Mytrueancestry.com

Below, my best match with ancient samples, according Archaic DNA matches of GEDmatch.
It will be that Mr. mlukas think that my results, mainly the first one result, are a bullshit?

1

You must find for comparison those sample which you have as matches from MTA, like Salento with Illyrian above, to check real shared segments on Gedmatch and MTA.

For some reason they don't give you Loschbour, LBK, NE1 or BR2 samples, interesting why btw.
 
All interested here should read this:
https://isogg.org/wiki/Identical_by_descent

This is interesting, but not sure it's enough for explaining the results:
"The companies' matching algorithms do not treat the paternal and maternal chromosomes separately. Consequently consecutive SNP results for a short segment of DNA may appear to be half-identical in two individuals when in actuality the DNA sequences are not identical because the SNPs match on opposing chromosomes or because of errors in the matching algorithms. False matches can be the result of pseudosegments (matching alleles zig-zagging backwards and forwards between the maternal side and the paternal side), compound segments and fuzzy boundaries.[5][6] For a good illustration and explanation of a pseudosegment (also known as a spurious segment, an erroneous segment or a phantom segment) see Don Worth's diagram."
(...)
"False positive matches are more likely to be seen in unphased data (phasing is the process of assigning alleles to the mother or the father.) The highest degree of accuracy is achieved by using the phased data from a two-parent/one child trio, where the error rate for phasing is only 0.01%. In the absence of trio data it is possible to phase data by inference using samples from reference populations. This is known as statistical phasing, computational phasing or algorithm-based phasing. AncestryDNA is currently the only company to phase all the customer data prior to matching. Ancestry uses a proprietary phasing algorithm known as Underdog." (...)

Apparently a bit outdated article though, 'cause Ancestry is not the only one.

From the 23andMe Ancestry Composition guide (https://www.23andme.com/en-int/ancestry-composition-guide/):
"Recall wrinkle #2 above. For each customer, we measure a set of genotypes (pairs of alleles). But what we really want is a pair of haplotypes for each chromosome. That is, we want to figure out the series of alleles present on each of your two copies of, for example, chromosome 7: one you received from your mother and one you received from your father. To do so, we first build a very large "phasing reference panel" using data from hundreds of thousands of customers. We then use Eagle (Loh et al., 2016) to phase these individuals jointly. Eagle uses sophisticated statistics and a very clever algorithm to do this." (...)
 
This is what I suggested since the begining:) So everyone can see now the true matches with those ancients.

imho

In all fairness, since they are not involved in this debate yet, we should give them the benefit of the doubt.

If they're listening, they’re welcome to join and make their case. :)
 
The type of sample doesn't matter.
What matters is that:
You said:

Guys, do you really didn';t notice that?:)

This is just biggest bullshit lately on Genetic Internet...

Do you know your one-to-many list on Gematch? What is your highest match (besides close family like parents) for me about 30 cM. And Gedmatch says common ancestor was about 4.5 generation ago.

Bez-nazwy-9.png


So what the hell means if you have common 80 cM with sample from Bronze Age Jutland? (It was example from another forum, but here were also posted very high "ancient matches") How many generation ago it was? Go figure
smile.png
It is impossible and completely biased result.

8fe4d8fb-7b3d-4ec7-ab3c-6f304623d26a.png



Posting it, is like posting random numbers taken from the... Nobody can defend those cM values in two post above. Unless you believe you match 3500 years old sample on the same level as 3rd cousin...

And I say that:

Below, my best match with ancient samples, according Archaic DNA matches of GEDmatch.
It will be that Mr. mlukas think that my results, mainly the first one result, are a bullshit?

1) F999918 (Loschbour, Lux.)
Largest segment = 5.3 cM
Total of segments > 1 cM = 24.0 cM
9 matching segments

651432 SNPs used for this comparison.

Comparison took 0.18067 seconds.

