A computationally feasible multi-trait single-step genomic prediction model with trait-specific marker weights

We investigated a single-step SNPBLUP model that can be used to accommodate trait-specific marker weights. The marker-weighted single-step model improved prediction accuracy. The approach can be used for large genomic data evaluations using precomputed marker weights.

Authors

Institutions

Publication Details

Journal
Genetics Selection Evolution
Published
2024-08-16
DOI
https://doi.org/10.1186/s12711-024-00926-2
Citations
4
Primary Topic
Genetic and phenotypic traits in livestock
Type
article
Field-Weighted Citation Impact
2.20

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A computationally feasible multi-trait single-step genomic prediction model with trait-specific marker weights

Ismo Strandén, Janez Jenko
4 citations
Genetics Selection Evolution
Genetic and phenotypic traits in livestock
2.20
article

A computationally feasible multi-trait single-step genomic prediction model with trait-specific marker weights

Ismo Strandén, Janez Jenko
article en
4 citations

Abstract

We investigated a single-step SNPBLUP model that can be used to accommodate trait-specific marker weights. The marker-weighted single-step model improved prediction accuracy. The approach can be used for large genomic data evaluations using precomputed marker weights.

Genetics Selection EvolutionVol. 56(1)
Natural Resources Institute Finland (FI), Geno (Norway) (NO)
Norges Forskningsråd
Openalex Percentile: Top 12%
Genetic and phenotypic traits in livestock
2.20
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.