Happy First Birthday Iowa DNA Project

The Iowa DNA Project was formed at the end of November 2014 and for its first birthday has now reached 361 members.  The project is ‘geographical’ in nature, and designed for those who have direct ancestors who lived in Iowa, or those researching collateral lines that lived in Iowa. Our focus is on autosomal, aka Family Finder results, but we also have members who have had or are in the process of having their mtDNA and YDNA tested.  Those new to DNA testing are especially welcome and their research aims are supported within the project.

The previous (August 2015) Quarterly Report can be viewed here.

Key Figures

  • Total Iowa DNA Project Members: 361
  • Family Finder Tests Completed: 305
  • Total Donations: $105  Current Balance $6
  • Highest number of database wide matches per member: 3000
  • Lowest number of database wide matches per member: 1
  • Average number of database wide matches per member: 858
  • Inter-Project Matches: 233
  • Highest number of Inter-Project matches per member: 11
  • Weekly Match Updates
  • 96 of 99 Iowa Counties Represented

iowa mapNuts and Bolts

The Iowa DNA Project Surname Index can be found here.  Surnames associated with specific counties can be found in our FAQ here.

  • Total Iowa Surnames: 667
  • Members with Family Trees:276
  • Members with listed Surnames: 317
  • Members with listed Most Distant Ancestors: 292

Iowan Family Groups

The Iowa DNA Project has many pioneers who were the first to test within their immediate family.  However, the backbone of the project is the inclusion of multiple generations and extended family members who have also tested.  These family groups assist in helping inter-project matches determine how they may be connected and which branch of their family trees to examine further.  In October, we teamed up with Göran Runfeldt of dnagen.net  to trial his ICW Tool to map out the interconnectedness of the entire Iowa DNA project.   Below is a depiction of the connections between our current members.


Using the ICW Tool gives Iowa DNA Project members easy access to a variety of additional information and charts including a tabulation of our members’ Suggested Relationships.  As you can see, our members are actively recruiting close family members to test.

match totals

Suggested Relationships

  • Parent/Child: 64
  • Full Siblings: 38
  • Grandparent/Grandchild/Half Siblings: 22
  • Aunt/Uncle/Niece/Nephew: 22
  • 1st Cousin: 22
  • 2nd Cousin: 30
  • 3rd Cousin: 62
  • 4th Cousin: 114

More can be learned about the process and results here*.

*Additional detailed information is available to Iowa DNA Project members


Project YDNAAs expected, the most common Y haplogroup is R and its subclades, with I and its subclades the second most common.  23 project members have completed the Big Y test.

Conf Y

Predicted Y

  • R-M269: 48
  • R (excluding R-M269): 44
  • I: 28
  • G: 3
  • E: 3
  • J: 2
  • N: 3

More information on the project’s patriarchs and YDNA results can be found here.

Project mtDNA:  The most common mtDNA continues to be H and its subclades with a variety of other haplogroups also represented. 105 project members have completed Full Mitochondrial Sequencing.

Member Haplogroups:

  • H: 68
  • K: 17
  • T: 16
  • U: 14
  • J: 12
  • I: 5
  • W: 3
  • V: 2
  • B: 2
  • C:1
  • X: 1

Complete information on our project’s mtDNA matriarchs, statistics and mutations can be found here.

conf mtdna

Declared Countries of YDNA and mtDNA Origin


mt COA

MyOrigins Leaderboard

Based on percentage points per member, the Iowa DNA Project populations are listed below in order of frequency.  Descriptions of each population cluster can be found here.  Additional admixture tools can be found at Gedmatch.

  • British Isles 12,333
  • Scandinavia 6931
  • Western and Central Europe 6558
  • Southern Europe 1710
  • Eastern Europe 1403
  • Finland and Northern Siberia 345
  • Asia Minor 296
  • West Africa 158
  • Ashkenazi Diaspora 120
  • Eastern Middle East 106
  • (Blended Population Cluster) Eastern, Western and Central European 100
  • Native American 87
  • Northeast Asia 78
  • Central Asia 75
  • North Africa 35
  • East Central Africa 5
  • South-Central Africa 4
  • (Blended Population Cluster) British Isles and Western and Central Europe 1

As a matter of interest:

  • 100% British Isles 3 members
  • 100% Western and Central Europe 2 members
  • 100% Scandinavian 1 member
  • 100% Eastern, Western and Central European 1 member

Coming Results:

Currently, we are waiting for 3 kits to be returned to the lab for testing: 1 Factoid, 1 YDNA 67 Marker and 1 mtFull Sequence.  We have 13 members who have kits that have been transferred but not yet unlocked. Current members, please keep in mind you cannot be checked for inter-project matches without a completed and unlocked Family Finder test.

From the FTDNA lab, we are waiting for:

  • 2 mtFull Sequence (1 delayed)
  • 1 YDNA 37 marker
  • 7 Factoids (same project member)
  • 1 Y Haplogroup Backbone (delayed)
  • 1 R1b-CTS4466 SNP Pack
  • 1 R1b-L21 SNP Pack
  • 1 Big Y
  • 5 individual SNPS (same project member, 4 delayed)

Do You have Iowan Roots?

I would like to thank the project members for their patience and many efforts over the last year.  In October, I attended the Irish Genetic Genealogy Conference in Dublin, Ireland and had the pleasure of attending lectures, meeting cousins, members of ISOGG and other project administrators.  Lots of great information came out of the conference as well as ideas to make the project better. I look forward to making and sharing our discoveries in the months to come.

You can read more about the benefits of joining a project at FTDNA here.  If you would like to join the Iowa DNA Project, please visit our homepage here.  The project has converted to MyGroups and has activated its Activity Feed to encourage collaboration. The Feed may be accessed after joining and of course our links section is available to all.


MDLP K13 Ultimate

For you ancestral-origin addicts, if your kit isn’t already uploaded to Gedmatch, you might want to consider adding it to their free database.  Not only can you get additional matches from the Big Three DNA companies, but there are numerous admixture tools to explore, including Vadim Verenich’s new MDLP K13 Ultimate.

Vadim discusses and explains his methodology in creating MDLP K13 Ultimate here.  According to Vadim, the tool is especially useful for showing the deep ancestry of Western Europeans.

MDLP K13 Ultimate’s Components

  • Amerindian – the modal component of the Native American
  • ANE – the modal component of the Northern Eurasians, which has been isolated from the common cluster with WHG – the highest values ​​in the samples of MA1, AG2, as well as the ancient genomes from Sintashta, Andronov, Afanasievo, Yamnaya, Corded Ware etc. Among the modern populations the highest percentage of ANE has been detected in Kalash population. Almost the same with the ANE component in Lazaridis et al. 2014
  • Arctic – modal component with peak populations Koryak, Chukchi, Eskimos and Itelmens
  • ASI – еру modal component of South Indian populations (i assume that this component is identical to ASI in (Reich et al. 2009).
  • Caucasus-Gedrosia – identical to Pontikos’s Caucasus-Gedrosia cluster
  • EastAsian – the modal component of East Asia
  • ENF – the component of the ancient European Neolithic farmers with the peak in the ancient samples of LBK culture (Lazaridis et al. 2014, Haak et al. 2015). Among the modern populations – the highest values ​​have been detected in Sardinians, Corsicans and Basques.
  • NearEast – the modal component of Middle Easterners
  • Oceanian – the modal component of the aboriginal inhabitants of Oceania, Austronesian, Melanesia and Micronesia (the peak in modern Papuans and Australian Aborigines)
  • Paleo-African – the modal component of African Pygmies and Bushmen
  • Siberian – the modal component of south eastern Siberia
  • Subsaharian – the second African component (Mandinka, Yoruba and Esan)
  • WHG-UHG – the native component of the ancient European Mesolithic hunter-gatherers (Lazaridis et al. 2014, Haak et al. 2015). Among the modern populations – the highest percentage in the population of Estonians, Lithuanians, Finns and others.

A Test Run

The testers in this experiment include 3 family groups that are predominantly Western European.

Group 1

Group 1 consists of 4 generations of my immediate family as shown in Figure 1.


Group 1 MDLP K13 Ultimate Admixture Results:

group 1


Below are each tester’s Oracle 4 results. Oracles are designed to find the population(s) you are most similar to.   As an example of what you might see in your own results, for Gladys I have shown the full Oracle 4 output.  For the rest of the testers, I’ve only included the top estimate in each of the 4 population approximations.  When using the Oracles, ideally you want your results to be a distance close to 1 or less.  The further the distance, the less your sample matches the reference population.  Please note, the MDLP K13 Ultimate Calculator has no Irish samples and thus no Irish population is included in the Oracle estimates.

Gladys mtDNA J1c3e Irish, small amount Alsace

Using 1 population approximation:

1 Germany_South @ 4.725954

2 Welsh @ 4.760169
3 Hungary @ 5.075449
4 Slovenian2 @ 5.144983
5 Slovak @ 5.262948
6 Austria @ 5.263268
7 North_European @ 5.285005
8 Czech2 @ 5.398787
9 Belgian @ 5.461259
10 German @ 5.465462
11 Slovenian @ 5.676105
12 South-German @ 5.796731
13 Austrian @ 5.843022
14 Hungarian @ 5.923850
15 Germany_North @ 6.175276
16 Inkeri @ 6.573199
17 Croat_BH @ 6.697131
18 North_German @ 6.715919
19 English_GBR @ 6.953663
20 Moldavian @ 7.103191

Using 2 populations approximation:

1 50% France +50% Vepsa @ 3.396806

Using 3 populations approximation:

1 50% Icelandic +25% Lak +25% Spanish_Pais_Vasco_IBS @ 2.251328

Using 4 populations approximation:

1 Avar + Basque_French + Orcadian + Swedish @ 1.562552

2 Avar + Basque_Spanish + Norwegian + Swedish @ 1.587619
3 Avar + Basque_French + Norwegian + Swedish @ 1.589907
4 Basque_Spanish + Lak + Norwegian + Swedish @ 1.604312
5 Avar + Basque_French + Icelandic + Swedish @ 1.609077
6 Avar + Basque_Spanish + Orcadian + Swedish @ 1.617271
7 Avar + Basque_Spanish + Scottish_Argyll_Bute_GBR + Swedish @ 1.627082
8 Basque_Spanish + Icelandic + Lak + Swedish @ 1.632314
9 Basque_French + Icelandic + Lak + Swedish @ 1.636813
10 Avar + French_South + Orcadian + Swedish @ 1.652004
11 Basque_Spanish + Norwegian + Swedish + Tabasaran @ 1.676389
12 Basque_French + Lak + Norwegian + Swedish @ 1.702851
13 Avar + Basque_Spanish + Icelandic + Swedish @ 1.707930
14 Basque_Spanish + Orcadian + Swedish + Tabasaran @ 1.720994
15 Avar + Basque_French + Scottish_Argyll_Bute_GBR + Swedish @ 1.737037
16 Avar + Basque_French + Orcadian + Russia @ 1.739913
17 Avar + French_South + Icelandic + Sweden @ 1.740096
18 Avar + Basque_Spanish + Russia + Scottish_Argyll_Bute_GBR @ 1.742547
19 Basque_Spanish + Icelandic + Swedish + Tabasaran @ 1.748318
20 Avar + Basque_Spanish + Orcadian + Russia @ 1.759932

To give a visual representation, I have plotted her 4 population approximation with the Geographic Midpoint Calculator.  The thumbtack with the ‘M’ is the midpoint between the 4 locations. At FTDNA, Gladys is 99% British Isles and 1% Asia Minor.

gladys midpoint

Steve mtDNA J1c3e yDNA R-Z251 ½ Irish, ½ East Flanders

Using 1 population approximation:

1 Germany_South @ 2.569169

Using 2 populations approximation:

1 50% Germany_South +50% Germany_South @ 2.569169

Using 3 populations approximation:

1 50% English_GBR +25% Greek_Comas +25% Vepsa @ 2.216009

Using 4 populations approximation:

1 Basque_Spanish + English_Kent_GBR + Kumyk_Stalskoe + Polish @ 1.199786

Steve’s midpoint plots in the Czech Republic.  Although he is half Irish and half East Flemish, he also has small amounts of Asia Minor and Southern and Eastern European at FTDNA:

steve midpoint

Lori mtDNA W3

Using 1 population approximation:

1 North_European @ 3.871830

Using 2 populations approximation:

1 50% French +50% Vepsa @ 3.446190

Using 3 populations approximation:

1 50% English_Kent_GBR +25% French_South +25% Tajik_Yagnobi @ 2.150152

Using 4  populations approximation:

1 Basque_Spanish + English_Kent_GBR + Orcadian + Tajik_Yagnobi @ 1.698324

lori midpoint

Jeremy mtDNA W3 ¼ English (Newcastle), ¼ Colonial

Using 1 population approximation:

1 Welsh @ 1.196703

Using 2 populations approximation:

1 50% Welsh +50% Welsh @ 1.196703

Using 3 populations approximation:

1 50% English_Cornwall_GBR +25% English_GBR +25% Romanians @ 0.840597

Using 4 populations approximation:

1 English_Cornwall_GBR + English_Cornwall_GBR + English_GBR + Romanians @ 0.840597

J midpoint

Gavan mtDNA W3 half Irish and Scots

Using 1 population approximation:

1 English_GBR @ 3.039722

Using 2 populations approximation:

1 50% France +50% Scottish_Argyll_Bute_GBR @ 2.266037

Using 3 populations approximation:

1 50% English_GBR +25% Spanish_Aragon_IBS +25% Vepsa @ 1.150668

Using 4 populations approximation:

1 Belgian + English_Cornwall_GBR + Spanish_Aragon_IBS + Vepsa @ 1.059918

Ga midpoint

Leona mtDNA W3 ½ Pomeranian, ¼ Norwegian, ¼ Alsatian

Using 1 population approximation:

1 Welsh @ 1.911880

Using 2 populations approximation:

1 50% North European +50% Slovenian2 @ 1.408170

Using 3 populations approximation:

1 50% North_European +25% Slovak +25% Welsh @ 1.243836

Using 4 populations approximation:

1 French_South + Georgian + Latvian + Norwegian @ 1.187358

leona midpoint

Jackie mtDNA W3

Using 1 population approximation:

1 Belgian @ 1.387411

Using 2 populations approximation:

1 50% Belgian +50% Welsh @ 1.096892

Using 3 populations approximation:

1 50% Belgian +25% Welsh +25% Welsh @ 1.096892

Using 4 populations approximation:

1 French_South + Georgian + Icelandic + Sorbs @ 1.075442

jack midpoint


Using 1 population approximation:

1 South-German @ 1.934086

Using 2 populations approximation:

1 50% South-German +50% South-German @ 1.934086

Using 3 populations approximation:

1 50% North_German +25% Romanian +25% United-Kingdom @ 1.519436

Using 4 populations approximation:

1 English_Cornwall_GBR + Romanians + Slovak + United-Kingdom @ 1.441976

Group 2

MDLP K13 Ultimate Admixture Results

Untitled - 1

As seen in Figure 1, Group 2 includes 2 unrelated mothers, Nancy and Lori, and their sons, AJ and Jeremy who are ½ uncle and nephew.