ChrStart LocationEnd LocationCentimorgans (cM)SNPs
2199,959,143202,251,0811.6523


ChrStart LocationEnd LocationCentimorgans (cM)SNPs
3121,007,341124,168,8032.0639


ChrStart LocationEnd LocationCentimorgans (cM)SNPs
5168,130,883170,215,6695.3772


ChrStart LocationEnd LocationCentimorgans (cM)SNPs
793,351,34994,969,9031.7539


ChrStart LocationEnd LocationCentimorgans (cM)SNPs
1164,694,95767,174,7781.7535
1173,572,62476,549,8172.9690


ChrStart LocationEnd LocationCentimorgans (cM)SNPs
1246,523,55449,661,5851.9621


ChrStart LocationEnd LocationCentimorgans (cM)SNPs
1433,819,26336,259,8162.4509


ChrStart LocationEnd LocationCentimorgans (cM)SNPs
1934,138,10636,511,6704.4587

2) F999937 (NE1, Hungary)
Largest segment = 4.2 cM
Total of segments > 1 cM = 27.9 cM
11 matching segments

641142 SNPs used for this comparison.

Comparison took 0.24602 seconds.

ChrStart LocationEnd LocationCentimorgans (cM)SNPs
1169,174,798170,862,2471.3626



ChrStart LocationEnd LocationCentimorgans (cM)SNPs
2162,348,971165,446,1772.0522
2168,913,845170,340,1743.4513

ChrStart LocationEnd LocationCentimorgans (cM)SNPs
379,268,77485,601,2701.6815

ChrStart LocationEnd LocationCentimorgans (cM)SNPs
5141,746,135143,033,7102.6514

ChrStart LocationEnd LocationCentimorgans (cM)SNPs
679,513,94182,460,0201.2536
6164,686,566166,543,9074.2588


ChrStart LocationEnd LocationCentimorgans (cM)SNPs
78,572,78510,482,7543.9639

ChrStart LocationEnd LocationCentimorgans (cM)SNPs
817,456,62518,665,6122.6704

ChrStart LocationEnd LocationCentimorgans (cM)SNPs
10115,771,517118,305,3953.3586



3) F999916 (LBK, Stuttgart)
Largest segment = 3.9 cM
Total of segments > 1 cM = 19.9 cM
9 matching segments

647360 SNPs used for this comparison.

Comparison took 0.18539 seconds.

ChrStart LocationEnd LocationCentimorgans (cM)SNPs
196,887,63798,992,3041.6893


ChrStart LocationEnd LocationCentimorgans (cM)SNPs
266,153,16667,862,7632.2541


ChrStart LocationEnd LocationCentimorgans (cM)SNPs
348,385,37853,971,5191.8915


ChrStart LocationEnd LocationCentimorgans (cM)SNPs
5136,514,492141,052,0632.9770


ChrStart LocationEnd LocationCentimorgans (cM)SNPs
7139,186,936141,179,4032.5565



ChrStart LocationEnd LocationCentimorgans (cM)SNPs
862,167,32664,668,2641.7502

ChrStart LocationEnd LocationCentimorgans (cM)SNPs
1073,126,27476,119,8191.6511


ChrStart LocationEnd LocationCentimorgans (cM)SNPs
1137,476,11840,466,6401.9524


ChrStart LocationEnd LocationCentimorgans (cM)SNPs
2019,342,13020,932,5103.9550




4) F999933 (BR2, Hungary)
Largest segment = 2.9 cM
Total of segments > 1 cM = 13.4 cM
6 matching segments

644040 SNPs used for this comparison.

Comparison took 0.17078 seconds.

ChrStart LocationEnd LocationCentimorgans (cM)SNPs
195,792,17697,665,4461.0630

ChrStart LocationEnd LocationCentimorgans (cM)SNPs
2122,860,984126,194,2582.9700

ChrStart LocationEnd LocationCentimorgans (cM)SNPs
652,642,89054,727,6222.8649
6100,699,314103,759,0842.2513

ChrStart LocationEnd LocationCentimorgans (cM)SNPs
1230,313,33332,133,4461.7510


ChrStart LocationEnd LocationCentimorgans (cM)SNPs
2037,338,84540,017,3342.7583

Who is wrong and who is right, Mr. mlukas? :)
 
It really seems odd.
I prepared a text to post here, but people with similar arguments did it before me. Better this way. :)

@Jovialis
With your AncestryDNA, your longest block shared with RISE397, from Bronze Age Armenia, would have 10.58 cM. The GedMatch kit of RISE397 is supposedly M497255 (https://www.eupedia.com/forum/threads/34338-GEDmatch-list-of-ancient-samples-with-kit-numbers).
Could you try a One-to-one at GedMatch, for comparison?
Thanks in advance.

