Article

Incorporating prior information into signal-detection analyses across biologically informed gene-sets

2019-01-23

Abstract excerpt

<h4>ABSTRACT</h4> Signal detection analyses are used to assess whether there is any evidence of signal within a large collection of hypotheses. For example, we may wish to assess whether there is any evidence of association with disease among a set of biologically related genes. Such an analysis typically treats all genes within the sets similarly, even though there is substantial information concerning the likel...

Topics

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

Identifiers and source

Literature Corpus work: 7b1aadbe-1dcb-54ef-b57e-9a9c17830a22
DOI: 10.1101/525840

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Incorporating prior information into signal-detection analyses across biologically informed gene-setsDOI 10.1101/525840Read

Incorporating external information to improve sparse signal detection in rare-variant gene-set-based analyses.Semantic proximity Read

Focused goodness of fit tests for gene set analyses.Semantic proximity Read

Evaluating de novo locus-disease discoveries in GWAS using the signal-to-noise ratio.Semantic proximity Read

Bayes factors for genome-wide association studies: comparison with P-values.Semantic proximity Read

Priors, population sizes, and power in genome-wide hypothesis testsSemantic proximity Read

Bayesian estimation of gene constraint from an evolutionary model with gene featuresSemantic proximity Read

Finding disease variants in Mendelian disorders by using sequence data: methods and applications.Semantic proximity Read

An Optimal Bahadur-Efficient Method in Detection of Sparse Signals with Applications to Pathway Analysis in Sequencing Association Studies.Semantic proximity Read

Incorporating prior knowledge to increase the power of genome-wide association studies.Semantic proximity Read

Counterfactual inference for single-cell gene expression analysisSemantic proximity Read

Improving power of genome-wide association studies with weighted false discovery rate control and prioritized subset analysis.Semantic proximity Read

Boosting signals in gene-based association studies via efficient SNP selection.Semantic proximity Read