Using 1 population approximation:

1 English_GBR @ 1.889876

Using 2 populations approximation:

1 50% English_GBR +50% English_GBR @ 1.889876

Using 3 populations approximation:

1 50% Russian_Orjol +25% Spanish_Pais_Vasco_IBS +25% Welsh @ 1.239205

Using 4 populations approximation:

1 Basque_French + Czech2 + Inkeri + West-Belarusian @ 1.045225

nancy midpoint


Using 1 population approximation:

1 North_European @ 2.072961

Using 2 populations approximation:

1 50% European_Utah +50% Welsh @ 1.128120

Using 3 populations approximation:

1 50% Czech2 +25% Spanish_Cantabria_IBS +25% Ukranian @ 0.942059

Using 4 populations approximation:

1 Czech2 + Slovak + Sorbs + Spanish_Cataluna_IBS @ 0.914081

aj midpoint

Lori mtDNA W3

Using 1 population approximation:

1 North_European @ 3.871830

Using 2 populations approximation:

1 50% French +50% Vepsa @ 3.446190

Using 3 populations approximation:

1 50% English_Kent_GBR +25% French_South +25% Tajik_Yagnobi @ 2.150152

Using 4  populations approximation:

1 Basque_Spanish + English_Kent_GBR + Orcadian + Tajik_Yagnobi @ 1.698324

Jeremy mtDNA W3 ¼ English (Newcastle), ¼ Colonial

Using 1 population approximation:

1 Welsh @ 1.196703

Using 2 populations approximation:

1 50% Welsh +50% Welsh @ 1.196703

Using 3 populations approximation:

1 50% English_Cornwall_GBR +25% English_GBR +25% Romanians @ 0.840597

Using 4 populations approximation:

1 English_Cornwall_GBR + English_Cornwall_GBR + English_GBR + Romanians @ 0.840597

Group 3

MDLP K13 Ultimate Admixture Results

group 3

Group 3 consists of two full sisters, Jean and Sally, and Sally’s daughter Julie.  Jean and Sally’s father was born in Glasgow from a family that originated primarily in the north of Scotland.  Maternally, they derive mainly from early Irish and German immigrants.  Paternally, Julie’s family has lived in Lippe, Germany for centuries.


Jean 1/2 Northern Scots, ½ Colonial

Using 1 population approximation:

1 North_German @ 4.487704

Using 2 populations approximation:

1 50% English_Cornwall_GBR +50% Vepsa @ 3.162740

Using 3 populations approximation:

1 50% English_Cornwall_GBR +25% Scottish_Argyll_Bute_GBR +25% Vepsa @ 2.750026

Using 4 populations approximation:

1 English_Cornwall_GBR + English_Cornwall_GBR + Scottish_Argyll_Bute_GBR + Vepsa @ 2.750026


Sally ½ Northern Scots, half Colonial

Using 1 population approximation:

1 North_European @ 1.952304

Using 2 populations approximation:

1 50% English_GBR +50% North_European @ 1.668977

Using 3 populations approximation:

1 50% Slovak +25% Spanish_Pais_Vasco_IBS +25% Vepsa @ 1.005733

Using 4 populations approximation:

1 Basque_French + Hungary + Russian_Smolensk + Vepsa @ 0.987646

Sally has a small amount of Central Asia in her FTDNA ancestral origins that her sister Jean does not have.

sally midpoint

Julie ¼ Northern Scots, ¼ Colonial, half German (Lippe)

Using 1 population approximation:

1 English_GBR @ 3.404993

Using 2 populations approximation:

1 50% French +50% Vepsa @ 3.007144

Using 3 populations approximation:

1 50% North_German +25% Spanish_Valencia_IBS +25% Vepsa @ 2.082997

Using 4 populations approximation:

1 Basque_French + Slovak + Vepsa + Vepsa @ 1.434730

julie midpoint


For my testers, the admixture calculators (ANR, ENF, WHG etc) appear reasonable and tick all the boxes I look for when considering the value of admixture tools.  The Oracle estimates are another consideration. As the calculator is exposing deep ancestry, and as a whole very little of the group’s paper trail reaches the 1500’s, let alone precedes it, we have no way of determining its precision.  We can, however, look at the population approximations  passed down and across the group’s generations, as well as consistency between estimated regions and estimated regions/populations from other calculators.

Admittedly, I needed to google some of the reference populations to find where to plot them on the map.  Despite the seemingly exotic populations some of our testers received in their estimates, once each 4 population approximation was plotted (and the non-tested parent’s known ancestry taken into account) for the most part each closely related family member plotted within the same general region.

Of course, as always, we must remember admixture calculators are estimates of ancestry, and a work in progress being improved upon as the science and reference samples grow.  They are interesting, and as long as you don’t let unexpected admixture results derail your genetic and genealogical efforts, they can be entertaining.

Missing and Small Matches

One of the pleasures of having multiple generations tested is the ability to make comparisons.  Like many DNA testers, I’d love to track the source of each match’s connection and map as much of my ancestors’ DNA as possible. When a new match arrives the first task is to determine whether it is a maternal or paternal match, which grandparent it might belong to, and if possible, to assign a more distant ancestral couple.

The more matches you have to work with, the more likely you are to connect with those that will help determine the source of your DNA.  Due to the FTDNA match requirement of at least 20 cM total shared, each kit I manage has many more FTDNA matches at Gedmatch than it does at FTDNA. In some cases, these FTDNA kits match myself and my paternal grandmother Gladys, but not my father Steve.  To determine whether these matches are false or victim of the FTDNA 20 cM total requirement, I took the advice of the larger community.  It was a simple matter to search for FTDNA kits at Gedmatch that matched grandmother Gladys and myself but not my dad.

Regardless of where you have tested, at Gedmatch it is possible to lower the minimum threshold and compare kits on a 1 to 1 basis to tease out or force matches, depending on your perspective.  Is it wise to do so?  According to an ISOGG article on phasing, “It may be reasonable to map some segments in the 3-5 cM range if both the parent and the child share that same segment with the relative but caution is warranted when mapping segments that don’t contain at least 700 or more SNPs because some matching segments could be IBS and not IBD.

Normally, I do not lower the minimum defaults at Gedmatch nor do I recommend doing so.  If you are reducing the threshold at Gedmatch to compare with a suspected relative, to ‘prove’ a match below Gedmatch’s default levels, you are taking a big risk and not necessarily proving what you intended.  However, in this special case of using 4 generations to illustrate missing matches, small matches, and small matches that could appear to some as valid and belonging to a specific ancestral couple, for all comparisons I dropped the minimum levels to 350 SNPS and 3 cM.

Cousin Malcolm

Malcolm fit the pattern of matching my grandmother Gladys, myself and one of my children at FTDNA, but he didn’t match my dad Steve. It was a different story at Gedmatch.

Glad and Malcolm

Figure 1

Steve and Malcolm

Figure 2

As seen by comparing Figures 1-3, Malcolm, Gladys and Steve all match on the highlighted portions of chromosome 1.  I also have an overlapping segment on chromosome 1 as does my son Gavan.  Are the small, non-highlighted segments valid?  Generally, I consider them to be IBS. and whatever their origin, not large enough to pursue.


Figure 3

My son Jeremy also matches Malcolm at segments up to 4.4 cM/784 SNPs, none of which were inherited from his grandmother Gladys or our common ancestor shared with Malcolm.   

Jeremy and Malcolm

Cousin Kay

Kay, too, fits the pattern of matching grandmother Gladys, myself and one of my children at FTDNA, and while she matches him at Gedmatch, she doesn’t match Steve at FTDNA.