Here is the comparison:

k1XQf5k.png
 
Here is the comparison:

k1XQf5k.png

Jovialis, could you set it to 1? Let's see the total for any that show up.

Just generally, even on gedmatch it makes no sense for people to get such big segments with "real" ancients like Loschbour, bigger than with more proximate samples.

I'm not comfortable with this heated criticism either. It's not like the MDLP results are so great. My fits there are terrible, and I know exactly where my ancestors have been for the last 600 years. I think this is a very complicated topic, and I don't see any clear cut "winner" in terms of results.

Ed. "It says no shared segments, however chromosome 21 does seem to have a lot of green base pairs with a full match. Chromosome 21 is where it said I have the cMs with it. I'm not sure how to interpret that."

A different algorithm, I guess, but I don't know. As I said, maybe lower the threshold.
 
Here is the comparison:

k1XQf5k.png

It says no shared segments, however chromosome 21 does seem to have a lot of green base pairs with a full match. Chromosome 21 is where it said I have the cMs with it. I'm not sure how to interpret that.
 
Jovialis, could you set it to 1? Let's see the total for any that show up.

Just generally, even on gedmatch it makes no sense for people to get such big segments with "real" ancients like Loschbour, bigger than with more proximate samples.

I'm not comfortable with this heated criticism either. It's not like the MDLP results are so great. My fits there are terrible, and I know exactly where my ancestors have been for the last 600 years. I think this is a very complicated topic, and I don't see any clear cut "winner" in terms of results.

Ed. "It says no shared segments, however chromosome 21 does seem to have a lot of green base pairs with a full match. Chromosome 21 is where it said I have the cMs with it. I'm not sure how to interpret that."

A different algorithm, I guess, but I don't know. As I said, maybe lower the threshold.

Here it is with 1 cM threshold:

bOjSw3z.png
 
Last edited:
I noticed that they don't include the X chr.

Does anybody know if Gedmatch calculates the X chr. in the standard Admixture Utilities?

EDITED:

never mind, I just looked at it, the Answer is NO.

i guess we’re all getting incomplete results when we run 23andme, Ancestry, ...

Am I wrong?
 
Here is it is with 1 cM threshold:

bOjSw3z.png

Well, there you go. They're doing something different.

They should issue a white paper explaining their method.
 
I noticed that they don't include the X chr.
Does anybody know if Gedmatch calculates the X chr. in the standard Admixture Utilities?
EDITED:
never mind, I just looked at it, the Answer is NO.
i guess we’re all getting incomplete results when we run 23andme, Ancestry, ...
Am I wrong?
There are One-to-one Autosomal and One-to-one X. You can try them both, separately.

@All
It may be also a matter of Settings. The defaults for GedMatch and Genesis seem different from each other, meaning different results? No time to try them.
 
There are One-to-one Autosomal and One-to-one X. You can try them both, separately.

@All
It may be also a matter of Settings. The defaults for GedMatch and Genesis seem different from each other, meaning different results? No time to try them.

I need to do a visit to Loschbour to leave some flowers on the grave :)

GEDmatch® Genesis Autosomal One-to-one Comparison - V1.0

F999918 (Loschbour, Lux., 8ky) [GEDmatch Xfer]

Segment threshold size will be adjusted dynamically between 200 and 400 SNPs
Minimum segment cM to be included in total = 1.0 cM
Mismatch-bunching Limit will be adjusted dynamically to 60 percent of the segment threshold size for any given segment.
Largest segment = 5.3 cM

Total Half-Match segments (HIR) = 224.8 cM (6.268 Pct)

140 shared segments found for this comparison.

611151 SNPs used for this comparison.

54.485 Pct SNPs are full identical

Comparison took 0.296 seconds.
CPU time used: 0.079 cpu seconds.

