957,-0.0011761021180000236,-0.03324865219399963,0.01112743029099983,0.00160537 94520000438,-0.007075810915000095,-0.0012092602529999007,-0.007351572866999993,-0.002596312009000003,0.003562883665000016,0.013094 22137899984,-0.004961145419000038,0.009569700263000056,-0.0028174290830001465
DEU_Haven_200-400AD:HVN004,0.11723702177700022,0.119442474108999 98,0.06333712129079998,0.06415555437699974,0.03891 417002200001,0.022051100404059984,0.00230060724700 00147,0.005346456256000012,0.008851213119999923,-0.004795090314000026,-0.007548705709979999,0.004585485696000024,-0.008659786489000003,-0.008582609877999872,0.022736330446000014,0.008055 166853000008,-0.00783358275000002,0.001107550464000042,0.0005360 998699999813,0.004824639134999998,0.00758678425000 0055,0.003781278055999952,-0.0010504854420000254,0.014577585900999973,-0.00010867628800004941
DEU_Haven_200-400AD:HVN005,0.13268343987200015,0.129930678434000 02,0.0701496152346,0.05723021177199977,0.040703520 879000005,0.021568735485299993,0.00229100938600003 4,0.0038937801280000683,0.004391650136000014,-0.003029867500000172,-0.0057818953259,0.0036230321259999865,-0.009222788595999988,-0.008103209379999754,0.022716520806000007,0.007808 651912000031,-0.009104464468000062,0.002219253095999879,0.003069 327908000012,0.004458088221999997,0.00550387783199 9904,0.002366415934000138,0.0013089528719999813,0. 01559037349200007,0.0003673756799997263
DEU_Haven_200-400AD:HVN006,0.1252687865670001,0.122508567536,0.0 6810866728360002,0.05999353570899969,0.03370160092 1000004,0.023017574169359997,0.00338204194400005,0 .0022591317890000087,-0.0009010048940003221,-0.012136344278999964,-0.006207524058352002,0.0033655294169999857,-0.008661159479000008,-0.008354800364999953,0.025143075572999975,0.007829 454094999983,-0.007337535674000007,0.003061370954999892,0.001903 8012669999975,0.00647093244399999,0.00596577240600 0101,0.0034126699979999133,0.001849128226999984,0. 018103271210999958,-0.0003624655150001057
DEU_Haven_200-400AD:HVN007,0.12594778796300024,0.131223159927,0. 0639846448218,0.05217685949500019,0.04182159768800 001,0.01666414181518,0.005409915519999966,0.007276 982762000243,0.005507489966999905,-0.0019772778449997303,-0.005555183471079999,0.003216124780999982,-0.008056901458999984,-0.006832459808999611,0.018718726128000025,0.007834 745995999964,-0.005094416196999995,0.0016745559309999953,0.00270 24602410000405,0.005064884613799987,0.005077461520 000147,0.0008576602909998636,0.0018840991499999265 ,0.011843825369999988,0.0013531249539998468
DEU_Haven_200-400AD:HVN008,0.1253982141650001,0.1039075476629999 9,0.0539648795988,0.053683096779000065,0.038067775 415000005,0.016789448925300002,0.00032902312400005 275,-0.0005472765359999694,-0.0005798783679999628,-0.0034508394980000013,-0.007383230133879999,0.005971777421000064,-0.010418333903999996,-0.01658582966399999,0.0235704281769998,0.007413009 505000166,-0.008577444030000086,0.0022902711330001664,0.00093 15454409999865,0.00171273254699999,0.0053830484540 001704,0.006152236554000003,0.0007703222570000241, 0.019584362006000007,-0.002287958745999826
DEU_Haven_200-400AD:HVN010,0.12095293711399993,0.122311868814,0. 06144392617620003,0.0588649172740001,0.03539027018 799999,0.023972466635419985,0.0049183448409999804, 0.006961356421000143,0.0021655190500000296,-0.007963407506999899,-0.006220761019392,0.00478708700300003,-0.009417260598999999,-0.010122292543999808,0.02640059121300025,0.0087402 20029000184,-0.010884387823,0.0018922904530000208,0.00239853636 99999887,0.004296973611200007,0.007630741891000031 ,0.0023837681969999906,0.0008981193589999957,0.011 723641354999963,0.0016142274050000086

Could be indicative of an older Jastorf movement of R-Z18 and I1 into that area.

[Rodoorn]

Rodoorn, after a lot of trial and error I arrived at a model (for your dad) that closely resembles the one you propose in your post #340:
Transversions + transitions

left pops:
finndad
Denmark_IA.imputed_Allentoft_VK582
Schleswig-Holstein

right pops:
Russia_Ust_Ishim.DG
Cameroon_SMA.DG
Italy_North_Villabruna_HG
Czech_Vestonice16
Belgium_UP_GoyetQ116_1
Russia_MA1_HG.SG
Iran_GanjDareh_N
Russia_Kostenki14.SG
Indian_GreatAndaman_100BP.SG
Israel_PPNB
Georgia_Kotias.SG
Turkey_N_I0707
Ukraine_Yamnaya


best coefficients: 0.495 0.505
totmean: 0.495 0.505
boot mean: 0.492 0.508
      std. errors: 0.486 0.486


fixed pat wt dof chisq tail prob
            00 0 11 6.173 0.861572 0.495 0.505
            01 1 12 11.864 0.456686 1.000 0.000
            10 1 12 14.987 0.242128 0.000 1.000
best pat: 00 0.861572 - -
best pat: 01 0.456686 chi(nested): 5.691 p-value for nested model: 0.0170554

As it is good policy when the target is modern and the sources ancient to keep only the transversions, when possible, here is the corresponding model without the transitions:

best coefficients:    0.698    0.302
totmean:      0.698    0.302
boot mean:    0.911    0.089
      std. errors:    5.816    5.816
     
     
fixed pat  wt  dof    chisq      tail prob
          00  0    11    5.354        0.912793    0.698    0.302
          01  1    12    5.914        0.920333    1.000    0.000
          10  1    12    11.402        0.494846    0.000    1.000
best pat:          00        0.912793              -  -
best pat:          01        0.920333  chi(nested):    0.560 p-value for nested model:        0.454269

The optimists will say "wow, it's the same coefficients as G25!" I will tell them to look at the standard errors.

edit: in the model with transversions only the nested model (as "pure" VK582) passes with an excellent p-value. But not in the model with all SNPs. Why? Not the same SNPs panel > not necessarily the same stats. That's life.

great thanks for time and effort!

[NewEnglander]

I wonder if it's possible that some of the settlement of Scandinavians in the Danelaw and Normandy could be from the older inhabitants of the Danish Isles and Scania fleeing the influx of the new Danes and centralization under the Jelling Dynasty, perhaps in a similar manner to Iceland being settled by people fleeing the centralization of Norway under Harald Fairhair. I also think of the Jomsvikings, perhaps it was a situation similar to the Heruli wandering around as armed bands after being pushed out and the later Anglo-Saxon emigrants to Byzantium, but that may be a stretch.

[Anglesqueville]

I wonder if it's possible that some of the settlement of Scandinavians in the Danelaw and Normandy could be from the older inhabitants of the Danish Isles and Scania fleeing the influx of the new Danes and centralization under the Jelling Dynasty, perhaps in a similar manner to Iceland being settled by people fleeing the centralization of Norway under Harald Fairhair. I also think of the Jomsvikings, perhaps it was a situation similar to the Heruli wandering around as armed bands after being pushed out and the later Anglo-Saxon emigrants to Byzantium, but that may be a stretch.

About Normandy, the doctrine is that only men settled there. The problem is that some toponyms contain women's names (the best known is Tove), and that especially among the countless Scandinavian words that have penetrated local dialects, many refer to objects or occupations that were affairs of women, not of warriors. The answer to this problem is that presumably most of the people who settled in our countryside were children or grandchildren of Scandinavian settlers from England. So in the end your question essentially concerns the Danelaw, and Normandy only indirectly.

edit: I add that I am not at all convinced by the Doxa, which is based only on period texts, which only know the men who in the cities integrated into feudal structures to found the aristocracy of the new duchy. In short, these texts ignore everything that was happening elsewhere.

[Rodoorn]

Back to the text of the paper.

I concentrate on the Danish Isles IA ancestry and the question if it is a a possible source for influx of Anglo Saxons around the North Sea about 400 AD>.


"With representatives of each of the additional northern European Bronze Age source clusters, we resolve in more detail the extent of a previously documented expansion of Eastern Scandinavian ancestry 59,60. By the Iron Age in Scandinavia, almost all individuals are modelled with >50% Eastern Scandinavian ancestry. The impact of this expansion is most apparent on the Danish Islands, followed by Norway (Supplementary Note S6.9.4) and finally the Danish peninsula of Jutland (Figure 5)."