Gladys and Kay

Figure 1

Steve and Kay

Figure 2

Lori and Kay

Figure 3

When comparing Figure 1 and Figure 2, Steve’s match on chromosome 1 occupies an area within the same start and stop points as the segment he shares with Gladys.  In Figure 3, you can see I also match Kay on chromosome 1, but my start point is 69, 937,274.  The DNA I match with my dad and grandmother has a start point for my dad of 70, 268, 967.  The differences in those start points makes it appear as though I share 8.2 cM of DNA as opposed to the 8.0 cM of DNA my dad shares with Kay.  Although a trivial amount, it could indicate my dad having no calls in that portion, or it could be a case of recombination.

Meanwhile, Kay matches my son Gavan on the same 8 cM segment he shares with me/Steve/Gladys.  On the other hand, my son Jeremy shares 5.6 cM/691 SNPs on chromosome 9 with Kay that he also shares with me but not my father or grandmother.  Jeremy and Kay may have a common ancestor through my grandmother on paper, but it is not reflected in their phased DNA results.

Jeremy and Kay

Cousin Bonnie

Bonnie also matches Gladys at FTDNA but does not match Steve.  Again, Steve has another new match at Gedmatch.


On chromosome 1, Bonnie, my dad and I share 6.1 cM/362 SNPs that we don’t share with my paternal grandmother Gladys.  362 SNPs falls well short of the ISOGG recommended minimum of 7 cM/700 SNPs. Chromosome 18 shows a match between Bonnie and myself at 3.2 cM/514 SNPs.  My dad also shares a match with Bonnie on chromosome 18 at 3.4 cM/492 SNPs.  My start point on chromosome 18 precedes the start point for my dad, and is another example of possible no calls or IBS.  Either way, neither small segment was inherited through Gladys and her ancestor in common with Bonnie.

Bonnie and Lori

At reduced threshold levels of 3cM/300 SNPs, Bonnie also matches Gavan on segments that she only otherwise shares with me and not Steve or Gladys.  Bonnie and Jeremy share segments that are shared with no one else.

Gavan and Bonnie Jeremy and Bonnie

Cousin Sean

In this example, at FTDNA Sean matches only my grandmother Gladys.  However, at Gedmatch he is also on my dad’s match list.

Glad and Sean

Figure 1

As seen when comparing Figure 1 and Figure 2, Steve matches an 8.6 cM segment on chromosome 1 with his mother Gladys.  On chromosome 17 we see another small overlap:  3.1 cM/465 SNPs.  The start points vary.

Steve and Sean

Figure 2

Neither I nor my children match Sean at FTDNA or Gedmatch, but our results do represent what type of results we could expect if we were lowering thresholds and comparing 1 to 1 with out the safety net of additional tested generations and their data.  In Figure 3, my results are added and compared against my grandmother and father.  While Sean and I have numerous ‘matches’, up to 5.1 cM,  I didn’t inherit the vast majority of them from my grandmother Gladys or the ancestor we share with Sean, and none of them fall within the phased extreme minimum recommended range of 3-5cM/700 SNPs.

Sean and Lori

Figure 3

In Figure 4, my Irish born son Gavan is compared to Northern Irish Sean.  He also has matches, with segments up to 4.4cM/683 cM with Sean, although none of them were inherited from Gladys or the ancestor we share with Sean.

Gavan and Sean

Similarly, my son with deep American Colonial ancestry Jeremy also matches with Northern Irish Sean at up to 5.4 cM/838 SNPs, but again, none of the matches were provided by Gladys and our common ancestor.

Jeremy and Sean

Closer Cousins


Previously, I’ve been concentrating on distant cousin matches that could easily be missed by FTDNA’s minimum requirements but could appear at Gedmatch with single blocks of shared DNA above 7cM/700 SNPs.  In the following examples I am concentrating on another multi-generationally tested family.  Their patriarch, CK is my grandmother Gladys’s 2nd cousin through common ancestors Henry Kane and Katherine Forrestal of County Mayo, Ireland.

Gladys and CK, as second cousins, share abundant DNA in excess of 7 cM/700 SNPs from Henry and Katherine.  They also share 2 segments above 5cM/700 SNPs on chromosome 15.

Gladys and CK

Two of CK’s children, HaK and HeK have also tested. In Figures 1 and 2, we see the DNA they share with both Gladys (G) and CK (C) highlighted, as well as segments that are partial overlaps with Gladys and CK.

Gladys HaK

Figure 1

Glad and HeK

Figure 2

In Figure 3, we see the DNA shared between CK and Steve, Gladys’s son.  All the highlighted portions match CK, Steve and his mother Gladys, including a 3.9 cm/772 SNPs segment on chromosome 15 and  3.9 cM/400 SNPs segment on chromosome 16.  The segments that don’t match Gladys fall below the 700 SNP range.

Steve and CK

Figure 3

Adding a 3rd Generation

HeK and HaK both have children that have tested.  HeK’s son does not appear on any of the match lists of Gladys, Steve, Lori, Jeremy or Gavan.  However, HaK’s children, KaK and KeK do and are shown below, with the highlighted portions illustrating the segments they share with Gladys (G), their grandfather CK (C) and their father HaK (H).

Gladys and KaK

Above, KaK matches Gladys, her grandfather and father  on chromosomes 3, 4 and 13 and partially overlaps on chromosome 6.  The match she shares with her father on chromosome 8 doesn’t match the DNA shared by CK and Gladys. Of the remaining segments KaK  shares with Gladys, on chromosome 1 she shares 3.1 cM/854 SNPs which she does not share with her grandfather CK.

Below are highlighted the shared segments of KeK, his father HaK (H), grandfather CK (C), and Gladys(G). KeK matches his father, grandfather and Gladys on chromosomes 6 and 13 match and partially matches them on chromosomes 3, 15 and 19 . On chromosome 1 KeK share the same 3.1 cM/852 SNPs as his full sibling KaK.

Gladys and KeK

Gladys(G) has a grandchild and Steve (S) a child who has tested (me), so I am also able to compare my segments against the group to ferret out DNA I’ve inherited from Katherine and Henry via my grandmother Gladys.

Lori and CK

In the above example all highlighted matches except one on chromosome 15 match Gladys, Steve and CK.  The smaller segments match neither Gladys nor Steve.

Adding a 4th Generation

My sons make up the 4th generation.  Below, Jeremy has one match at 50.3 cM/13,569 SNPs shared by CK, Gladys, Steve and myself as well as one that is 3.4 cM/492 SNPs. Two of the non-highlighted matches he shares with CK but not his mother or the rest of the group are in excess of 700 SNPs.

Jeremy and CK

Gavan has 4 matches shared between CK, his mother, grandfather Steve and great-grandmother Gladys. None of the non-highlighted matches Gavan shares with CK but not the rest of the group are in excess of 700 SNPs.

Gavan and CK

Putting it Together

Determining whether a match is valid is clearly extremely important when working with your results.  Making sure you have added your kit to Gedmatch, whether you have tested at Ancestry, 23andMe or FTDNA is an essential part of the process.  I haven’t yet gone through all the FTDNA matches missing from my dad’s list that Gladys and I share, but I have yet to find a FTDNA match that has also uploaded to Gedmatch that he doesn’t also match above 7cM/700 SNPs.

Recombination, crossover, IBS, IBD and phasing are important concepts all budding genetic genealogists must grapple with.  Minimum acceptable segment length will doubtlessly continue to be debated and redefined.  Certainly, if you are using reduced thresholds/small segments and haven’t tested a parent(s) you are taking a very big gamble.

For further reading you might be interested in: Small Segments and Triangulation by Jim Bartlett,  Hotspots and Crossover,  and Anatomy of an IBS Segment and What a Difference a Phase Makes by Ann Turner.  You might also wish to add your voice to the subject at the FTDNA forums.

