Using principal components of genetic variation for robust and powerful detection of gene-gene interactions in case-control and case-only studies.
about
Gene-environment interactions in genome-wide association studies: current approaches and new directionsLikelihood ratio test for detecting gene (G)-environment (E) interactions under an additive risk model exploiting G-E independence for case-control data.A kernel of truth: statistical advances in polygenic variance component models for complex human pedigrees.Genome-wide association of familial late-onset Alzheimer's disease replicates BIN1 and CLU and nominates CUGBP2 in interaction with APOEImproved statistics for genome-wide interaction analysis.Sample size requirements to detect gene-environment interactions in genome-wide association studies.Large-scale exploration of gene-gene interactions in prostate cancer using a multistage genome-wide association study.Family-based gene-by-environment interaction studies: revelations and remediesRare and common variants: twenty arguments.Application of a novel score test for genetic association incorporating gene-gene interaction suggests functionality for prostate cancer susceptibility regions.A sibling-augmented case-only approach for assessing multiplicative gene-environment interactions.Invited commentary: GE-Whiz! Ratcheting gene-environment studies up to the whole genome and the whole exposomeGene-environment interactions in genome-wide association studies: a comparative study of tests applied to empirical studies of type 2 diabetesUsing shared genetic controls in studies of gene-environment interactionsChallenges and opportunities in genome-wide environmental interaction (GWEI) studiesEnvironmental confounding in gene-environment interaction studiesA Novel Test for Detecting SNP-SNP Interactions in Case-Only Trio StudiesA kernel regression approach to gene-gene interaction detection for case-control studies.Variation in predictive ability of common genetic variants by established strata: the example of breast cancer and age.Personalized medicine: Genetic risk prediction of drug response.Efficient two-step testing of gene-gene interactions in genome-wide association studies.The logistic regression model for gene-environment interactions using both case-parent trios and unrelated case-controls.A novel method to detect gene-gene interactions in structured populations: MDR-SP.Stratification in population-based studies: hidden pitfalls.
P2860
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P2860
Using principal components of genetic variation for robust and powerful detection of gene-gene interactions in case-control and case-only studies.
description
2010 nî lūn-bûn
@nan
2010 թուականի Մարտին հրատարակուած գիտական յօդուած
@hyw
2010 թվականի մարտին հրատարակված գիտական հոդված
@hy
2010年の論文
@ja
2010年論文
@yue
2010年論文
@zh-hant
2010年論文
@zh-hk
2010年論文
@zh-mo
2010年論文
@zh-tw
2010年论文
@wuu
name
Using principal components of ...... control and case-only studies.
@ast
Using principal components of ...... control and case-only studies.
@en
type
label
Using principal components of ...... control and case-only studies.
@ast
Using principal components of ...... control and case-only studies.
@en
prefLabel
Using principal components of ...... control and case-only studies.
@ast
Using principal components of ...... control and case-only studies.
@en
P2093
P2860
P50
P1476
Using principal components of ...... control and case-only studies.
@en
P2093
Julia Ciampa
Samsiddhi Bhattacharjee
P2860
P304
P356
10.1016/J.AJHG.2010.01.026
P407
P577
2010-03-04T00:00:00Z