Ver: Mar 26 2019 01:00:34

Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
1
5,088,617
5,684,301
1.3
235
1
42,269,458
43,976,157
1.4
320
1
50,835,606
53,217,335
1.1
252
1
66,825,944
67,672,765
1.2
207
1
80,251,910
81,316,894
1.0
259
1
92,925,390
94,509,226
1.3
268
1
102,308,337
103,610,579
1.1
223
1
106,967,482
108,139,636
1.2
270
1
109,357,456
110,307,263
1.2
225
1
211,201,592
212,670,865
1.1
287
1
214,425,225
215,361,603
1.2
239
1
215,848,587
216,688,839
1.6
216
1
218,348,909
220,454,111
1.6
452
1
238,650,133
239,567,065
1.9
269


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
2
18,674
1,377,042
1.7
315
2
38,762,291
40,493,990
1.3
384
2
113,953,508
115,487,457
1.9
239
2
125,499,930
127,120,893
1.7
233
2
133,368,556
134,624,276
1.9
378
2
151,885,556
153,464,499
1.2
309
2
161,784,214
164,441,667
1.7
377
2
184,701,773
186,317,662
1.2
234
2
194,990,534
196,664,766
1.1
234
2
200,250,898
202,542,836
1.7
458
2
237,720,634
238,721,240
1.3
269


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
3
25,146,601
26,582,570
2.0
311
3
31,511,691
32,303,140
1.3
210
3
39,817,494
41,019,888
1.1
210
3
55,801,004
57,021,793
1.5
254
3
103,174,143
104,864,415
1.1
347
3
119,524,651
122,686,113
2.0
565
3
182,433,424
183,572,790
2.2
233


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
4
5,080,052
5,743,512
2.0
207
4
159,317,442
160,905,205
1.1
202


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
5
1,962,256
2,564,145
2.3
251
5
6,708,483
7,859,523
2.2
330
5
72,601,498
73,432,001
1.2
235
5
89,368,792
90,799,333
1.3
254
5
95,949,002
97,929,333
1.6
361
5
100,302,925
101,946,798
1.1
253
5
111,139,696
113,134,734
1.6
458
5
147,188,475
148,216,692
1.1
243
5
151,435,875
152,992,110
1.2
270
5
166,618,942
167,402,174
1.5
201
5
168,198,305
170,283,091
5.3
752


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
6
15,279,490
16,080,109
1.3
220
6
24,053,169
24,926,730
1.6
297
6
34,041,306
35,473,252
1.2
279
6
52,050,493
52,745,061
1.1
225
6
53,961,513
55,144,102
1.1
239
6
97,234,433
99,230,880
1.5
238
6
100,247,048
101,801,581
1.3
232
6
139,962,127
142,283,198
1.2
260
6
147,503,799
148,771,965
2.4
357
6
150,637,477
151,161,836
1.1
201


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
7
2,115,163
2,946,141
1.3
208
7
8,780,037
9,334,068
1.4
252
7
37,929,694
38,692,014
1.2
245
7
62,517,629
66,689,729
1.4
312
7
68,656,780
70,144,987
1.7
206
7
71,115,769
73,141,464
1.8
243
7
93,513,413
95,131,967
1.7
474
7
109,910,153
111,500,553
1.2
280
7
122,986,940
124,397,026
1.3
247
7
145,145,326
146,569,874
1.5
201


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
8
18,212,931
18,787,795
1.3
327
8
25,536,691
26,600,068
1.7
339
8
29,873,603
31,072,165
1.4
210
8
50,654,234
52,496,221
1.2
269
8
53,885,194
55,269,485
1.1
251
8
121,009,824
122,497,385
1.2
297


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
9
329,830
847,292
1.5
258
9
11,578,233
12,829,714
1.7
358
9
23,738,335
24,864,882
1.2
204
9
76,228,755
77,809,291
1.8
285
9
109,838,977
110,573,303
1.7
265
9
114,919,707
116,386,438
2.3
344
9
121,320,294
122,319,889
1.8
234


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
10
8,245,150
8,919,297
1.9
287
10
16,706,766
17,334,935
1.3
250
10
20,611,613
22,284,878
1.3
375
10
22,961,707
24,584,036
1.7
328
10
65,452,546
67,211,369
1.1
328
10
81,175,250
82,411,802
1.9
247
10
83,259,758
84,444,585
1.3
309
10
85,715,152
87,154,121
1.2
335
10
94,502,244
95,431,535
1.4
355
10
100,242,195
101,790,389
1.3
336
10
122,530,844
123,094,884
1.4
207


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
11
5,671,623
6,304,710
1.4
204
11
14,255,818
15,942,032
1.6
343
11
59,612,859
60,750,048
1.4
270
11
64,938,381
67,418,202
1.8
425
11
73,894,976
76,872,169
3.0
651
11
86,650,282
87,667,815
1.1
239


