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

Short communication: Genomic prediction using imputed whole-genome sequence variants in Brown Swiss Cattle.

Journal of dairy science - 1 Feb 2018

Frischknecht Mirjam, Meuwissen Theodorus H E, Bapst Beat, Seefried Franz R, Flury Christine, Garrick Dorian, Signer-Hasler Heidi, Stricker Christian, Bieber Anna, Fries Ruedi, Russ Ingolf, Sölkner Johann, Bagnato Alessandro, Gredler-Grandl Birgit

Abstract excerpt

The accuracy of genomic prediction determines response to selection. It has been hypothesized that accuracy of genomic breeding values can be increased by a higher density of variants. We used imputed whole-genome sequence data and various single nucleotide polymorphism (SNP) selection criteria to estimate genomic breeding values in Brown Swiss cattle. The extreme scenarios were 50K SNP chip data and whole-genome...

Read the complete abstract on PubMed

Topics

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

Share to Cattle
Share to Breeding

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Genome

Share to Genome-Wide Association Study

Share to Genomics

Share to Linkage Disequilibrium

Share to Oligonucleotide Array Sequence Analysis

Share to Polymorphism, Single Nucleotide

Source

Identifiers

PMID: 29153527
DOI: 10.3168/jds.2017-12890

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

Short communication: Genomic prediction using imputed whole-genome sequence variants in Brown Swiss Cattle.PMID 29153527Read ↗

Genomic prediction using preselected DNA variants from a GWAS with whole-genome sequence data in Holstein-Friesian cattle.Semantic proximity Read ↗

Highly accurate sequence imputation enables precise QTL mapping in Brown Swiss cattle.Semantic proximity Read ↗

Genomic prediction using imputed whole-genome sequence data in Holstein Friesian cattle.Semantic proximity Read ↗

Estimates of missing heritability for complex traits in Brown Swiss cattle.Semantic proximity Read ↗

Within- and across-breed genomic prediction using whole-genome sequence and single nucleotide polymorphism panels.Semantic proximity Read ↗

Genomic prediction based on selected variants from imputed whole-genome sequence data in Australian sheep populations.Semantic proximity Read ↗

Genomic prediction in French Charolais beef cattle using high-density single nucleotide polymorphism markers.Semantic proximity Read ↗

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

Opportunities and computational challenges in large-scale whole-genome sequencing data analysis.Semantic proximity Read ↗

Marker effect p-values for single-step SNP-BLUP genomic modelsSemantic proximity Read ↗

Utility of whole-genome sequence data for across-breed genomic prediction.Semantic proximity Read ↗

Assessment of Imputation from Low-Pass Sequencing to Predict Merit of Beef Steers.Semantic proximity Read ↗

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