Iowa Surnames and Counties November 2015

iowa map
With 390 members, 96 of 99 counties represented and 233 inter-project matches, the Iowa DNA Project has grown tremendously over the last year.  Each new member increases the likelihood of finding matches and learning more about our ancestors and the settlement of Iowa.  Is your surname represented?  If not, consider joining!  If you don’t already have an account at FTDNA but have tested with another company, you might like to consider transferring your raw data.

Counties and Associated Surnames

Adair: Aspinwall, Bates,Hoisington, Lounsbury, Scott, Sias, Nichols, Stillians/Stillions, Newcomb

Adams: Shiffer, Riggle, Henry, Jones, Newcomb, Ankeny, Rogers, Fleharty

Allamakee: Whalen, Regan, Devine, Laughlin, Danaher, Ryan, Fitzgerald, Born, Dee, O’Conner/Conner,Kruger, Winke, Flage, Henning, Ludeking, Baxter, Butler, Buckley, Ralston,Archibald, Sires, Duff, Speigler, Healy, Brady, Werhan

Appanoose: Milburn, Awalt, Morlan, Murphy, Brown, Robinson, Phares, Flowers, Crawford, Martin, Jackson, Gates, Wilcox,Watson, Zimmerman, Richards, Bowman, Richards

Audubon: Drake, Finch

Benton: Gallup, Dilley, Stewart, Cue, Calhoon, Younglove, Hinkle

Black Hawk: Belt, Whaylen, Corrigan, O’Neill, Stewart, McNaughton, House, Purdie,Mallett, Richmond, Bates, Robinson, Kerns,Beirschmitt, Duffy, Kane, Forrestal, Burns, Flaherty, Kennedy, Harned, Singer, Robertshaw, Olsen, Jensen,Hansen, Morgensen, Baer, Bender, Buehner, Call,Carpenter, Fuller, Hare, Haun, Meisch,Neisen, DuBois, Kelly

Boone: Lyman, Benjamin, Fenn,Harmon, Smith, Miller, Peachey, McGregor,Ballentine

Bremer: Harned, Singer, Baer, Bender, Buehner, Call, Carpenter, Fuller, Hare,Haun

Buchanan: Leach, Chicken, Grim,Duffy, Kane, Forrestal, McCloskey, Kinney, Clark, Harned, Singer

Buena Vista: Jessip, Carney, Marshall, Howard, Dale, Ginn, Taylor,Larson, Johnson,  Lydell

Butler:  Bigsby

Calhoun: Osborn, Godwin

Carroll: Wilkens, Piper, Conner, Wenck, Best, Rabe, Brunen

Cass: Scovel, Baker, Gillpatrick, Randles, Brown, Bruun, Tobieson, Sandham

Cedar: Orcutt, Dutton, Baker,Gaines, Gillpatrick, Randles, Wagner, Knipfer, Mottschall

Cerro Gordo:  Hacker

Cherokee: Beyer, Schubert, Sorensen,Smith, Larson, Johnson, Lydell, Gengler, Niehus, Foerster, Heinis, Niggeling, Nothem, Engeldinger, Wanderscheid

Chickasaw: Robinson, Colligan, Pierson/Pearson, Hawkins, Glass, Pangborn

Clarke: Sowers, Lee

Clayton: Scovel, Cagley, Hulverson/Halverson, Sass, Roth, Kamin, Wilke, Meye, Clark, Weideman/Wedeman, Stevens, Greene, Beckmann, Stutheit, Hempeler

Clinton: Berg, Wink/Wienke,Johnson, Halversen, Halverson, Halvorsdatter, Maklebust, Hansen, Johannesdatter,Dossland, Ask, Olson, Carter, Edwards, Hazlett, Whitaker, Coffman, Cunningham, Van Cruijningen, Alcorn, Chase, Hartson, Clark

Crawford: Endrulat, Reese, Jahn, Krause, Kutschinski, Wiese, Klaus, Eyer,Neddermeyer

Dallas: Hanlon, Brady, Shiffer, Cone, Ballentine, Andersdotter, Jonsson,Curfman, Nichols

Davis: Lohrengel, McGachey

Decatur: Davis, Newcomer, Lushbaugh, Webster, Roselle, Dale,Marksbury, Higgs, Weable, Anderson,Sly

Delaware: Klaus, Clark, Webb, Arnold, Duncan, Field, Alloway, Fuller, Anderson, Rexford, Paddleford

Des Moines: Peterson

Dickinson: Guthrie, Lambertus, Franker

Dubuque: Wentz, Consor, Krueger, Metcalf, Noesen, Nattrass, Robson, Daykin, Hoffmann,Heiter, Pauly, Gloesener, Kayser, Miller/Mueller, Jordan, Singer

Emmet: Hansen

Fayette: Glass, Pangborn, Kappes, Bodensteiner,Vanginderhuyser, Wise, De Temmerman, Georgi, Kern, Amundsen, Kerns,Beirschmitt, McCloskey, Gifford, Johnston, Tope, Mittelstedt, Wroe, Burns/Burnes, Clark, McCann, Houlsworth, Perry, Wait/Waite, Finch, Kuhens/Kuhnes

Floyd: Miller, Klaus, Reed, Stickney

Fremont:  Garcia, Enos, Davina

Guthrie:  Dilley

Grundy: Campbell, Whitehead, Miller

Hamilton: Teget, Toedt, Pahl, Wing,Johnson, Dale

Hancock:  Nix

Hardin: Wing, Johnson, Vinje, Kelsey

Harrison:  Kirley, McBride, Davis, Jordan, Lewis, Anderson, Bolte

Henry: House, Sample, Shelton,Allen

Howard: Osborn, Gifford, Cushing,Roberts

Humboldt: Hilbert

Ida: Beyer, Endrulat, Grell, Haase, Helkenn, Reese, Schubert, Bauer, Meyer,Paustian, Ruhser/Ruser, Schroeder, Sorensen, Wink/Wienke

Iowa: Duffy, Burns, Masteller,Gallagher, Burns, Kinney, Murphy, Duggan, Welch

Jackson: Berg, Meyer, Wink/Wienke,Johnson, Halversen, Halverson, Halvorsdatter, Maklebust, Hoffmann, Miller/Mueller, Johannesdatter, Naegle, Nagel, Mueller, Carter, Edwards, Zeimet,Winkel

Jasper: Belt, Hyde, Pahl, Toedt, Holliday, Hickey, Debolt/De Bolt, Ross, Nichols, Weigel

Johnson: Minnich/Minnick, Lyle,Crossen, Fitzgerald, McCarthy, James,Bigsby, Coffman, Kile

Jones: Hanlon, Brady

Keokuk: Wilson, Willson, King

Kossuth: Young, Hilbert, Becker, Richter, Sires

Linn: Stewart, Cue, Calhoon, Gaines, Rickert, Richard, Wagner, Poorman,Gates, Wilcox, Watson, Zimmerman, Richards, Bowman, Stevens, Webb

Louisa: Johnston, Herron, Ramsey, Smith, Hand, Vanloon

Lucas: Stevenson, Coffelt, Vickroy,Welch, Truman, Hickman, Hasting, Davis, Mumford, Cain, McGlothlen, Rodgers, Avitt, Reed,Springer, Graves, Meadows

Madison: Shutt, Black, Cashman, Benedict, Marchel, Wolfe, Peed, Ross, Debolt/DeBolt, Gates, Wilcox, Watson, Zimmerman, Richards, Bowman

Mahaska: Heberer, Howard, Burke, Conklin, Holliday, Adair, Ives, Lowry,Ferrell, Addis, Adkisson, Zeppernick, Williams, Parr, Hoskinson, Myers, Wymore,James, McMains

Marion: McCombs, Howard, Godwin, Barr, Wilson, Cashman, Williams, Newman

Marshall: Wantz, Bryant, Brown

Mitchell: Baker, Gaines, Mackin,Kinney, Gerbig, Decker, Galt, Tretton, Gemaehlich

Monona: Nepper,Ordway, Ziems, Freerking

Montgomery: Lee, Pittman

Muscatine: Orcutt, Allen, Kuiper, Heuer, Pasdach, Yeater, Huff, O’Brien,Cain/Kain/Kane, Cashman, Alcorn, Ipock, Yates,Freers,Schreurs, Washburn, Bigsby, Ager

O’Brien: Stewart

Osceola: Hamann, Schubert

Page: Nicolson, Teget, Cox, Krey

Plymouth: Storer, Gengler, Niehus, Foerster, Heinis, Niggeling, Nothem, Engeldinger, Wanderscheid

Polk:  Smith, Hanlon, Brady, O’Connell, Wilson,Beatty, Stevenson, Coffelt, Burnett, Scovel, Foutch,Halterman, Boatwright, Davis, Freel, Stewart,Johnson, Warren, Flesher, Deaton, Powell, Freel, Butler, Shiffer, Brooks,Holliday, Lawrence, Cooper, Shutt, Cone, Mason, Baber, Nalley, Higgs, Kirsher,Huggins, Jones, Debolt/De Bolt, Nichols, Klaus, Poorman, Gates, Wilcox, Watson,Zimmerman, Richards, Bowman, Hendricks, Compton, Giese

Pottawattamie:Shanahan, Gallup, Stuart, Dolan, Hale, Davis, Wires, Fitzgerald, McCarthy, Randles, James, Slingerland, Kirley, McBride

Poweshiek:Watson, Sebring, Krouskop, Carpenter, Krise

Ringgold: Hazen, McCurdy, Carpenter,Humphreys, Cone, Arnold, Thorla

Sac: Schroeder, Masteller,Staton, Ragsdale, Masteller

Scott: Conrad, DahlDall/Doll,Frauen, Grell, Haase, Hamann, Helkenn, Reese, Rusch, Steffen, Bauer, Schween,Heckt, Paustian, Ruhser/Ruser, Sorensen, Kivlin, Feeney, Baugh, Collins,Jacobs, Crouch, Wulfe, Brus, Aufdenspring,Murphy, Foley, Ginn, Mills, Jones, Reed, Elshorst

Shelby: Gallup

Sioux: Meyn

Story: McDowell, Allen, Wing,Page, Hansens, Guddal

Taylor: White, Pace, Stephens

Tama: Howard, Krise

Union: Krise

Van Buren: Downard, Payne, Freel, Miller, Marriott, Shipley, Watt/Watts

Wapello: Ward,Hartshorn, Lowery, Robertson

Warren: Stewart,Black, Halterman, Flesher, Turnipseed, Deaton, Freel, Shutt, Cashman, Braucht,Mason, Vickroy, Wiley, Douglas, Williams, Martindale, Pierce, Hasting, Michael,Daugherty, Grant, Davis, Stewart, Cue, Calhoon, Flowers, Crawford

Washington: Longwell, Jury, Phillips,Deen, Downing, Bradford, Lambert, Story, Carr

Wayne:  Hanlon, Jones

Webster:  Carpenter, Porter, Feeney, Carter, McQuiston, Mabe, Berry, Cackler, Doherty, Coles, Kellum, Stillions, Shiffer, Burrell, Meyn

Winnebago: Forrestal

Winneshiek: Dörr/Doerr, Untereiner, Kruger, Winke, Flage, Henning, Ludeking, Buddenberg, Carolan

Woodbury: Berg, Wink/Wienke, Storer,Jessip

Worth:  Halgrimson, Vold, Turvold

Iowan DNA : Quarterly Roundup

The Iowa DNA Project was formed at the end of November 2014 and is already beginning to paint a picture of  Iowan DNA.  While the project is for folks who have ancestors who lived in Iowa, or who have collateral lines who lived in Iowa, and our focus is on autosomal, aka Family Finder results, we also have members who already have or are in the process of having their mtDNA and YDNA tested.

Some of our project members have roots in Iowa going back almost 200 years. As of February 2015, descendents of settlers from most counties in Iowa are now represented, and this month will see additional results being produced, including those of a descendent of the bulk migration from Lippe, Germany to Allamakee County, Iowa.

New members are always welcome and are of course needed to move the project forward.

Featured image

Featured image

Featured image

A few facts have already begun to present themselves:

  • The lowest number of matches any member has is 280
  • The highest number of matches any member has is 1350
  • Success is often achieved with 2nd-4th cousins or closer.  Our members have on average 20 2nd-4th cousins each
  • As expected, the most common Y haplogroup is R and subclades, with I and its subclades the second most common
  • As expected,the most common mtDNA is H and its subcaldes, but there are a variety of other haplogroups also appearing

According to MyOrigins the bulk of project member ancestry is from :

  1. British Isles
  2. Western and Central Europe
  3. Scandinavian

There is also a moderate representation of ancestry from Southern Europe and Eastern Europe, in that order.

Ancestry also represented but less common, in order, is:

  • Northeast Asia
  • Finland and Siberia
  • Central Asia
  • Asia Minor
  • Eastern Middle East
  • Ashkenazi
  • West African

All members are encouraged to upload their raw DNA to Gedmatch to expand their match lists and to take advantage of additional ancestral admixture tools.

To finish, I would like to express my admiration and gratitude that the vast majority of project members have done so much to help themselves make the most of their results by uploading their trees, surnames, and most distant ancestors.  Many have also recruited family to test and are joining other projects which will also help them with their research. I wish you all continued success and look forward to working with you in the months ahead.

An Irish Sampler

Born a Duffy, and extremely proud of her Irish heritage, it was no surprise when FTDNA’s MyOrigins returned a 99% British Isles result for my grandmother Gladys.  After seeing she also returned a 1% Asia Minor result, I decided to compare her ancestry results to her group of Irish cousins to see what other ancestry they might or -might not- have in common.

Featured image

FTDNA is the go-to company for international testers, and Gladys has many matches living in Ireland, the UK, New Zealand and Australia.  Some have also uploaded their raw data to Gedmatch, which provides the opportunity to use advanced admixture tools to compare cousins who are either completely or predominately Irish.  Two of the most popular admixture tools for Europeans, Eurogenes K13 and Dodecad V3 have also published the average results of their Irish samples.  Those results are entered in the last column of each table*.

Our Cousins

  • Gladys and CK are known second cousins through the Kane family from Castlebar, County Mayo. Gedmatch predicts: 2.9 generations to their common ancestor
  • Bridget is a cousin with an ancestor upstream of those shared by Gladys and CK, through the Kane/Forrestal families from Castlebar, Co Mayo. Gedmatch predicts a shared ancestor at 4.8.
  • Sean is a Mackin cousin from Northern Ireland. Gedmatch predicts a shared ancestor at 4.3 generations
  • Dennis belongs to a group of Northern Irish cousins. Their common ancestor is estimated at 4.8 generations
  • SK is a cousin with a shared ancestor upstream of the Mayo Kane ancestors shared by Gladys and CK. Gedmatch predicts a shared ancestor at 4.8 generations.
  • Maire is a Northern Irish X match cousin, and is probably shares an upstream ancestor of our Mackin or McCloskey ancestors. A common ancestor is estimated at 4.6 generations

Eurogenes K13

Detailed information about the Eurogenes K13 tool can be found here.  Information about all the Eurogenes tools can be found here.  A spreadsheet detailing the average results by population, including Irish samples, can be found here.

