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

Next generation modeling in GWAS: comparing different genetic architectures.

Human genetics - 1 Oct 2014

López de Maturana Evangelina, Ibáñez-Escriche Noelia, González-Recio Óscar, Marenne Gaëlle, Mehrban Hossein, Chanock Stephen J, Goddard Michael E, Malats Núria

Abstract excerpt

The continuous advancement in genotyping technology has not been accompanied by the application of innovative statistical methods, such as multi-marker methods (MMM), to unravel genetic associations with complex traits. Although the performance of MMM has been widely explored in a prediction cont...

Read the complete abstract on PubMed

Topics

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

Share to Bayes Theorem
Share to Computer Simulation
Share to Genes, Neoplasm

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Genotyping Techniques

Share to Hispanic or Latino

Share to Linkage Disequilibrium

Share to Quantitative Trait Loci

Share to Urinary Bladder Neoplasms

Source

Identifiers

PMID: 24934831
DOI: 10.1007/s00439-014-1461-1

Genes

MAF

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 4 Sept 2026. Prepared record publication-24934831-2026-09-04.2. Manifest publication-graph-cohort-2026-09-04.2.

Source receipt: PubMed via Helena Literature Corpus, retrieved 4 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Next generation modeling in GWAS: comparing different genetic architectures.PMID 24934831Read ↗

Revisiting genome-wide association studies from statistical modelling to machine learning.Semantic proximity Read ↗

Genetic Bases of Complex Traits: From Quantitative Trait Loci to Prediction.Semantic proximity Read ↗

Strategies for developing prediction models from genome-wide association studies.Semantic proximity Read ↗

Comparison of biometrical models for joint linkage association mapping.Semantic proximity Read ↗

Genome-wide association mapping including phenotypes from relatives without genotypes.Semantic proximity Read ↗

An efficient unified model for genome-wide association studies and genomic selection.Semantic proximity Read ↗

A Lasso multi-marker mixed model for association mapping with population structure correction.Semantic proximity Read ↗

Fine mapping and accurate prediction of complex traits using Bayesian Variable Selection models applied to biobank-size data.Semantic proximity Read ↗

Whole genome prediction of bladder cancer risk with the Bayesian LASSO.Semantic proximity Read ↗

Efficient weighting methods for genomic best linear-unbiased prediction (BLUP) adapted to the genetic architectures of quantitative traits.Semantic proximity Read ↗

Bayesian multiple logistic regression for case-control GWASSemantic proximity Read ↗

Evaluation of Bayesian Linear Regression Models as a Fine Mapping toolSemantic proximity Read ↗

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