We have developed a likelihood method to identify moderately
distant genealogical relationships from genomewide scan data. The
aim is to compare the genotypes of many pairs of people and
identify those pairs most likely to be related to one another. We
have tested the algorithm using the genotypes of 170 Tasmanians
with multiple sclerosis recruited into a haplotype association
study. It is estimated from genealogical records that approximately
$65\%$ of Tasmania's current population of 470,000 are direct
descendants of the 13,000 female founders living in this island
state of Australia in the mid-nineteenth century. All cases and
four to five relatives of each case have been genotyped with
microsatellite markers at a genomewide average density of 4 cM.
Previous genealogical research has identified 51 pairwise
relationships linking 56 of the 170 cases. Testing the likelihood
calculation on these known relative pairs, we have good power to
identify relationships up to degree eight (e.g. third cousins once
removed). Applying the algorithm to all other pairs of cases, we
have identified a further 61 putative relative pairs, with an
estimated false discovery rate of $10\%$. The power to identify
genealogical links should increase when the new, denser sets of SNP
markers are used. Except in populations where there is a searchable
electronic database containing virtually all genealogical links in
the past six generations, the algorithm should be a useful aid for
genealogists working on gene-mapping projects, both linkage studies
and association studies.
%0 Journal Article
%1 231
%A Stankovich, J.
%A Bahlo, M.
%A Rubio, J.P.
%A Wilkinson, C.R.
%A Thomson, R.
%A Banks, A.
%A Ring, M.
%A Foote, S.J.
%A Speed, T.P.
%D 2005
%J Human Genetics
%K imported
%N 2--3
%P 188--199
%T Identifying nineteenth century genealogical links from genotypes
%V 117
%X We have developed a likelihood method to identify moderately
distant genealogical relationships from genomewide scan data. The
aim is to compare the genotypes of many pairs of people and
identify those pairs most likely to be related to one another. We
have tested the algorithm using the genotypes of 170 Tasmanians
with multiple sclerosis recruited into a haplotype association
study. It is estimated from genealogical records that approximately
$65\%$ of Tasmania's current population of 470,000 are direct
descendants of the 13,000 female founders living in this island
state of Australia in the mid-nineteenth century. All cases and
four to five relatives of each case have been genotyped with
microsatellite markers at a genomewide average density of 4 cM.
Previous genealogical research has identified 51 pairwise
relationships linking 56 of the 170 cases. Testing the likelihood
calculation on these known relative pairs, we have good power to
identify relationships up to degree eight (e.g. third cousins once
removed). Applying the algorithm to all other pairs of cases, we
have identified a further 61 putative relative pairs, with an
estimated false discovery rate of $10\%$. The power to identify
genealogical links should increase when the new, denser sets of SNP
markers are used. Except in populations where there is a searchable
electronic database containing virtually all genealogical links in
the past six generations, the algorithm should be a useful aid for
genealogists working on gene-mapping projects, both linkage studies
and association studies.
@article{231,
abstract = {We have developed a likelihood method to identify moderately
distant genealogical relationships from genomewide scan data. The
aim is to compare the genotypes of many pairs of people and
identify those pairs most likely to be related to one another. We
have tested the algorithm using the genotypes of 170 Tasmanians
with multiple sclerosis recruited into a haplotype association
study. It is estimated from genealogical records that approximately
$65\%$ of Tasmania's current population of 470,000 are direct
descendants of the 13,000 female founders living in this island
state of Australia in the mid-nineteenth century. All cases and
four to five relatives of each case have been genotyped with
microsatellite markers at a genomewide average density of 4 cM.
Previous genealogical research has identified 51 pairwise
relationships linking 56 of the 170 cases. Testing the likelihood
calculation on these known relative pairs, we have good power to
identify relationships up to degree eight (e.g. third cousins once
removed). Applying the algorithm to all other pairs of cases, we
have identified a further 61 putative relative pairs, with an
estimated false discovery rate of $10\%$. The power to identify
genealogical links should increase when the new, denser sets of SNP
markers are used. Except in populations where there is a searchable
electronic database containing virtually all genealogical links in
the past six generations, the algorithm should be a useful aid for
genealogists working on gene-mapping projects, both linkage studies
and association studies.},
added-at = {2008-10-17T17:04:38.000+0200},
author = {Stankovich, J. and Bahlo, M. and Rubio, J.P. and Wilkinson, C.R. and Thomson, R. and Banks, A. and Ring, M. and Foote, S.J. and Speed, T.P.},
biburl = {https://www.bibsonomy.org/bibtex/284fd8dd0f9fbcd4c5669a7fbdc82de70/biobibs_matthew},
id = {info:sici/0340-6717(2005)117<188:INCGLF>2.0.CO;2-T,
info:pmid/15883841},
interhash = {197ea02968f142202a3af1e1b1315f87},
intrahash = {84fd8dd0f9fbcd4c5669a7fbdc82de70},
issn = {0340-6717, 1432-1203},
journal = {Human Genetics},
keywords = {imported},
number = {2--3},
pages = {188--199},
timestamp = {2008-10-17T17:04:39.000+0200},
title = {Identifying nineteenth century genealogical links from genotypes},
volume = 117,
year = 2005
}