Featured image

Figure 1

In addition to the broad breakdowns illustrated in Figure 1, Eurogenes K13 also provides an ‘oracle’.  This utility breaks down ancestry even further.  The ‘oracle’ attempts to match the tester’s DNA with the DNA of testers from various populations.  The closer the genetic distance (example @3.699) the better the DNA matches the population.

For each of the cousins, the Oracle 4 utility was run and the top 5 populations are listed below:


Using 1 population approximation:
1 Irish @ 3.699319
2 West_Scottish @ 4.227885
3 Orcadian @ 5.009747
4 Southwest_English @ 5.606747
5 North_Dutch @ 6.093086


Using 1 population approximation:
1 South_Dutch @ 3.740911
2 Southeast_English @ 4.757324
3 West_German @ 4.948592
4 Southwest_English @ 6.509983
5 Orcadian @ 6.739860


Using 1 population approximation:
1 Irish @ 4.181266
2 Southwest_English @ 4.201335
3 West_Scottish @ 4.536220
4 Orcadian @ 4.843127
5 Southeast_English @ 5.027599


Using 1 population approximation:
1 Southeast_English @ 4.672073
2 West_Scottish @ 4.773833
3 Southwest_English @ 4.905573
4 Orcadian @ 5.280790
5 Irish @ 5.639902


Using 1 population approximation:
1 Southeast_English @ 3.840825
2 Orcadian @ 4.607929
3 West_Scottish @ 4.867234
4 Southwest_English @ 5.397524
5 Irish @ 5.514109


Using 1 population approximation:
1 Irish @ 4.226087
2 West_Scottish @ 4.787307
3 Southwest_English @ 5.084749
4 Orcadian @ 5.592003
5 Southeast_English @ 7.030124


Using 1 population approximation:
1 Irish @ 2.728588
2 West_Scottish @ 3.401917
3 Orcadian @ 4.520518
4 Southwest_English @ 5.304957
5 North_Dutch @ 5.565923

The cousins with Kane ancestry from the port towns of Castlebar and Westport return nearly identical North Atlantic values that are lower than the Irish norm.  Their West Asian score is also almost identical and higher than the Irish average. Only two cousins, both from Castlebar return Sub Saharan results and they are slightly higher than the Irish average.  3 of the 4 Kane cousins return South Asian ancestry and it is also higher than the Irish norm.  Only one of the Northern Irish cousins returns Northeast African ancestry and it is at less than half of the Irish average. When looking at the oracle results, the Kane cousin who differs has a German ancestor, and the oracle matches him most closely to a South Dutch population, while the rest of the cousins most closely resemble to Irish population samples.

The Northern Irish cousin group shows more variety in general.  As seen in Figure 2, their Baltic scores are lower than the Irish average, and their West Asian scores are higher.

Dodecad V3

Detailed information about the Dodecad project can be found here.  A spreadsheet detailing the average results by population, including Irish samples, can be found here.

Featured image

Figure 2


Using 1 population approximation:
1 Argyll @ 2.802603
2 N._European @ 3.152682
3 CEU @ 3.180986
4 Orcadian @ 3.840527
5 Orkney @ 4.039654


Using 1 population approximation:
1 Argyll @ 1.383295
2 Orcadian @ 1.830747
3 Orkney @ 2.134289
4 CEU @ 2.153667
5 N._European @ 2.927236


Using 1 population approximation:
1 Argyll @ 5.047738
2 Orcadian @ 5.080379
3 N._European @ 5.158332
4 Orkney @ 5.187712
5 CEU @ 5.332207


Using 1 population approximation:
1 CEU @ 6.219530
2 N._European @ 7.462104
3 Argyll @ 7.730925
4 Orcadian @ 8.337189
5 German @ 8.603835


Using 1 population approximation:
1 Orcadian @ 0.850356
2 Orkney @ 1.155132
3 Argyll @ 2.134491
4 CEU @ 2.274293
5 N._European @ 3.791664


Using 1 population approximation:
1 Orkney @ 1.008123
2 Argyll @ 1.034154
3 Orcadian @ 1.225209
4 CEU @ 3.116245
5 N._European @ 3.219170


Using 1 population approximation:
1 Orkney @ 2.687200
2 Orcadian @ 2.962321
3 Argyll @ 3.461854
4 N._European @ 4.474788
5 CEU @ 4.554245

Much like the Eurogenes K13 tool, all of the cousins were most closely matched to British Isles populations, except for the one cousin with a German ancestor.  Oddly, all of our Irish cousins have much more Eastern European and much less Western European than the Irish samples reported by Dodecad.

Mixed Modes and Calculator Effect

To produce ‘mixed mode’ results, the tools compare your DNA to sample populations. The algorithm then calculates the differences or similarities, or ‘genetic distance’ between your DNA and the population in question. Mixed mode results are the estimate of the 1-4 most similar populations to your DNA.   The algorithms also attempt to estimate which combined populations, or ‘admixtures’ most closely resemble your DNA.  This is often referred to as a ‘best fit’, or best estimate.

The Eurogenes K13 oracle 4 populations gives a 1st choice guess of Gladys having 4 Irish grandparents.  Its next best guess is an Irish parent and a parent 1/2 Irish and 1/2 Scottish.  Both guesses are very good considering her known ancestry. Dodecad’s algorithm didn’t do quite so well!

Gladys Eurogenes K13

Using 4 populations approximation:
1 Irish + Irish + Irish + Irish @ 3.699319
2 Irish + Irish + Irish + West_Scottish @ 3.780499
3 Irish + Irish + West_Scottish + West_Scottish @ 3.893456
4 Irish + Irish + Irish + Southwest_English @ 3.898322
5 Irish + Irish + Irish + Orcadian @ 3.937483

Gladys Dodecad V3

Using 4 populations approximation:
1 British_Isles + French + Hungarians + Argyll @ 0.643529
2 British + French + Hungarians + Argyll @ 0.673814
3 British_Isles + French + Hungarians + N._European @ 0.727025
4 British_Isles + French + Hungarians + Argyll @ 0.735014
5 French + Hungarians + Kent + Argyll @ 0.758637

This is a young, growing science, and it is important to realize results will improve as more samples are taken and compared. 

No tool is 100% accurate and results must be taken as part of a work in progress. Also, different tools work better with different populations.  None the less, they are another tool at your disposal to use as a general guideline in your research.  Eurogene’s Polako points out, “users from the UK often come out much more continental European than they should. Some of them actually believe that this is because they’re genetically more Norman or Saxon than the average Brit. Nope, the real reason is what I call the ‘calculator effect’.”  Dodecad’s  explains, “This is when the algorithm produces different results for people who are part of the original ADMIXTURE runs that set up the allele frequencies used by the calculators, than those who aren’t, even though both sets of users are of exactly the same origin, and should expect basically identical results.”   More information about the calculator effect can be found here.

Cousin Collaboration: It Works!

Featured image

I wonder what great grandmother Erna would think of all of this?

DNA testing, no matter what company you test with or what type of test you take, is not going to neatly serve your heritage and family tree up on a silver platter.  Rather, DNA testing is only a single weapon in your arsenal, along with traditional research, family collaboration and perseverance.

My direct maternal, or mtDNA line has been one that I’ve banged my head against for decades.  During most of those decades I only knew my maternal lineage as far back as my great-great grandmother Marie Haeger.  Despite pestering family members, combing through records and making my tree public in order to connect with potential relatives, I had bupkis. After two decades of next to no progress, I accepted that I probably wouldn’t be learning much more.

