abstract：:High-throughput sequencing data can be used to predict phenotypes from genotypes, and this corresponds to establishing a prognostic model. In extended pedigrees the relatedness of subjects provides additional information so that genetic values, fixed or random genetic components, and heritability can be estimated. At ...

journal_title：Genetic epidemiology

authors： Ziegler A,Bohossian N,Diego VP,Yao C

更新日期：2014-09-01 00:00:00

abstract：:With challenges in data harmonization and environmental heterogeneity across various data sources, meta-analysis of gene-environment interaction studies can often involve subtle statistical issues. In this paper, we study the effect of environmental covariate heterogeneity (within and between cohorts) on two approache...

journal_title：Genetic epidemiology

authors： Li S,Mukherjee B,Taylor JM,Rice KM,Wen X,Rice JD,Stringham HM,Boehnke M

更新日期：2014-07-01 00:00:00

abstract：:By analyzing more next-generation sequencing data, researchers have affirmed that rare genetic variants are widespread among populations and likely play an important role in complex phenotypes. Recently, a handful of statistical models have been developed to analyze rare variant (RV) association in different study des...

journal_title：Genetic epidemiology

authors： He L,Sillanpää MJ,Ripatti S,Pitkäniemi J

更新日期：2014-05-01 00:00:00

abstract：:Linkage analysis of complex traits has had limited success in identifying trait-influencing loci. Recently, coding variants have been implicated as the basis for some biomedical associations. We tested whether coding variants are the basis for linkage peaks of complex traits in 42 African-American (n = 596) and 90 His...

journal_title：Genetic epidemiology

authors： Hellwege JN,Palmer ND,Raffield LM,Ng MC,Hawkins GA,Long J,Lorenzo C,Norris JM,Ida Chen YD,Speliotes EK,Rotter JI,Langefeld CD,Wagenknecht LE,Bowden DW

更新日期：2014-05-01 00:00:00

abstract：:DNA methylation is an important epigenetic mechanism that has been linked to complex diseases and is of great interest to researchers as a potential link between genome, environment, and disease. As the scale of DNA methylation association studies approaches that of genome-wide association studies, issues such as popu...

journal_title：Genetic epidemiology

authors： Barfield RT,Almli LM,Kilaru V,Smith AK,Mercer KB,Duncan R,Klengel T,Mehta D,Binder EB,Epstein MP,Ressler KJ,Conneely KN

更新日期：2014-04-01 00:00:00

abstract：:We propose a new approach to detect gene × gene joint action in genome-wide association studies (GWASs) for case-control designs. This approach offers an exhaustive search for all two-way joint action (including, as a special case, single gene action) that is computationally feasible at the genome-wide level and has r...

journal_title：Genetic epidemiology

authors： Won S,Kwon MS,Mattheisen M,Park S,Park C,Kihara D,Cichon S,Ophoff R,Nöthen MM,Rietschel M,Baur M,Uitterlinden AG,Hofmann A,GROUP Investigators.,Lange C

更新日期：2014-01-01 00:00:00

abstract：:Advances in high throughput technology have enabled the generation of unprecedented amounts of genomic data (e.g., next-generation sequence data, transcriptomics, metabolomics, and proteomics), which promises to unravel the genetic architecture of complex traits. These discoveries may lead to novel therapeutic targets...

journal_title：Genetic epidemiology

authors： Lee SM,Karrison TG,Cox NJ,Im HK

更新日期：2013-12-01 00:00:00

abstract：:In spite of the success of genome-wide association studies in finding many common variants associated with disease, these variants seem to explain only a small proportion of the estimated heritability. Data collection has turned toward exome and whole genome sequencing, but it is well known that single marker methods ...

journal_title：Genetic epidemiology

authors： Ayers KL,Cordell HJ

更新日期：2013-09-01 00:00:00

abstract：:For most complex diseases, the fraction of heritability that can be explained by the variants discovered from genome-wide association studies is minor. Although the so-called "rare variants" (minor allele frequency [MAF] < 1%) have attracted increasing attention, they are unlikely to account for much of the "missing h...

journal_title：Genetic epidemiology

authors： Lin WY,Yi N,Lou XY,Zhi D,Zhang K,Gao G,Tiwari HK,Liu N

更新日期：2013-09-01 00:00:00

abstract：:Testing association between a genetic marker and multiple-dependent traits is a challenging task when both binary and quantitative traits are involved. The inverted regression model is a convenient method, in which the traits are treated as predictors although the genetic marker is an ordinal response. It is known tha...

journal_title：Genetic epidemiology

authors： Yan T,Li Q,Li Y,Li Z,Zheng G

更新日期：2013-09-01 00:00:00

abstract：:There has been extensive literature on modeling gene-gene interaction (GGI) and gene-environment interaction (GEI) in case-control studies with limited literature on statistical methods for GGI and GEI in longitudinal cohort studies. We borrow ideas from the classical two-way analysis of variance literature to address...

