Your nearest IBS neighbors (up to DOD603)

I have calculated your nearest identity-by-state (IBS) neighbors based on the same set of ~146K markers used for the standard K=10 analysis.

As explained here, it is not always the case that your nearest neighbors will belong to the same ethnic group as you. For closely related groups in the global context (e.g., Europeans), it's quite possible for a member of a different group to be more similar to you than a member of your own.

I am distributing the data as an R object. You must first install R, and then you can open this object by double-clicking on it (in Windows), or by using the File->Load Workspace menu within R. Then, you simply enter the following command at the prompt:

closest("DBV001")

Replace "DBV001" with your own project ID. If that ID is not included in the data, or you mistyped it, you will get an error message:

closest("qwerty")

[1] "This ID is not included"

Otherwise, you will get your results:

closest("DBV001")

[1] "Your nearest neighbor is 0.05 standard deviations more distant to you than for the average project participant"

RANK ID IBS

V3 "1" "DBV001" "1"

V133 "2" "DOD151" "0.749907"

V313 "3" "DOD344" "0.749559"

V943 "4" "Ashkenazy_Jews" "0.749298"

V50 "5" "DOD051" "0.74926"

V935 "6" "Ashkenazy_Jews" "0.749082"

V944 "7" "Ashkenazy_Jews" "0.749018"

V243 "8" "DOD272" "0.748985"

V25 "9" "DOD022" "0.748982"

V157 "10" "DOD179" "0.748904"

V942 "11" "Ashkenazy_Jews" "0.748822"

V939 "12" "Ashkenazy_Jews" "0.748821"

V954 "13" "Ashkenazy_Jews" "0.748767"

V251 "14" "DOD280" "0.748607"

V936 "15" "Ashkenazy_Jews" "0.748582"

V940 "16" "Ashkenazy_Jews" "0.748529"

V950 "17" "Ashkenazy_Jews" "0.748515"

V949 "18" "Ashkenazy_Jews" "0.748398"

V201 "19" "DOD228" "0.748382"

V308 "20" "DOD338" "0.748344"

By default, this produces the first 20 closest IBS matches. You can change this behavior by entering:

closest("DBV001", k=50)

Notice, that the sentence: [1] "Your nearest neighbor is 0.05 standard deviations more distant to you than for the average project participant" gives you an idea of how close your nearest neighbor is to you compared to other Project members.

For people of well-represented groups, their nearest neighbor is likely to be closer to them than average.

I have also included the 692 reference individuals from the standard K=10 analysis set, so your list of closest neighbors will include both DOD-labeled project participants, as well as reference individuals.

IBS similarity matrix and Population Concordance Ratio for Dodecad populations

In Dienekes' Anthropology Blog, I presented a new method of comparing populations, the population concordance ratio. You can refer to that post for the rationale, definitions, and code, but for the present, I will just say that this ratio estimates the probability that two random individuals from a population A are more similar to each other than either of them is to a random individual from another population B. Its expected value ranges from 0.25 (two very similar populations) to 1 (two very dissimilar populations).

Another common way of comparing populations is by computing an identity-by-state (IBS) similarity matrix. Comparing the genomes of two individuals across many loci, you can get a number (IBS) ranging beteween 0 and 1: in humans 0 is almost never encountered, as two random individuals may share some alleles in common by pure chance, while 1 indicates either monozygotic twins or a clerical error.

I have computed these two statistics over populations of the Dodecad Project with at least 5 individuals. The analysis is based on 282,409 SNPs with a 99%+ genotyping rate over the combined sample.

The results can be found in this spreadsheet.

[NOTE: I have taken down the spreadsheet on Apr 15, in order to investigate a possible error in the Brazilian_D sample]

[NOTE II: The results seem to be correct, so spreadsheet is back up]

For the population concordance ratio each row represents an estimate of the probability that two individuals from that population are more similar to each other than either of them is to a member from a population in each column; this is an asymmetric matrix.

Below are some visualizations of these statistics for the Greek_D sample.

First, the IBS similarity matrix. These ranged between 0.70383 and 0.73689, so I have subtracted 0.7 in order to bring out the scale of the differences.

Second, the population concordance ratio: