Article

Predicting causal variants affecting expression using whole genome sequence and RNA-seq from multiple human tissues

2016-11-21

Abstract excerpt

Genetic association mapping produces statistical links between phenotypes and genomic regions, but identifying the causal variants themselves remains difficult. Complete knowledge of all genetic variants, as provided by whole genome sequence (WGS), will help, but is currently financially prohibitive for well powered GWAS studies. To explore the advantages of WGS in a well powered setting, we performed eQTL mapping...

Topics

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

Identifiers and source

Literature Corpus work: ef362bfd-93eb-5f10-8935-531f25d38f49
DOI: 10.1101/088872

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Predicting causal variants affecting expression using whole genome sequence and RNA-seq from multiple human tissuesDOI 10.1101/088872Read

Predicting causal variants affecting expression by using whole-genome sequencing and RNA-seq from multiple human tissues.Semantic proximity Read

Efficient and accurate causal inference with hidden con-founders from genome-transcriptome variation dataSemantic proximity Read

Adjusting for genetic confounders in transcriptome-wide association studies improves discovery of risk genes of complex traits.Semantic proximity Read

Efficient and accurate causal inference with hidden confounders from genome-transcriptome variation data.Semantic proximity Read

The impact of structural variation on human gene expressionSemantic proximity Read

Transcriptome-wide association studies: opportunities and challengesSemantic proximity Read

Determining causality and consequence of expression quantitative trait loci.Semantic proximity Read

Leveraging allele-specific expression to refine fine-mapping for eQTL studiesSemantic proximity Read

Probabilistic fine-mapping of transcriptome-wide association studiesSemantic proximity Read

Leveraging supervised learning for functionally-informed fine-mapping of cis-eQTLs identifies an additional 20,913 putative causal eQTLsSemantic proximity Read

A Unifying Statistical Framework to Discover Disease Genes from GWASSemantic proximity Read

reg-eQTL: Integrating transcription factor effects to unveil regulatory variants.Semantic proximity Read