ArticleGenetics, selection, evolution : GSE2018
Hybrid peeling for fast and accurate calling, phasing, and imputation with sequence data of any coverage in pedigrees.
Article in Genetics, selection, evolution : GSE, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
27 citing papers in PubMed, 78 citations in OpenAlex.
- Quantifying the Evolutionary Potential for Delta Smelt Persistence in a Warming Habitat.Evolutionary applications · 2026Article
- Quantifying the evolutionary potential for Delta Smelt persistence in a warming habitat.bioRxiv : the preprint server for biology · 2026Article
- A vision of how low-coverage sequence data should contribute to genetic evaluation in the future.Journal of animal science · 2025Article
- Targeted genotyping-by-sequencing of potato and data analysis with R/polyBreedR.The plant genome · 2024Article
- Species-wide genomics of kākāpō provides tools to accelerate recovery.Nature ecology & evolution · 2023Article
- Using residual regressions to quantify and map signal leakage in genomic prediction.Genetics, selection, evolution : GSE · 2023Article
- Using pre-selected variants from large-scale whole-genome sequence data for single-step genomic predictions in pigs.Genetics, selection, evolution : GSE · 2023Article
- A genome-wide association study for loin depth and muscle pH in pigs from intensely selected purebred lines.Genetics, selection, evolution : GSE · 2023Article
- Selection, recombination and population history effects on runs of homozygosity (ROH) in wild red deer (Cervus elaphus).Heredity · 2023Article
- Multi-line ssGBLUP evaluation using preselected markers from whole-genome sequence data in pigs.Frontiers in genetics · 2023Article
- Interrogating the Human Diplome: Computational Methods, Emerging Applications, and Challenges.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Additive and non-additive genetic variance in juvenile Sitka spruce (Tree genetics & genomes · 2023Article
- Genomic prediction with whole-genome sequence data in intensely selected pig lines.Genetics, selection, evolution : GSE · 2022Article
- Rare and population-specific functional variation across pig lines.Genetics, selection, evolution : GSE · 2022Article
- Genetic architecture and major genes for backfat thickness in pig lines of diverse genetic backgrounds.Genetics, selection, evolution : GSE · 2021Article
- Genetic variation in recombination rate in the pig.Genetics, selection, evolution : GSE · 2021Article
- The Future of Livestock Management: A Review of Real-Time Portable Sequencing Applied to Livestock.Genes · 2020Review
- AlphaFamImpute: high-accuracy imputation in full-sib families from genotype-by-sequencing data.Bioinformatics (Oxford, England) · 2020Article
- Accuracy of whole-genome sequence imputation using hybrid peeling in large pedigreed livestock populations.Genetics, selection, evolution : GSE · 2020Article
- Evaluation of sequencing strategies for whole-genome imputation with hybrid peeling.Genetics, selection, evolution : GSE · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
backgroundIn this paper, we extend multi-locus iterative peeling to provide a computationally efficient method for calling, phasing, and imputing sequence data of any coverage in small or large pedigrees. Our method, called hybrid peeling, uses multi-locus iterative peeling to estimate shared chromosome segments between parents and their offspring at a subset of loci, and then uses single-locus iterative peeling to aggregate genomic information across multiple generations at the remaining loci.
resultsUsing a synthetic dataset, we first analysed the performance of hybrid peeling for calling and phasing genotypes in disconnected families, which contained only a focal individual and its parents and grandparents. Second, we analysed the performance of hybrid peeling for calling and phasing genotypes in the context of a full general pedigree. Third, we analysed the performance of hybrid peeling for imputing whole-genome sequence data to non-sequenced individuals in the population. We found that hybrid peeling substantially increased the number of called and phased genotypes by leveraging sequence information on related individuals. The calling rate and accuracy increased when the full pedigree was used compared to a reduced pedigree of just parents and grandparents. Finally, hybrid peeling imputed accurately whole-genome sequence to non-sequenced individuals.
conclusionsWe believe that this algorithm will enable the generation of low cost and high accuracy whole-genome sequence data in many pedigreed populations. We make this algorithm available as a standalone program called AlphaPeel.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.