We see these respective proportions of Southern and Eastern Scandinavian Bronze Age ancestry persist throughout the Iron Age (2800 – 1575 BP) in Jutland, the Danish Isles and Southern Sweden. In Jutland during the Iron Age, individuals tend to fall within the Southern Scandinavian cluster (Figure 6), and are modelled with ~55% Southern and ~45% Eastern Scandinavian BA (Figure 5). Further east, individuals fall within the Eastern Scandinavian cluster; on the Danish Isles individuals are modelled as ~20% Southern and ~80% Eastern Scandinavian BA and in Sweden most individuals are modelled as ~100% Eastern Scandinavian BA (Figure 5).

By including the two Iron Age Southern Scandinavian clusters in the sources (Jutland and Mecklenburg) together with two Iron Age Eastern Scandinavian clusters (Danish Isles and Sweden), we are able to further disentangle these migrations (Extended Data Figure 11). The Danish Isles ancestry that was widespread on Zealand from 2200 BP disappears from ~1600 BP. For the few samples between 1600 BP and 1230 BP we find instead a variety of ancestries, Swedish Iron Age, Celtic Iron Age, Norwegian Iron Age, and Jutlandic (check) Iron Age. In Northern Jutland, this additional resolution reveals a transition within the constant proportion Bronze Age Southern Scandinavian ancestry. Prior to 1600 BP it ismodelled as North Jutlandic IA ancestry, which gradually shifts to become primarily modelled as North German IA ancestry. Small proportions of Jutlandic IA ancestry are modelled in many later individuals, which is in direct contrast to Zealand, where it appears a population replacement occurred.


The arrival of northern continental European ancestry during the Saxon period in England from a broad region ranging from the Netherlands to Southern Sweden has previously been shown 47. Here we find almost all samples from England fall within the Southern Scandinavian clusters, restricting the range from the Netherlands to Jutland (Extended Data Figure 7). By adding a second Iron Age Southern Scandinavian source from Mecklenburg,Northern Germany, we are able to distinguish between the two Southern Scandinavian IA sources, allowing us to restrict this range further (Extended Data Figure 7). 

We find Southern Scandinavian ancestry in almost all Saxons from England, Frisians from the Netherlands and Iron Age Germans to be modelled as the Northern German source. 

Interestingly, the distribution of those two closely related ancestries largely resembles that of the two lineages of the dominant R1b Y-chromosome in the region (Supplemental Section 6.6.4.2). In contrast, individuals from Northern Jutland are modelled primarily as the local Southern Scandinavian IA ancestry

Dutch coastal areas see a habitation hiatus around 1600 BP andsubsequent appearance of a new material culture that is often referred to as Anglo-Saxon in nature 82, mirroring the genetics and timing of the Late Iron Age, linguistically West- Germanic Frisians in this dataset. In addition, we find that the Southern Scandinavian ancestry of these migrating populations is better modelled by individuals near Southern rather than the Northern Jutland, and that the migrating populations often carry varying but minor proportions of ENS ancestry, inherited from the earlier people who previously lived in the region. 

In contrast to previous studies, which relied on Scandinavian samples postdating the Migration Period 47, we can now reject the Danish Isles and Sweden as a source area for the Anglo-Saxons in Britain, as these were dominated by Eastern Scandinavian ancestry prior to the Viking Age (Figure 6).

We can put big question marks behind the last statement. There is literaly stated we can reject the Danish Isles ancestry (= the one previous 400 AD!) because they were dominated by eastern Scandinavian ancestry prior to the Viking age.

The claim is that we see only Southern Scandic ancestry in EMA English and Frisians. In the case Southern Scandic ancestry is seen as from Northern Germany (Mecklenburg) and from Southern Jutland.

Why is this not valid?

- samples from Midlum Friesland (EMA) and Groningen (EMA) show in G25 no unsino preference for Southern Scandic ancestry as transmitted by Northern Germans (Häven, Mecklenburg) many 'prefer' Danish Isles IA (80% Eastern Scandic).
- the Saxon ancestry in the form of modern North Dutch population (in casu the Rodoorn's) are according to a Qpadm "pure Danish Isles IA" and show also a 70 vs 30 % preference between Danish Isles IA and Hidestorf (North Germany) or Danish Isles IA and Schleswig(North Germany).
- the timing is perfect: the disappearance of the Danish Isles IA ancestry about 400 AD> correspondences perfect with a Saxon appearance around the North Sea.
- after the migration period there is no major influx of people with a big East Scandic cluster component, along the continental North Sea Coast, so it must be brought in during migration time.

Conclusion: the paper has needles written off Danish Isles IA ancestry as a source for the Anglo-Saxons around the North Sea.



bb

[Cejo]

"For the previously detected major migrations in Europe, the use of f-statistics have been
sufficient to confirm demographic transitions between deeply divergent populations.
However here, the migrations in question here are between populations that are much more
closely related, making these tools unsuitable. As such, we instead explored the genomic
affinities between all the individuals in the entire dataset using the identity-by-descent (IBD)
hierarchical clustering method and mixture modelling described in 60 which is particularly
powerful for discerning closely related genomic ancestries."