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
12
4,417,127
5,056,535
1.9
230
12
18,684,104
19,701,039
1.5
234
12
21,408,845
22,146,930
1.1
288
12
28,978,861
29,736,480
1.3
216
12
31,085,405
32,242,179
1.2
298
12
48,237,303
51,375,318
2.1
551
12
63,275,017
64,401,412
1.1
244
12
117,571,041
118,328,555
2.0
302
12
124,980,586
125,795,991
2.6
258


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
13
22,343,925
22,804,312
1.4
252
13
26,700,284
27,498,549
2.0
246
13
35,140,690
36,200,686
1.4
206
13
71,118,979
72,330,504
1.6
283
13
96,132,701
97,526,225
1.1
220


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
14
34,749,512
37,190,065
2.4
484
14
67,291,186
69,136,881
1.1
377
14
78,800,072
80,805,243
2.3
448
14
98,267,909
99,020,763
1.8
214


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
15
32,309,184
33,477,222
3.3
266
15
33,929,082
34,667,075
1.9
237
15
35,086,366
36,041,183
1.8
205
15
45,425,864
46,595,789
1.4
233
15
68,881,524
69,936,082
2.1
200


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
16
8,313,272
8,870,618
1.5
202
16
12,237,623
13,247,355
3.1
367
16
14,379,836
16,277,685
1.8
342
16
20,109,653
21,610,804
2.2
238
16
71,459,146
72,910,403
1.2
204
16
89,350,038
90,163,275
1.0
209


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
17
7,017,420
7,721,030
1.4
200
17
18,856,896
20,855,951
1.2
223
17
50,212,182
51,319,040
1.1
201


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
18
8,793,236
9,814,639
3.0
331
18
35,058,664
37,876,759
2.2
533
18
54,056,577
55,236,342
1.3
269


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
19
29,446,266
31,819,830
4.4
544


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
20
5,783,694
6,410,854
1.9
203
20
8,419,818
9,259,371
1.9
258
20
19,058,878
19,985,970
2.8
367
20
37,713,976
40,317,262
2.5
518


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
21
32,528,960
33,507,584
1.7
256
21
36,223,627
36,854,998
1.6
208
21
43,816,548
44,574,541
1.6
260


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
22
32,830,958
33,456,090
1.1
228
22
48,578,966
49,027,559
3.2
225
 
I need to do a visit to Loschbour to leave some flowers on the grave :)

GEDmatch® Genesis Autosomal One-to-one Comparison - V1.0

F999918 (Loschbour, Lux., 8ky) [GEDmatch Xfer]

Segment threshold size will be adjusted dynamically between 200 and 400 SNPs
Minimum segment cM to be included in total = 1.0 cM
Mismatch-bunching Limit will be adjusted dynamically to 60 percent of the segment threshold size for any given segment.
Largest segment = 5.3 cM

Total Half-Match segments (HIR) = 224.8 cM (6.268 Pct)

140 shared segments found for this comparison.

611151 SNPs used for this comparison.

54.485 Pct SNPs are full identical

Comparison took 0.296 seconds.
CPU time used: 0.079 cpu seconds.

Ver: Mar 26 2019 01:00:34

Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
1
5,088,617
5,684,301
1.3
235
1
42,269,458
43,976,157
1.4
320
1
50,835,606
53,217,335
1.1
252
1
66,825,944
67,672,765
1.2
207
1
80,251,910
81,316,894
1.0
259
1
92,925,390
94,509,226
1.3
268
1
102,308,337
103,610,579
1.1
223
1
106,967,482
108,139,636
1.2
270
1
109,357,456
110,307,263
1.2
225
1
211,201,592
212,670,865
1.1
287
1
214,425,225
215,361,603
1.2
239
1
215,848,587
216,688,839
1.6
216
1
218,348,909
220,454,111
1.6
452
1
238,650,133
239,567,065
1.9
269


