i tried out that tool and put the setting on 25 chromosomes showing both heterozygous and homozygous results. that results were kind of confusing. here's the copy/paste of the results. can anyone make sense of these results?
RSID Chr Position (B36) Genotype %Occurrence Gene Matching Origins
rs10088365 8 10134808 Ag 0.017507 MSRA
rs2240801 17 46105801 Ag 0.0439136 ABCC3
rs829062 12 21845568 gT 0.0525578 ABCC9
rs1069915 12 21813381 aC 0.0701262 KCNJ8
rs8177743 10 6035056 cT 0.0875503 IL15RA Eritrea
rs35335722 12 10202159 aG 0.113995
rs11568365 2 169560131 GG 0.123444 SPC25
rs12570091 10 128159445 Ag 0.137011 C10orf90
rs12435710 14 57808196 Ct 0.140723 PSMA3 Guatemala
Mayan
Mexico
New Mexico, USA
rs17837645 7 155705267 Ag 0.145615 Croatia
rs8105775 19 4459945 Ag 0.145647 KIAA1881
rs267034 5 117010501 aC 0.16672 Colombia
East Asian
rs12595405 15 79807815 cT 0.17784 Mexico
rs3739806 9 86681441 Ct 0.178494 Switzerland
rs2299900 7 139328532 cT 0.204786 JHDM1D Guatemala
rs3756787 6 131999548 aG 0.209723 Ecuador
El Salvador
Ireland
Norway
rs2297632 1 94289754 CC 0.220193 ABCA4 East Asian
Norway
rs10743868 12 10113019 cT 0.221072 France
Poland
rs28364601 2 10502815 Ag 0.23511 HPCAL1 Guatemala
Mayan
Mexico
rs1575033 7 143505793 Ct 0.253752 ARHGEF5 Guatemala
rs12494041 3 115039120 aG 0.262904 Iran
rs12675844 8 137159846 Ag 0.268904 Guatemala
Mayan
rs12492542 3 114850862 Ct 0.2734 KIAA2018 Colombia
Iran
Mexico
rs4147824 1 94333563 CC 0.278009
rs433032 3 13368384 GG 0.278087 NUP210
does anyone here understand
Those are the SNP markers in the test kit that are rarely found around the world based on a database used by the person that wrote the program. http://pngu.mgh.harvard.edu/~purcell/
I went to his tools site at http://pngu.mgh.harvard.edu/~purcell/details.html and then to the PLINK which is used in a lot of studies.
In the resources link he shows HapMap as a PLINK fileset.
http://pngu.mgh.harvard.edu/~purcell/plink/res.shtml
The International HapMap Project is a multi-country effort to identify and catalog genetic similarities and differences in human beings.
http://hapmap.ncbi.nlm.nih.gov/thehapmap.html.en
Both HapMap and Human Genome Diversity Project are datasets or filesets or databases of invidividuals from around the world whose genomes were analyzed.
HGDP (Human Genome Diversity Project) was started by Stanford University. http://www.hagsc.org/hgdp/
Most biogeographical analysis calculators such as FTDNA, 23andme, AncestryDNA, Dienekes' Dodecad, Eurogenes, and Harrappaworld, use one of the two or both databases as a source.
The country name beside the rare SNP shows where the rare SNP markers are mostly found. To read up on an SNP see http://www.isogg.org/wiki/SNP
For more info on RSIDs (reference snp cluster id) see https://www.ncbi.nlm.nih.gov/books/NBK44417/
Armando
does anyone here understand
why are some of the snp's located in area far away from each other like for example rs3756787 and rs2297632. i'm kind of confused about the eritea one also. i don't think the trans-atlantic slave trade imported slaves from that far. I wonder how my mom got a gene that's mostly found in east africa.
does anyone here understand
The SNPs are far apart from each other because they are only the rare SNPs that are listed out of the 682,549 tested by Ancestry.com. SNP markers occur randomly so two SNP events could have occurred in one generation in completely different chromosomes.
Having a rare SNP that is found in Eritrea does not mean that it was passed down through the slave trade and it does not mean it was less than 500 years old. It could be an SNP that is 60,000 years old and is from the Out of Africa event and any of the multiple immigration events could have passed it down to an ancestor of your mother's. It could have have been a coincidence and your mother's ancestors also had the mutation from a different ancestor than the person from Eritrea had.
Armando
does anyone here understand
so an old snp can be rare. I thought only newer ones were rare
does anyone here understand
I tested a person with only northern European ancestry and they show rare each individual rare SNP is found all over the world. So either they are rare SNPs that coincidentally happened in multiple people or they are rare SNPs that are ancient. The Rare SNP (minor alleles) Utility doesn't seem to be much help.
Admixture and One-to-many matches are the tools that are the most useful.
Armando
does anyone here understand
the admixture tools were kind of confusing. some didn't even test for native american, and some cranked out some weird results. the mldp-22 1,2,3 population approximation part was confusing especially since miwok appeared on the lists more often than mexican
does anyone here understand
Stick with Eurogenes K13. It is the latest tool. Plus you can compare your mother's results with the populations in the spreadsheet that has the source populations. https://docs.google.com/spreadsheet/ccc?key=0Ato3EYTdM8lQdEUtZjRwTkQxRz…
Add Amerindian and Siberian for the Native American total.
Iberians are mainly North Atlantic, West Med, East Med, Baltic, and West Asian. They are 1% or less for Sub-Saharan.
Any Sub-Saharan that shows up in the result at more than the 1% should be from mulato ancestors. You also have to consider that the Amerindian portion should make the Sub-Saharan from Iberians to be proportionally lower.
You can also compare your results with the one to many matches by putting their kit numbers into Eurogenes K13. Of course it helps if you know the people and their trees. The gedcom of the individuals that have uploaded their tree to the site is available in the one to many match list.
You could also use Eurogenes K36 for a result similar to Ancestry.com, FTDNA, and 23andme.
Armando
does anyone here understand
thanks for sharing the link to the spreadsheet, here's my results for the k13
North_Atlantic 23.52%
Baltic 3.72%
West_Med 15.69%
West_Asian 6.65%
East_Med 7.08%
Red_Sea 1.21%
South_Asian 0.52%
East_Asian 1.29%
Siberian 2.44%
Amerindian 31.71%
Oceanian 0.13%
Northeast_African 1.59%
Sub-Saharan 4.46%
i'm going to compare my results to others
does anyone here understand
thanks for sharing the link to the spreadsheet, here's my results for the k13
North_Atlantic 23.52%
Baltic 3.72%
West_Med 15.69%
West_Asian 6.65%
East_Med 7.08%
Red_Sea 1.21%
South_Asian 0.52%
East_Asian 1.29%
Siberian 2.44%
Amerindian 31.71%
Oceanian 0.13%
Northeast_African 1.59%
Sub-Saharan 4.46%
i'm going to compare my mom's results to others