ArticleBMC bioinformatics2012
Detection of identity by descent using next-generation whole genome sequencing data.
Article in BMC bioinformatics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Refining rare disease variant discovery in an isolated Andean community through imputation-enhanced IBD and kinship inference from whole exome sequencing data.Human molecular genetics · 2025Article
- Kinship Decouple and Phenotype Selection (KDPS): a tool for phenotype-aware decoupling of related subjects.Briefings in bioinformatics · 2025Article
- Beyond broad strokes: sociocultural insights from the study of ancient genomes.Nature reviews. Genetics · 2020Review
- Identity by descent analysis identifies founder events and linksNPJ genomic medicine · 2020Article
- The time and place of European admixture in Ashkenazi Jewish history.PLoS genetics · 2017Article
- Rapidly Registering Identity-by-Descent Across Ancestral Recombination Graphs.Journal of computational biology : a journal of computational molecular cell biology · 2016Article
- Atlas of Cryptic Genetic Relatedness Among 1000 Human Genomes.Genome biology and evolution · 2016Article
- hsphase: an R package for pedigree reconstruction, detection of recombination events, phasing and imputation of half-sib family groups.BMC bioinformatics · 2014Article
- Whole-genome haplotyping approaches and genomic medicine.Genome medicine · 2014Article
- HapFABIA: identification of very short segments of identity by descent characterized by rare variants in large sequencing data.Nucleic acids research · 2013Article
- Detecting identity by descent and estimating genotype error rates in sequence data.American journal of human genetics · 2013Article
- Gene hunting in autoinflammation.Clinical and translational allergy · 2013Article
- Detecting identity by descent and homozygosity mapping in whole-exome sequencing data.PloS one · 2012Article
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Authors and funding
8 authors.
Funding
Abstract
backgroundIdentity by descent (IBD) has played a fundamental role in the discovery of genetic loci underlying human diseases. Both pedigree-based and population-based linkage analyses rely on estimating recent IBD, and evidence of ancient IBD can be used to detect population structure in genetic association studies. Various methods for detecting IBD, including those implemented in the soft- ware programs fastIBD and GERMLINE, have been developed in the past several years using population genotype data from microarray platforms. Now, next-generation DNA sequencing data is becoming increasingly available, enabling the comprehensive analysis of genomes, in- cluding identifying rare variants. These sequencing data may provide an opportunity to detect IBD with higher resolution than previously possible, potentially enabling the detection of disease causing loci that were previously undetectable with sparser genetic data.
resultsHere, we investigate how different levels of variant coverage in sequencing and microarray genotype data influences the resolution at which IBD can be detected. This includes microarray genotype data from the WTCCC study, denser genotype data from the HapMap Project, low coverage sequencing data from the 1000 Genomes Project, and deep coverage complete genome data from our own projects. With high power (78%), we can detect segments of length 0.4 cM or larger using fastIBD and GERMLINE in sequencing data. This compares to similar power to detect segments of length 1.0 cM or higher with microarray genotype data. We find that GERMLINE has slightly higher power than fastIBD for detecting IBD segments using sequencing data, but also has a much higher false positive rate.
conclusionWe further quantify the effect of variant density, conditional on genetic map length, on the power to resolve IBD segments. These investigations into IBD resolution may help guide the design of future next generation sequencing studies that utilize IBD, including family-based association studies, association studies in admixed populations, and homozygosity mapping studies.
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