Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Imputation for sequencing variants preselected to a customized low-density chip.

Scientific reports - 12 Jun 2020

Liu Aoxing, Lund Mogens Sandø, Boichard Didier, Mao Xiaowei, Karaman Emre, Fritz Sebastien, Aamand Gert Pedersen, Wang Yachun, Su Guosheng

Abstract excerpt

The sequencing variants preselected from association analyses and bioinformatics analyses could improve genomic prediction. In this study, the imputation of sequencing SNPs preselected from major dairy breeds in Denmark-Finland-Sweden (DFS) and France (FRA) was investigated for both contemporary animals and old bulls in Danish Jersey. For contemporary animals, a two-step imputation which first imputed to 54 K and...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Cattle
Share to Gene Frequency

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Oligonucleotide Array Sequence Analysis

Share to Polymorphism, Single Nucleotide

Source

Open in PubMed Open full text

Identifiers

PMID: 32533087
DOI: 10.1038/s41598-020-66523-7
PMCID: PMC7293337

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 6 Sept 2026. Manifest publication-graph-cohort-2026-09-06.1.

Source receipt: pubmed, retrieved 6 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Imputation for sequencing variants preselected to a customized low-density chip.PMID 32533087Read ↗

Novel methods for genotype imputation to whole-genome sequence and a simple linear model to predict imputation accuracy.Semantic proximity Read ↗

Imputation of genotypes from different single nucleotide polymorphism panels in dairy cattle.Semantic proximity Read ↗

Multi-breed genomic prediction using Bayes R with sequence data and dropping variants with a small effect.Semantic proximity Read ↗

Prediction of unobserved single nucleotide polymorphism genotypes of Jersey cattle using reference panels and population-based imputation algorithms.Semantic proximity Read ↗

Comparing strategies for selection of low-density SNPs for imputation-mediated genomic prediction in U. S. Holsteins.Semantic proximity Read ↗

Design of a low-density SNP chip for the main Australian sheep breeds and its effect on imputation and genomic prediction accuracy.Semantic proximity Read ↗

Using pre-selected variants from large-scale whole-genome sequence data for single-step genomic predictions in pigs.Semantic proximity Read ↗

Short communication: Imputation performances of 3 low-density marker panels in beef and dairy cattle.Semantic proximity Read ↗

Strategies and utility of imputed SNP genotypes for genomic analysis in dairy cattle.Semantic proximity Read ↗

Imputation accuracy from low- to medium-density SNP chips for US crossbred dairy cattle.Semantic proximity Read ↗

Imputation of canine genotype array data using 365 whole-genome sequences improves power of genome-wide association studiesSemantic proximity Read ↗

Consequences of splitting whole-genome sequencing effort over multiple breeds on imputation accuracy.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.