ArticleBioinformatics (Oxford, England)2014
FISH: fast and accurate diploid genotype imputation via segmental hidden Markov model.
Article in Bioinformatics (Oxford, England), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 17 papers, 9 of them syntheses that pooled it.
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Who cites it
17 citing papers in PubMed, 9 syntheses or guidelines pooled it.
- Identification of pleiotropic loci underlying hip bone mineral density and trunk lean mass.Journal of human genetics · 2021Pooled it
- Three pleiotropic loci associated with bone mineral density and lean body mass.Molecular genetics and genomics : MGG · 2021Pooled it
- Four pleiotropic loci associated with fat mass and lean mass.International journal of obesity (2005) · 2020Pooled it
- Two novel pleiotropic loci associated with osteoporosis and abdominal obesity.Human genetics · 2020Pooled it
- Identification of a 1p21 independent functional variant for abdominal obesity.International journal of obesity (2005) · 2019Pooled it
- Pooled it
- Genomic variants at 20p11 associated with body fat mass in the European population.Obesity (Silver Spring, Md.) · 2017Pooled it
- Association of 3q13.32 variants with hip trochanter and intertrochanter bone mineral density identified by a genome-wide association study.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2016Pooled it
- Pooled it
- BiU-Net: A Biologically Informed U-Net for Genotype Imputation.Research square · 2025Article
- Pleiotropic genomic variants at 17q21.31 associated with bone mineral density and body fat mass: a bivariate genome-wide association analysis.European journal of human genetics : EJHG · 2021Article
- Pleiotropic loci underlying bone mineral density and bone size identified by a bivariate genome-wide association analysis.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2020Article
- A Review of Integrative Imputation for Multi-Omics Datasets.Frontiers in genetics · 2020Review
- Two functional variants at 6p21.1 were associated with lean mass.Skeletal muscle · 2019Article
- Genome-wide identification of mOsteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2018Article
- Genome-Wide Identification of NFrontiers in genetics · 2018Article
- Unified tests for fine-scale mapping and identifying sparse high-dimensional sequence associations.Bioinformatics (Oxford, England) · 2016Article
Corrections and comments
- Erratum issued
Authors and funding
6 authors.
Funding
Abstract
motivationFast and accurate genotype imputation is necessary for facilitating gene-mapping studies, especially with the ever increasing numbers of both common and rare variants generated by high-throughput-sequencing experiments. However, most of the existing imputation approaches suffer from either inaccurate results or heavy computational demand.
resultsIn this article, aiming to perform fast and accurate genotype-imputation analysis, we propose a novel, fast and yet accurate method to impute diploid genotypes. Specifically, we extend a hidden Markov model that is widely used to describe haplotype structures. But we model hidden states onto single reference haplotypes rather than onto pairs of haplotypes. Consequently the computational complexity is linear to size of reference haplotypes. We further develop an algorithm 'merge-and-recover (MAR)' to speed up the calculation. Working on compact representation of segmental reference haplotypes, the MAR algorithm always calculates an exact form of transition probabilities regardless of partition of segments. Both simulation studies and real-data analyses demonstrated that our proposed method was comparable to most of the existing popular methods in terms of imputation accuracy, but was much more efficient in terms of computation. The MAR algorithm can further speed up the calculation by several folds without loss of accuracy. The proposed method will be useful in large-scale imputation studies with a large number of reference subjects. AVAILABILITY: The implemented multi-threading software FISH is freely available for academic use at https://sites.google.com/site/lzhanghomepage/FISH.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.