journal_title：Genetic epidemiology

authors： Ko YA,Saha-Chaudhuri P,Park SK,Vokonas PS,Mukherjee B

更新日期：2013-09-01 00:00:00

abstract：:Results of studies for the association of BRCA1 genotypes and haplotypes with sporadic breast cancer have been inconsistent. Therefore, a candidate single nucleotide polymorphism (SNP) approach was used in a breast cancer case-control study to explore genotypes and haplotypes that have the potential to affect protein ...

journal_title：Genetic epidemiology

authors： Ricks-Santi LJ,Nie J,Marian C,Ochs-Balcom HM,Trevisan M,Edge SB,Kanaan Y,Freudenheim JL,Shields PG

更新日期：2013-07-01 00:00:00

abstract：:Standard linear regression is commonly used for genetic association studies of quantitative traits. This approach may not be appropriate if the trait, on its original or transformed scales, does not follow a normal distribution. A rank-based nonparametric approach that does not rely on any distributional assumptions c...

journal_title：Genetic epidemiology

authors： Li Q,Li Z,Zheng G,Gao G,Yu K

更新日期：2013-05-01 00:00:00

abstract：:Genome-wide association studies (GWAS) have identified many single nucleotide polymorphisms (SNPs) associated with complex traits. However, the genetic heritability of most of these traits remains unexplained. To help guide future studies, we address the crucial question of whether future GWAS can detect new SNP assoc...

journal_title：Genetic epidemiology

authors： Lindquist KJ,Jorgenson E,Hoffmann TJ,Witte JS

更新日期：2013-05-01 00:00:00

abstract：:The potential importance of the joint action of genes, whether modeled with or without a statistical interaction term, has long been recognized. However, identifying such action has been a great challenge, especially when millions of genetic markers are involved. We propose a likelihood ratio-based Mann-Whitney test t...

journal_title：Genetic epidemiology

authors： Lu Q,Wei C,Ye C,Li M,Elston RC

更新日期：2012-09-01 00:00:00

abstract：:In genetic association studies, a single marker is often associated with multiple, correlated phenotypes (e.g., obesity and cardiovascular disease, or nicotine dependence and lung cancer). A pervasive question is then whether that marker exerts independent effects on all phenotypes. In this paper, we address this ques...

journal_title：Genetic epidemiology

authors： Berzuini C,Vansteelandt S,Foco L,Pastorino R,Bernardinelli L

更新日期：2012-09-01 00:00:00

abstract：:This paper presents a projection regression model (PRM) to assess the relationship between a multivariate phenotype and a set of covariates, such as a genetic marker, age, and gender. In the existing literature, a standard statistical approach to this problem is to fit a multivariate linear model to the multivariate p...

journal_title：Genetic epidemiology

authors： Lin JA,Zhu H,Knickmeyer R,Styner M,Gilmore J,Ibrahim JG

更新日期：2012-09-01 00:00:00

abstract：:For many clinical studies in cancer, germline DNA is prospectively collected for the purpose of discovering or validating single-nucleotide polymorphisms (SNPs) associated with clinical outcomes. The primary clinical endpoint for many of these studies are time-to-event outcomes such as time of death or disease progres...

journal_title：Genetic epidemiology

authors： Owzar K,Li Z,Cox N,Jung SH

更新日期：2012-09-01 00:00:00

abstract：:We construct data exploration tools for recognizing important covariate patterns associated with a phenotype, with particular focus on searching for association with gene-gene patterns. To this end, we propose a new variable selection procedure that employs latent selection weights and compare it to an alternative for...

journal_title：Genetic epidemiology

authors： Papathomas M,Molitor J,Hoggart C,Hastie D,Richardson S

更新日期：2012-09-01 00:00:00

abstract：:Although next-generation DNA sequencing technologies have made rare variant association studies feasible and affordable, the development of powerful statistical methods for rare variant association studies is still under way. Most of the existing methods for rare variant association studies compare the number of rare ...

journal_title：Genetic epidemiology

authors： Fang S,Sha Q,Zhang S

更新日期：2012-07-01 00:00:00

abstract：:Sequencing studies using whole-genome or exome scans are still more expensive than genome-wide association studies on a per-subject basis. As a result, only a subset of subjects from a larger study will be selected for sequencing. To perform an agnostic investigation of the entire genome, subjects may be selected that...

journal_title：Genetic epidemiology

authors： Edwards TL,Li C

更新日期：2012-07-01 00:00:00

abstract：:With new technologies, multiple types of genomic data are commonly collected on a single set of samples. However, standard analysis methods concentrate on a single data type at a time and ignore the relationships between genes, proteins, and biochemical reactions that give rise to complex phenotypes. In this paper, we...

