Article

GMIP-PLSR: A Nextflow Pipeline for GWAS and Multi-Omics Integration in Gene Prioritization Using PLSR

2026-04-09

Abstract excerpt

Genome-wide association studies (GWAS) have significantly advanced our understanding of complex traits and diseases, but their interpretive power remains limited due to challenges in identifying causal genes and pathways. Integrating GWAS with multi-omics data—such as gene expression, protein-protein interactions, and gene-pathway networks have the potential to enhance biological insights and improve gene prioriti...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 3582797f-8390-51da-8239-d127f8d31d68
DOI: 10.64898/2026.04.06.716845

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

GMIP-PLSR: A Nextflow Pipeline for GWAS and Multi-Omics Integration in Gene Prioritization Using PLSRDOI 10.64898/2026.04.06.716845Read

Prioritization of therapeutic targets for dyslipidemia using integrative multi-omics and multi-trait analysis.Semantic proximity Read

Multi-Omics Integration Improves Polygenic Risk Prediction for Lipid Traits: A Multi-Ancestry Study in UK Biobank.Semantic proximity Read

Performing post-genome-wide association study analysis: overview, challenges and recommendationsSemantic proximity Read

multi-GPA-Tree: Statistical approach for pleiotropy informed and functional annotation tree guided prioritization of GWAS results.Semantic proximity Read

HAPPI GWAS: Holistic Analysis with Pre- and Post-Integration GWAS.Semantic proximity Read

PGA: post-GWAS analysis for disease gene identification.Semantic proximity Read

A methodology for gene level omics-WAS integration identifies genes influencing traits associated with cardiovascular risks: the Long Life Family Study.Semantic proximity Read

Simplifying Systems Genetics with QTLretrievR: An R Package for Molecular QTL IdentificationSemantic proximity Read

Evaluation of Bayesian Linear Regression models for gene set prioritization in complex diseases.Semantic proximity Read

Leveraging polygenic enrichments of gene features to predict genes underlying complex traits and diseasesSemantic proximity Read

An open approach to systematically prioritize causal variants and genes at all published human GWAS trait-associated loci.Semantic proximity Read

Analyzing associations and higher-order effects in multi-omics data with double machine learningSemantic proximity Read