A method for detecting IBD regions simultaneously in multiple individuals--with applications to disease genetics
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A method for detecting IBD regions simultaneously in multiple individuals--with applications to disease genetics. / Moltke, Ida; Albrechtsen, Anders; Hansen, Thomas V O; Nielsen, Finn C; Nielsen, Rasmus.
In: Genome Research, Vol. 21, No. 7, 2011, p. 1168-80.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - A method for detecting IBD regions simultaneously in multiple individuals--with applications to disease genetics
AU - Moltke, Ida
AU - Albrechtsen, Anders
AU - Hansen, Thomas V O
AU - Nielsen, Finn C
AU - Nielsen, Rasmus
PY - 2011
Y1 - 2011
N2 - All individuals in a finite population are related if traced back long enough and will, therefore, share regions of their genomes identical by descent (IBD). Detection of such regions has several important applications-from answering questions about human evolution to locating regions in the human genome containing disease-causing variants. However, IBD regions can be difficult to detect, especially in the common case where no pedigree information is available. In particular, all existing non-pedigree based methods can only infer IBD sharing between two individuals. Here, we present a new Markov Chain Monte Carlo method for detection of IBD regions, which does not rely on any pedigree information. It is based on a probabilistic model applicable to unphased SNP data. It can take inbreeding, allele frequencies, genotyping errors, and genomic distances into account. And most importantly, it can simultaneously infer IBD sharing among multiple individuals. Through simulations, we show that the simultaneous modeling of multiple individuals makes the method more powerful and accurate than several other non-pedigree based methods. We illustrate the potential of the method by applying it to data from individuals with breast and/or ovarian cancer, and show that a known disease-causing mutation can be mapped to a 2.2-Mb region using SNP data from only five seemingly unrelated affected individuals. This would not be possible using classical linkage mapping or association mapping.
AB - All individuals in a finite population are related if traced back long enough and will, therefore, share regions of their genomes identical by descent (IBD). Detection of such regions has several important applications-from answering questions about human evolution to locating regions in the human genome containing disease-causing variants. However, IBD regions can be difficult to detect, especially in the common case where no pedigree information is available. In particular, all existing non-pedigree based methods can only infer IBD sharing between two individuals. Here, we present a new Markov Chain Monte Carlo method for detection of IBD regions, which does not rely on any pedigree information. It is based on a probabilistic model applicable to unphased SNP data. It can take inbreeding, allele frequencies, genotyping errors, and genomic distances into account. And most importantly, it can simultaneously infer IBD sharing among multiple individuals. Through simulations, we show that the simultaneous modeling of multiple individuals makes the method more powerful and accurate than several other non-pedigree based methods. We illustrate the potential of the method by applying it to data from individuals with breast and/or ovarian cancer, and show that a known disease-causing mutation can be mapped to a 2.2-Mb region using SNP data from only five seemingly unrelated affected individuals. This would not be possible using classical linkage mapping or association mapping.
KW - Alleles
KW - Breast Neoplasms
KW - Chromosome Mapping
KW - Computer Simulation
KW - Databases, Genetic
KW - Female
KW - Genetic Linkage
KW - Genome, Human
KW - Genome-Wide Association Study
KW - Genotype
KW - Humans
KW - Markov Chains
KW - Models, Genetic
KW - Monte Carlo Method
KW - Mutation
KW - Ovarian Neoplasms
KW - Pedigree
KW - Polymorphism, Single Nucleotide
KW - Ubiquitin-Protein Ligases
U2 - 10.1101/gr.115360.110
DO - 10.1101/gr.115360.110
M3 - Journal article
C2 - 21493780
VL - 21
SP - 1168
EP - 1180
JO - Genome Research
JF - Genome Research
SN - 1088-9051
IS - 7
ER -
ID: 37670471