ArticleHuman heredity2008
Multilocus lod scores in large pedigrees: combination of exact and approximate calculations.
Article in Human heredity, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
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Who cites it
31 citing papers in PubMed.
- Variant Prioritization by Pedigree-Based Haplotyping.Genetic epidemiology · 2026Article
- Genomic Exploration of Essential Hypertension in African-Brazilian Quilombo Populations: A Comprehensive Approach With Pedigree Analysis and Family-Based Association Studies.Journal of the American Heart Association · 2025Article
- Genetic analysis of cognitive preservation in the midwestern Amish reveals a novel locus on chromosome 2.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Genetic analysis of cognitive preservation in the midwestern Amish reveals a novel locus on chromosome 2.medRxiv : the preprint server for health sciences · 2023Article
- Familial multiple discoid fibromas is linked to a locus on chromosome 5 including the FNIP1 gene.Journal of human genetics · 2023Article
- A fast linkage method for population GWAS cohorts with related individuals.Genetic epidemiology · 2023Article
- A rare genomic duplication in 2p14 underlies autosomal dominant hearing loss DFNA58.Human molecular genetics · 2020Article
- Analysis of pedigree data in populations with multiple ancestries: Strategies for dealing with admixture in Caribbean Hispanic families from the ADSP.Genetic epidemiology · 2018Article
- Whole-genome characterization in pedigreed non-human primates using genotyping-by-sequencing (GBS) and imputation.BMC genomics · 2016Article
- FamPipe: An Automatic Analysis Pipeline for Analyzing Sequencing Data in Families for Disease Studies.PLoS computational biology · 2016Article
- Genetic Candidate Variants in Two Multigenerational Families with Childhood Apraxia of Speech.PloS one · 2016Article
- PBAP: a pipeline for file processing and quality control of pedigree data with dense genetic markers.Bioinformatics (Oxford, England) · 2015Article
- Leveraging Identity-by-Descent for Accurate Genotype Inference in Family Sequencing Data.PLoS genetics · 2015Article
- Combinatorial Conflicting Homozygosity (CCH) analysis enables the rapid identification of shared genomic regions in the presence of multiple phenocopies.BMC genomics · 2015Article
- Pedigree-Free Descent-Based Gene Mapping from Population Samples.Human heredity · 2015Article
- PedBLIMP: extending linear predictors to impute genotypes in pedigrees.Genetic epidemiology · 2014Article
- A statistical framework to guide sequencing choices in pedigrees.American journal of human genetics · 2014Article
- Identity-by-descent graphs offer a flexible framework for imputation and both linkage and association analyses.BMC proceedings · 2014Article
- Visualization of haplotype sharing patterns in pedigree samples.Human heredity · 2014Article
- Efficient identification of equivalences in dynamic graphs and pedigree structures.Journal of computational biology : a journal of computational molecular cell biology · 2013Article
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2 authors.
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Abstract
To detect the positions of disease loci, lod scores are calculated at multiple chromosomal positions given trait and marker data on members of pedigrees. Exact lod score calculations are often impossible when the size of the pedigree and the number of markers are both large. In this case, a Markov Chain Monte Carlo (MCMC) approach provides an approximation. However, to provide accurate results, mixing performance is always a key issue in these MCMC methods. In this paper, we propose two methods to improve MCMC sampling and hence obtain more accurate lod score estimates in shorter computation time. The first improvement generalizes the block-Gibbs meiosis (M) sampler to multiple meiosis (MM) sampler in which multiple meioses are updated jointly, across all loci. The second one divides the computations on a large pedigree into several parts by conditioning on the haplotypes of some 'key' individuals. We perform exact calculations for the descendant parts where more data are often available, and combine this information with sampling of the hidden variables in the ancestral parts. Our approaches are expected to be most useful for data on a large pedigree with a lot of missing data.
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