Article

Benchmarker: an unbiased, association-data-driven strategy to evaluate gene prioritization algorithms

2018-12-17

Abstract excerpt

Genome-wide association studies (GWAS) are valuable for understanding human biology, but associated loci typically contain multiple associated variants and genes. Thus, algorithms that prioritize likely causal genes and variants for a given phenotype can provide biological interpretations of association data. However, a critical, currently missing capability is to objectively compare performance of such algorithms...

Topics

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

Identifiers and source

Literature Corpus work: 5b2515b0-bcb5-59ac-9709-264eadafa471
DOI: 10.1101/497602

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Benchmarker: an unbiased, association-data-driven strategy to evaluate gene prioritization algorithmsDOI 10.1101/497602Read

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

Simplifying causal gene identification in GWAS lociSemantic proximity Read

Simplifying causal gene identification in GWAS loci.Semantic proximity Read

Settling the score: variant prioritization and Mendelian disease.Semantic proximity Read

Evaluation of phenotype-driven gene prioritization methods for Mendelian diseases.Semantic proximity Read

Bayesian Effect Size Ranking to Prioritise Genetic Risk Variants in Common Diseases for Follow-Up Studies.Semantic proximity Read

Benchmarking genome-wide association study causal gene prioritization for drug discoverySemantic proximity Read

Revisiting benchmark study for response to methodological critiques of 'Evaluation of phenotype-driven gene prioritization methods for Mendelian diseases'.Semantic proximity Read

Chapter 15: disease gene prioritization.Semantic proximity Read

SNP prioritization using a Bayesian probability of association.Semantic proximity Read

Leveraging polygenic enrichments of gene features to predict genes underlying complex traits and diseases.Semantic proximity Read

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