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

Association studies for next-generation sequencing.

Genome research - 1 Jul 2011

Luo Li, Boerwinkle Eric, Xiong Momiao

Abstract excerpt

Genome-wide association studies (GWAS) have become the primary approach for identifying genes with common variants influencing complex diseases. Despite considerable progress, the common variations identified by GWAS account for only a small fraction of disease heritability and are unlikely to explain the majority of phenotypic variations of common diseases. A potential source of the missing heritability is the...

Read the complete abstract on PubMed

Topics

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

Share to Models, Biological
Share to Models, Statistical
Share to Multivariate Analysis

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Angiopoietins

Share to Computational Biology

Share to Computer Simulation

Share to Databases, Genetic

Share to Genome, Human

Source

Open in PubMed Open full text

Identifiers

PMID: 21521787
DOI: 10.1101/gr.115998.110
PMCID: PMC3129252

Genes

ANGPTL4

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

Association studies for next-generation sequencing.PMID 21521787Read ↗

A novel genome-information content-based statistic for genome-wide association analysis designed for next-generation sequencing data.Semantic proximity Read ↗

Family-based association studies for next-generation sequencing.Semantic proximity Read ↗

Smoothed functional principal component analysis for testing association of the entire allelic spectrum of genetic variation.Semantic proximity Read ↗

A fast and noise-resilient approach to detect rare-variant associations with deep sequencing data for complex disorders.Semantic proximity Read ↗

Quality control issues and the identification of rare functional variants with next-generation sequencing data.Semantic proximity Read ↗

Methods for collapsing multiple rare variants in whole-genome sequence data.Semantic proximity Read ↗

Using genetic prediction from known complex disease Loci to guide the design of next-generation sequencing experiments.Semantic proximity Read ↗

A weighted U-statistic for genetic association analyses of sequencing data.Semantic proximity Read ↗

Calculating the statistical significance of rare variants causal for Mendelian and complex disordersSemantic proximity Read ↗

Pathway analysis with next-generation sequencing data.Semantic proximity Read ↗

RAPIDSNPs: A new computational pipeline for rapidly identifying key genetic variants reveals previously unidentified SNPs that are significantly associated with individual platelet responses.Semantic proximity Read ↗

Rare Variants Association Analysis in Large-Scale Sequencing Studies at the Single Locus Level.Semantic proximity Read ↗

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