Of course I tested my autosomal DNA, but given the mysterious nature of my maternal line, I considered the expense of mtDNA testing was also warranted.  By that time, I had found a little more about Marie Haeger’s family, and managed to add an additional 3 generations to our maternal line, where I again stalled out.    At that point, it seemed that if anything, I had been lucky to have learned as much as I had. I was content that finding any new tidbits on my maternal line would depend solely upon DNA breakthroughs.

When my mtDNA  results came in, we fell into one of the unusual haplogroups: W3.  By then I knew my maternal line had been living along the Baltic shore for centuries, and I found our haplogroup in keeping with our paper trail.  It looked as though my female ancestral line had traveled from Pakistan through the Caucasus Mountains, and decided to stay put in North Eastern Pomerania, rather than travel on with the rest of the group that finally settled in Finland.  When my grandmother’s Family Finder results came in, they supported that scenario.

As chance would have it, shortly after I tested my maternal grandmother at FTDNA, a previously unknown cousin happened across my entry at Genealogy.net.  Cousin Peter is also an avid genealogist, lives in Germany and our 4th great grandmothers Dorothea and Wilhemine were sisters.  He has been researching our family in the German records for years.

When we exchanged data I mentioned DNA testing, and shared my post covering my grandmother’s Family Finder and mtDNA results.  Peter hasn’t done DNA testing, but the news sparked a lively exchange of information and turned a new cousin into a friend.

Although Peter had been unaware of our Eastern DNA, he said, “Of course you’re right, if the DNA points to Slavic roots.  Slavs and Kashubians settled in the area many hundreds of years ago. Long before there were church books. The generation of your grandmother and generations before, felt safe as German, Prussia or Pomerania and not as Slavs. Many local and family names have still points to the Slavic or Kashubian roots.”

I was thrilled with both my new cousin and the new bits Peter had sent me. I hoped our DNA results gave him a little more insight into the distant ancestry of our family and added a little high tech flair to his traditional research.  Once again, I was content that this time surely we really had exhausted the surviving records.

With my various year end commitments, it took longer than I had hoped to begin keying in the years of hard work Peter had so graciously shared with me.  I picked the first PDF at random, which happened to be our direct maternal line, which ended with Sophia Friederike Schultz who had been born in 1771.

I’d already known Sophia’s father’s name, but cousin Peter also had the names of her brothers which were new to me. As soon I entered the names into my tree, an infamous Ancestry shaking leaf appeared.  We all know that shaking leaves must be taken with a mountain of salt, but when I clicked on it I discovered it was a distant cousin with whom I was already familiar and one that was also in Germany and also used the Luessin and Dresow Church records as a primary source of documentation.

She had added new information to her tree since the last time I looked.  She had the name of Dorothea and Wilhemine’s long-unknown mother, my 6th great grandmother Eleanora Marquardt. She had the church book entry connecting her as the mother of our Dorothea and Wilhemine.

I will be doing the traditional research rounds on my new great-grandma, and sharing the news with Cousin Peter.  Maybe he will test his DNA. I will invite my other German cousin to test as well.  Meanwhile, it will be a lot of work to check, translate and type in this new additional information and to update all of our Most Distant Maternal Ancestor entries at FTDNA to include Eleanora, but every key stroke will be worth it.  We all had to work together to get to this point.

I bought a FTDNA test. Now what?

Congratulations, you’ve taken the first step in bringing your family’s story to the next level!  Whether you bought a Family Finder, mtDNA or YDNA test, there are a few things you will want to do to get off on the right foot.

Once you have made your purchase, you’ll receive an email with a kit number and password.  The kit number will be your ‘username’ each time you log into your account.  You can of course change your password to anything you like.  To do so, go to your main, or Welcome page and find the ‘Change Password’ entry on the left hand side.

Featured image

Next, go to the ‘Manage Personal Information’ entry. It is directly above ‘Change’ Password’.

From the Manage Personal Information page, there are a number of choices you can make to increase your chances of being contacted by matches, and responded to when you make contact.  First, add a profile picture.  It will make your account stand out among the faceless sea of 4th cousins.  Also, it’ll make it harder for ’em to ignore you!  You may also want to write about your research goals in the ‘About Me’ box, or mention immediate family that has also tested.

At the top of the Manage Personal Information page, you will see 5 tabs.

Featured image

Until you get your bearings, it is good idea to leave all the settings at their default position. Still, you have a bit of work to do.

Account Settings: Genealogy

From the genealogy tab, you can choose your privacy settings.  This is also where you will enter the names and locations of your most distant ancestors.  Be sure to add their year of birth/death and locations.  From here, you can also list your family surnames.  This will help you connect with matches.  If they see a surname or location that is familiar to them, they are more likely to contact you and you are more likely to determine how your trees connect.  Everyone, without exception should fill in this basic information.

Account Settings: Match and Email Settings

There is one setting you should not touch:  Family Finder Matches & Email Notifications.  If you change any of the defaults, it will not only turn off email notifications at that level. It will turn off matching at that level.  You will no longer see those matches and they will no longer see you.

Welcome Page: Family Tree

FTDNA has recently changed the family tree interface, and truth be told it is not great.  They have already made improvements and let us hope they continue in that vein. Meanwhile, it is still a good idea to upload your tree.  Although it is cumbersome to navigate, the new version does have one very important feature, and that is the search box in the upper right corner.  If you see a match with a surname or location you recognize, you can click on their tree and enter either of those terms into the search box. They can do the same with your tree.  Et viola, a connection is made!

Featured image

To upload a family tree you must have a file that ends in ‘ged’. All major family tree programs will export a file in this format. Once your file is prepared, go to your Welcome Page and click ‘Family Tree’.

Select ‘Upload a Gedcom’ and choose your file.  Alternately, you may build your tree from scratch directly at FTDNA.


Now that you have covered the basics to help matches find you, there is one more thing that you can do to help you find them and more importantly figure out how you relate.  FTDNA has a large number of projects, from groups for specific surnames , to groups which study mtDNA or YDNA haplogroups to groups that study families from a particular region, such as the Iowa DNA Project.   For YDNA testers, it is vitally important to join your project if you are hoping to learn more about your haplogroup or your terminal snps.  Your project leader will be able to provide more information on your place in the phylotree and to offer advice on additional testing if you are interested.  To browse the available projects, go to the top of your Welcome page and choose the entry My Projects.  Joining is free and you can join as many as you think could be helpful.

MtDNA Tests

There is one setting that is important for people that have tested FMS or their Full Mitochondrial Sequence.  Those testers have gone beyond the basic level and have values known as, ‘Coding Region Mutations’.  Go to your Manage Personal Information Page, then your Account Settings Tab and choose Results Display Settings.  You will be directed to ‘Click Here’.  Choose ‘Who can view my mtDNA Coding Region mutations?’ and make sure ‘Project Administrators’ is selected.  After you have learned your mtDNA haplogroup, it will be very important that your group’s administrator can see your coding region mutations in order to know where you fit within your haplogroup.  Once that is determined, you will be able to learn more about your deep maternal ancestry and make the most of your test results.

Where is my Test?

If you have ordered a kit and it hasn’t reached you within two weeks, call FTDNA and have them send you a new one at no charge.  I order my kits from Ireland and they usually arrive from Texas within a week.  FTDNA can be reached here and at 713-868-1438.  For more information on how to get the best sample collection see here.

The Wait for Results

Featured imageThere is a good chance it will take about month from the time you order your kit before it is ‘batched’ or received by the lab and testing begins.  If all goes to plan, from that point, it will be another 3-4 weeks for your Family Finder test to be processed, and generally at least 8 weeks for mtDNA and yDNA testing to complete.  In the meantime, take the opportunity to work on your family tree, especially extending your collateral lines as that is where you will intersect with the majority of your matches.  Also, take advantage of the Forums and Learning Center at FTDNA and download their free ebook, which is available from your welcome page.