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
2
18,674
1,377,042
1.7
315
2
38,762,291
40,493,990
1.3
384
2
113,953,508
115,487,457
1.9
239
2
125,499,930
127,120,893
1.7
233
2
133,368,556
134,624,276
1.9
378
2
151,885,556
153,464,499
1.2
309
2
161,784,214
164,441,667
1.7
377
2
184,701,773
186,317,662
1.2
234
2
194,990,534
196,664,766
1.1
234
2
200,250,898
202,542,836
1.7
458
2
237,720,634
238,721,240
1.3
269


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
3
25,146,601
26,582,570
2.0
311
3
31,511,691
32,303,140
1.3
210
3
39,817,494
41,019,888
1.1
210
3
55,801,004
57,021,793
1.5
254
3
103,174,143
104,864,415
1.1
347
3
119,524,651
122,686,113
2.0
565
3
182,433,424
183,572,790
2.2
233


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
4
5,080,052
5,743,512
2.0
207
4
159,317,442
160,905,205
1.1
202


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
5
1,962,256
2,564,145
2.3
251
5
6,708,483
7,859,523
2.2
330
5
72,601,498
73,432,001
1.2
235
5
89,368,792
90,799,333
1.3
254
5
95,949,002
97,929,333
1.6
361
5
100,302,925
101,946,798
1.1
253
5
111,139,696
113,134,734
1.6
458
5
147,188,475
148,216,692
1.1
243
5
151,435,875
152,992,110
1.2
270
5
166,618,942
167,402,174
1.5
201
5
168,198,305
170,283,091
5.3
752


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
6
15,279,490
16,080,109
1.3
220
6
24,053,169
24,926,730
1.6
297
6
34,041,306
35,473,252
1.2
279
6
52,050,493
52,745,061
1.1
225
6
53,961,513
55,144,102
1.1
239
6
97,234,433
99,230,880
1.5
238
6
100,247,048
101,801,581
1.3
232
6
139,962,127
142,283,198
1.2
260
6
147,503,799
148,771,965
2.4
357
6
150,637,477
151,161,836
1.1
201


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
7
2,115,163
2,946,141
1.3
208
7
8,780,037
9,334,068
1.4
252
7
37,929,694
38,692,014
1.2
245
7
62,517,629
66,689,729
1.4
312
7
68,656,780
70,144,987
1.7
206
7
71,115,769
73,141,464
1.8
243
7
93,513,413
95,131,967
1.7
474
7
109,910,153
111,500,553
1.2
280
7
122,986,940
124,397,026
1.3
247
7
145,145,326
146,569,874
1.5
201


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
8
18,212,931
18,787,795
1.3
327
8
25,536,691
26,600,068
1.7
339
8
29,873,603
31,072,165
1.4
210
8
50,654,234
52,496,221
1.2
269
8
53,885,194
55,269,485
1.1
251
8
121,009,824
122,497,385
1.2
297


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
9
329,830
847,292
1.5
258
9
11,578,233
12,829,714
1.7
358
9
23,738,335
24,864,882
1.2
204
9
76,228,755
77,809,291
1.8
285
9
109,838,977
110,573,303
1.7
265
9
114,919,707
116,386,438
2.3
344
9
121,320,294
122,319,889
1.8
234


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
10
8,245,150
8,919,297
1.9
287
10
16,706,766
17,334,935
1.3
250
10
20,611,613
22,284,878
1.3
375
10
22,961,707
24,584,036
1.7
328
10
65,452,546
67,211,369
1.1
328
10
81,175,250
82,411,802
1.9
247
10
83,259,758
84,444,585
1.3
309
10
85,715,152
87,154,121
1.2
335
10
94,502,244
95,431,535
1.4
355
10
100,242,195
101,790,389
1.3
336
10
122,530,844
123,094,884
1.4
207


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
11
5,671,623
6,304,710
1.4
204
11
14,255,818
15,942,032
1.6
343
11
59,612,859
60,750,048
1.4
270
11
64,938,381
67,418,202
1.8
425
11
73,894,976
76,872,169
3.0
651
11
86,650,282
87,667,815
1.1
239


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
12
4,417,127
5,056,535
1.9
230
12
18,684,104
19,701,039
1.5
234
12
21,408,845
22,146,930
1.1
288
12
28,978,861
29,736,480
1.3
216
12
31,085,405
32,242,179
1.2
298
12
48,237,303
51,375,318
2.1
551
12
63,275,017
64,401,412
1.1
244
12
117,571,041
118,328,555
2.0
302
12
124,980,586
125,795,991
2.6
258


