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

Inexpensive Computation of the Inverse of the Genomic Relationship Matrix in Populations with Small Effective Population Size.

Genetics - 1 Feb 2016

Misztal Ignacy

Abstract excerpt

Many computations with SNP data including genomic evaluation, parameter estimation, and genome-wide association studies use an inverse of the genomic relationship matrix. The cost of a regular inversion is cubic and is prohibitively expensive for large matrices. Recent studies in cattle demonstrated that the inverse can be computed in almost linear time by recursion on any subset of ∼10,000 individuals. The...

Read the complete abstract on PubMed

Topics

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

Share to Algorithms
Share to Breeding
Share to Cattle

Methodology Data sources Editorial policy Privacy Delete account & data About Contact Helena Bioinformatics

Share to Genetics, Population

Share to Genome

Share to Genomics

Share to Population Density

Share to Selection, Genetic

Source

Open in PubMed Open full text

Identifiers

PMID: 26584903
DOI: 10.1534/genetics.115.182089
PMCID: PMC4788224

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence. Graph snapshot: 2026-09-29.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Inexpensive Computation of the Inverse of the Genomic Relationship Matrix in Populations with Small Effective Population Size.PMID 26584903Read ↗

The Dimensionality of Genomic Information and Its Effect on Genomic Prediction.Semantic proximity Read ↗

Using recursion to compute the inverse of the genomic relationship matrix.Semantic proximity Read ↗

Dimensionality of genomic information and performance of the Algorithm for Proven and Young for different livestock species.Semantic proximity Read ↗

On the equivalence between marker effect models and breeding value models and direct genomic values with the Algorithm for Proven and Young.Semantic proximity Read ↗

Large-scale genomic prediction using singular value decomposition of the genotype matrix.Semantic proximity Read ↗

Solving efficiently large single-step genomic best linear unbiased prediction models.Semantic proximity Read ↗

A recursive algorithm for decomposition and creation of the inverse of the genomic relationship matrix.Semantic proximity Read ↗

Hot topic: Use of genomic recursions in single-step genomic best linear unbiased predictor (BLUP) with a large number of genotypes.Semantic proximity Read ↗

A comprehensive study on size and definition of the core group in the proven and young algorithm for single-step GBLUP.Semantic proximity Read ↗

Marker effect p-values for single-step GWAS with the algorithm for proven and young in large genotyped populations.Semantic proximity Read ↗

Optimisation of the core subset for the APY approximation of genomic relationships.Semantic proximity Read ↗

Sparse single-step genomic BLUP in crossbreeding schemes.Semantic proximity Read ↗

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