A general framework for detecting disease associations with rare variants in sequencing studies.
about
Insights into blood lipids from rare variant discoveryRare-variant association analysis: study designs and statistical testsExome sequencing and complex disease: practical aspects of rare variant association studiesRationale, design and baseline results of the Guangxi manganese-exposed workers healthy cohort (GXMEWHC) studyThe Genetic Landscape of Renal Complications in Type 1 Diabetes.Introduction to deep sequencing and its application to drug addiction research with a focus on rare variants.Loss-of-function mutations in APOC3, triglycerides, and coronary diseaseA unified method for detecting secondary trait associations with rare variants: application to sequence data.Weighted pedigree-based statistics for testing the association of rare variantsTesting for association with multiple traits in generalized estimation equations, with application to neuroimaging data.Family-based association tests for sequence data, and comparisons with population-based association tests.Multiple genetic variant association testing by collapsing and kernel methods with pedigree or population structured dataTesting for rare variant associations in the presence of missing data.Adjusting for population stratification in a fine scale with principal components and sequencing dataRare-variant extensions of the transmission disequilibrium test: application to autism exome sequence data.A novel test for testing the optimally weighted combination of rare and common variants based on data of parents and affected children.A generalized genetic random field method for the genetic association analysis of sequencing data.A power set-based statistical selection procedure to locate susceptible rare variants associated with complex traits with sequencing data.Variant association tools for quality control and analysis of large-scale sequence and genotyping array dataTesting genetic association with rare and common variants in family data.Longitudinal data analysis for genetic studies in the whole-genome sequencing era.Adjusting family relatedness in data-driven burden test of rare variantsPerformance of statistical methods on CHARGE targeted sequencing dataReview of current methods, applications, and data management for the bioinformatics analysis of whole exome sequencing.A weighted U-statistic for genetic association analyses of sequencing data.Rare variant analysis of blood pressure phenotypes in the Genetic Analysis Workshop 18 whole genome sequencing data using sequence kernel association test.Association analysis of whole genome sequencing data accounting for longitudinal and family designs.Evaluation of gene-based association tests for analyzing rare variants using Genetic Analysis Workshop 18 data.Integrative analysis of sequencing and array genotype data for discovering disease associations with rare mutations.Analysis of Sequence Data Under Multivariate Trait-Dependent SamplingDetecting rare variants for quantitative traits using nuclear families.A powerful and efficient set test for genetic markers that handles confoundersGene-set association tests for next-generation sequencing dataThe Rare-Variant Generalized Disequilibrium Test for Association Analysis of Nuclear and Extended Pedigrees with Application to Alzheimer Disease WGS Data.Bounce Back Now! Protocol of a population-based randomized controlled trial to examine the efficacy of a Web-based intervention with disaster-affected familiesA powerful association test of multiple genetic variants using a random-effects model.The impact of rare and low-frequency genetic variants in common diseaseThe genetic basis of ankylosing spondylitis: new insights into disease pathogenesisDetecting association of rare and common variants based on cross-validation prediction error.On the association analysis of genome-sequencing data: A spatial clustering approach for partitioning the entire genome into nonoverlapping windows.
P2860
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P2860
A general framework for detecting disease associations with rare variants in sequencing studies.
description
2011 nî lūn-bûn
@nan
2011 թուականի Սեպտեմբերին հրատարակուած գիտական յօդուած
@hyw
2011 թվականի սեպտեմբերին հրատարակված գիտական հոդված
@hy
2011年の論文
@ja
2011年論文
@yue
2011年論文
@zh-hant
2011年論文
@zh-hk
2011年論文
@zh-mo
2011年論文
@zh-tw
2011年论文
@wuu
name
A general framework for detect ...... ariants in sequencing studies.
@ast
A general framework for detect ...... ariants in sequencing studies.
@en
type
label
A general framework for detect ...... ariants in sequencing studies.
@ast
A general framework for detect ...... ariants in sequencing studies.
@en
prefLabel
A general framework for detect ...... ariants in sequencing studies.
@ast
A general framework for detect ...... ariants in sequencing studies.
@en
P2860
P1476
A general framework for detect ...... ariants in sequencing studies.
@en
P2093
Dan-Yu Lin
Zheng-Zheng Tang
P2860
P304
P356
10.1016/J.AJHG.2011.07.015
P407
P577
2011-09-01T00:00:00Z