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
13
22,343,925
22,804,312
1.4
252
13
26,700,284
27,498,549
2.0
246
13
35,140,690
36,200,686
1.4
206
13
71,118,979
72,330,504
1.6
283
13
96,132,701
97,526,225
1.1
220


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
14
34,749,512
37,190,065
2.4
484
14
67,291,186
69,136,881
1.1
377
14
78,800,072
80,805,243
2.3
448
14
98,267,909
99,020,763
1.8
214


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
15
32,309,184
33,477,222
3.3
266
15
33,929,082
34,667,075
1.9
237
15
35,086,366
36,041,183
1.8
205
15
45,425,864
46,595,789
1.4
233
15
68,881,524
69,936,082
2.1
200


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
16
8,313,272
8,870,618
1.5
202
16
12,237,623
13,247,355
3.1
367
16
14,379,836
16,277,685
1.8
342
16
20,109,653
21,610,804
2.2
238
16
71,459,146
72,910,403
1.2
204
16
89,350,038
90,163,275
1.0
209


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
17
7,017,420
7,721,030
1.4
200
17
18,856,896
20,855,951
1.2
223
17
50,212,182
51,319,040
1.1
201


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
18
8,793,236
9,814,639
3.0
331
18
35,058,664
37,876,759
2.2
533
18
54,056,577
55,236,342
1.3
269


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
19
29,446,266
31,819,830
4.4
544


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
20
5,783,694
6,410,854
1.9
203
20
8,419,818
9,259,371
1.9
258
20
19,058,878
19,985,970
2.8
367
20
37,713,976
40,317,262
2.5
518


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
21
32,528,960
33,507,584
1.7
256
21
36,223,627
36,854,998
1.6
208
21
43,816,548
44,574,541
1.6
260


Chr
B37 Start Pos'n
B37 End Pos'n
Centimorgans (cM)
SNPs
22
32,830,958
33,456,090
1.1
228
22
48,578,966
49,027,559
3.2
225

i have full orange bars for NE1, BR2 and Stuttagart when I use archaic in gedmatch, .................yet have zero SNP for them when I compare ................is there a different method you use
 
i have full orange bars for NE1, BR2 and Stuttagart when I use archaic in gedmatch, .................yet have zero SNP for them when I compare ................is there a different method you use

I just compare the Kit F999918 with my Genesis GEDmatch kit. Standard adjusts. Nothing more. Nothing diferent or special.
 
There are One-to-one Autosomal and One-to-one X. You can try them both, separately.

@All
It may be also a matter of Settings. The defaults for GedMatch and Genesis seem different from each other, meaning different

results? No time to try them.

:unsure:just guessing

If the Autosomal results of a mainstream company is based on the totality of 22 plus the X chr. versus just 22 chr. of a third party site, the 2 results are incomparable.

In general, if both parents are ethnically equal and are from the same area, there won't be much difference in the results, regardless of X chr.

All Mix people will get only partial results if the X chromosome is not in the calculator.

just guessing, :)
 
@Duarte
ahah Boa! Será você um primo distante do Vanderlei Luxemburgo? ;)

Fellow, Loschbour is from Mesolithic, so it doesn't seem likely a "true" shared segment as large as that. Anyway, Settings do matter, apparently. I guess GedMatch results and Genesis' will be more similar to each other if you set Genesis' minimum segment threshold to 500 SNPs? If you put more than that, it could even affect the Largest segment size, I guess, depending on how many you choose.
I assume GedMatch/Genesis are, say, somewhat"flexible", and MyTrueAncestry may be even more, which could perhaps explain those "discrepancies", instead they're informing some dishonest random results. Still, it doesn't smell realistic to me. Particularly, I like the similarity tool they created, as I alrrady said. It's nice. But not really this IBD matching tool. In my opinion.

@Salento
Settings/criteria of each company also matter for comparisons. We saw that phasing is also important.
Now, if you wanna totals in GedMatch, you can just sum Autosomal results and X's, after run the tools separately. And that's it.
 
Last edited:
deleted.....
 
@Regio X
HA HA HA. Creio que eu e ele temos o Luxemburgo em comum. Mas ele é um homem do futebol, e ganha muito mais dinheiro do que eu :))
 
Basilicata was founded by the normans
 

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