Can someone with a firm understanding of the different strengths and weaknesses of these different analysis methods provide a little insight on this, or point out some reading material?

What makes IBD more suitable than f-statistics in this case (closely related populations)? How does G25 work, and how does it compare performance-wise in this kind of situation?

I am inclined to believe the authors on this point, but without better understanding, I am uncertain.

[Rodoorn]

I wonder if it's possible that some of the settlement of Scandinavians in the Danelaw and Normandy could be from the older inhabitants of the Danish Isles and Scania fleeing the influx of the new Danes and centralization under the Jelling Dynasty, perhaps in a similar manner to Iceland being settled by people fleeing the centralization of Norway under Harald Fairhair. I also think of the Jomsvikings, perhaps it was a situation similar to the Heruli wandering around as armed bands after being pushed out and the later Anglo-Saxon emigrants to Byzantium, but that may be a stretch.

I personally think the collaps of the Gudme realm- and the expel of Danish Isles IA ancestry- is due to the Scyldingas in Lerje. We see during the fifth century a decline of Gudme (became smaller, initial it was 100 ha!) in the sixth century it was turned into ashes....( small proportions) and with the fall of Gudme the star of Lerje rised. This central place was most probably the seat of the Scydlingas, they played also a part in Beowulf.

https://www.researchgate.net/publication..._and_Lejre

https://www.medieval.eu/the-great-halls-...cyldingas/

https://aelfwerasa.tripod.com/myth/scyld.htm

[Rodoorn]

Danish Isles IA ancestry?



From Jim Grant et al (2015)

Where is Jonik?

[Orentil]

As the paper is using "Mecklenburg" as a reference it would also be interesting to understand better the population dynamics in Mecklenburg-Vorpommern during the migration period.
There had just been a presentation by Hans-Ulrich Voß in January 2024, "Kontinuität und Wandel: Die Völkerwanderungszeit im Licht neuer Funde". I would have loved to visit it but it was to far away.

From the abstract:
"Die Völkerwanderungszeit in Mecklenburg-Vorpommern galt in der archäologischen Forschung lange als Epoche der Abwanderung und des weitgehenden Besiedlungsabbruches...Zahlreiche Neuentdeckungen und Ausgrabungen von Gräbern, Siedlungen und Hort- sowie Gewässerfunden zeigen nun im Verein mit einer Vielzahl von Metallfunden ein neues, wesentlich differenzierteres Bild der hier bis in das 7. Jahrhundert n. Chr. Hinein ansässigen, weiträumig vernetzten Bevölkerungsgruppen."
"In archaeological research, the migration period in Mecklenburg-Western Pomerania has long been considered an era of migration and extensive demolition of settlement... Numerous new discoveries and excavations of graves, settlements and hoards and water finds, together with a large number of metal finds, now show a new, much more differentiated Image of the widely networked population groups that lived here until the 7th century AD."

https://www.auf-nach-mv.de/veranstaltung...ommern,Chr.

I just ordered a copy of the brand new issue of "Archäologie in Deutschland" with the title "Völkerwanderungszeit im Norden" (of Germany) with articles about Schleswig-Holstein, Brandenburg, Mecklenburg-Vorpommern during the migration period. https://wbg-zeitschriften.de/produkt/voe...im-norden/
This journal is rather in a popular scientific style and the articles are rather short but the authors are well known archaeologists. Let's see if there is something relevant for our discussion topics. If yes, I will report it here.

[Rodoorn]

"For the previously detected major migrations in Europe, the use of f-statistics have been
sufficient to confirm demographic transitions between deeply divergent populations.
However here, the migrations in question here are between populations that are much more
closely related, making these tools unsuitable. As such, we instead explored the genomic
affinities between all the individuals in the entire dataset using the identity-by-descent (IBD)
hierarchical clustering method and mixture modelling described in 60 which is particularly
powerful for discerning closely related genomic ancestries."

Can someone with a firm understanding of the different strengths and weaknesses of these different analysis methods provide a little insight on this, or point out some reading material?

What makes IBD more suitable than f-statistics in this case (closely related populations)? How does G25 work, and how does it compare performance-wise in this kind of situation?

I am inclined to believe the authors on this point, but without better understanding, I am uncertain.

as a nitwit in these kind of matter;

https://chat.openai.com/share/f71f8b01-c...60e5f3723b