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

A framework for pathway knowledge driven prioritization in genome-wide association studies.

Genetic epidemiology - 1 Nov 2020

Biswas Shrayashi, Pal Soumen, Majumder Partha P, Bhattacharjee Samsiddhi

Abstract excerpt

Many variants with low frequencies or with low to modest effects likely remain unidentified in genome-wide association studies (GWAS) because of stringent genome-wide thresholds for detection. To improve the power of detection, variant prioritization based on their functional annotations and epigenetic landmarks has been used successfully. Here, we propose a novel method of prioritization of a GWAS by exploiting...

Read the complete abstract on PubMed

Topics

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

Share to Computer Simulation
Share to Databases, Genetic
Share to Diabetes Mellitus, Type 2

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Genome, Human

Share to Genome-Wide Association Study

Share to Models, Genetic

Share to Molecular Sequence Annotation

Share to Polymorphism, Single Nucleotide

Source

Open in PubMed Open full text

Identifiers

PMID: 32779262
DOI: 10.1002/gepi.22345
PMCID: PMC7116354

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 2 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

A framework for pathway knowledge driven prioritization in genome-wide association studies.PMID 32779262Read ↗

From genetic associations to genes: methods, applications, and challenges.Semantic proximity Read ↗

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

A Regression-based Framework for Scalable Pathway-guided Search in Genome-wide Association StudiesSemantic proximity Read ↗

GenoWAP: Post-GWAS Prioritization Through Integrated Analysis of Genomic Functional AnnotationSemantic proximity Read ↗

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

GenoWAP: GWAS signal prioritization through integrated analysis of genomic functional annotation.Semantic proximity Read ↗

Open Targets Genetics: An open approach to systematically prioritize causal variants and genes at all published human GWAS trait-associated lociSemantic proximity Read ↗

Simplifying causal gene identification in GWAS loci.Semantic proximity Read ↗

Simplifying causal gene identification in GWAS lociSemantic proximity Read ↗

Evaluation of Bayesian Linear Regression Models for Gene Set Prioritization in Complex DiseasesSemantic proximity Read ↗

Integrating functional data to prioritize causal variants in statistical fine-mapping studies.Semantic proximity Read ↗

Leveraging multiple gene networks to prioritize GWAS candidate genes via network representation learning.Semantic proximity Read ↗

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