journal_title：Genetic epidemiology

authors： Fridley BL,Lund S,Jenkins GD,Wang L

更新日期：2012-05-01 00:00:00

abstract：:Sub-Saharan Africa has been identified as the part of the world with the greatest human genetic diversity. This high level of diversity causes difficulties for genome-wide association (GWA) studies in African populations-for example, by reducing the accuracy of genotype imputation in African populations compared to no...

journal_title：Genetic epidemiology

authors： Huang L,Jakobsson M,Pemberton TJ,Ibrahim M,Nyambo T,Omar S,Pritchard JK,Tishkoff SA,Rosenberg NA

更新日期：2011-12-01 00:00:00

abstract：:Large-scale meta-analyses of genome-wide association scans (GWAS) have been successful in discovering common risk variants with modest and small effects. The detection of lower frequency signals will undoubtedly require concerted efforts of at least similar scale. We investigate the sample size-dictated power limits o...

journal_title：Genetic epidemiology

authors： Chapman K,Ferreira T,Morris A,Asimit J,Zeggini E

更新日期：2011-12-01 00:00:00

abstract：:In case-control genetic association studies, the robust procedure, Pearson's Chi-square test, is commonly used for testing association between disease status and genetic markers. However, this test does not take the possible trend of relative risks, which are due to genotype, into account. On the contrary, although Co...

journal_title：Genetic epidemiology

authors： Chen Z

更新日期：2011-11-01 00:00:00

abstract：:Methods to account for population structure (PS) in genome-wide association studies have been well developed in samples of unrelated individuals, but when a sample is composed of families, the task of finding and accounting for PS is not as straight forward. Family-based tests that condition on parental genotypes or t...

journal_title：Genetic epidemiology

authors： Peloso GM,Dupuis J,Lunetta KL

更新日期：2011-09-01 00:00:00

abstract：:The study of the genetic component of early-onset diseases requires investigation into parental genetic effects, particularly those mediated by the mother who can influence the offspring's risk of disease through the effects of her genes acting directly on the intrauterine milieu or indirectly through maternal-gene ch...

journal_title：Genetic epidemiology

authors： Bourgey M,Healy J,Saint-Onge P,Massé H,Sinnett D,Roy-Gagnon MH

更新日期：2011-09-01 00:00:00

abstract：:Association analysis has led to the identification of many genetic variants for complex diseases. While assessing the association between genes and a disease, other factors can play an important role. The consequence of not considering covariates (such as population stratification and environmental factors) is well-do...

journal_title：Genetic epidemiology

authors： Jiang Y,Zhang H

更新日期：2011-02-01 00:00:00

abstract：:As part of Genetic Analysis Workshop 17 (GAW17), our group considered the application of novel and standard approaches to the analysis of genotype-phenotype association in next-generation sequencing data. Our group identified a major issue in the analysis of the GAW17 next-generation sequencing data: type I error and ...

journal_title：Genetic epidemiology

authors： Tintle N,Aschard H,Hu I,Nock N,Wang H,Pugh E

更新日期：2011-01-01 00:00:00

abstract：:Genetic Analysis Workshop 17 (GAW17) focused on the transition from genome-wide association study designs and methods to the study designs and statistical genetic methods that will be required for the analysis of next-generation sequence data including both common and rare sequence variants. In the 166 contributions t...

journal_title：Genetic epidemiology

authors： Wilson AF,Ziegler A

更新日期：2011-01-01 00:00:00

abstract：:Penalized regression methods offer an attractive alternative to single marker testing in genetic association analysis. Penalized regression methods shrink down to zero the coefficient of markers that have little apparent effect on the trait of interest, resulting in a parsimonious subset of what we hope are true perti...

journal_title：Genetic epidemiology

authors： Ayers KL,Cordell HJ

更新日期：2010-12-01 00:00:00

abstract：:Meta-analyses of genetic association studies are usually performed using a single polymorphism at a time, even though in many cases the individual studies report results from partially overlapping sets of polymorphisms. We present here a multipoint (or multilocus) method for multivariate meta-analysis of published pop...

journal_title：Genetic epidemiology

authors： Bagos PG,Liakopoulos TD

更新日期：2010-11-01 00:00:00

abstract：:It is believed that interactions among genes (epistasis) may play an important role in susceptibility to common diseases (Moore and Williams [2002]. Ann Med 34:88-95; Ritchie et al. [2001]. Am J Hum Genet 69:138-147). To study the underlying genetic variants of diseases, genome-wide association studies (GWAS) that sim...

journal_title：Genetic epidemiology

authors： Jiang X,Barmada MM,Visweswaran S

更新日期：2010-09-01 00:00:00

abstract：:Family data are useful for estimating disease risk in carriers of specific genotypes of a given gene (penetrance). Penetrance is frequently estimated assuming that relatives' phenotypes are independent, given their genotypes for the gene of interest. This assumption is unrealistic when multiple shared risk factors con...

journal_title：Genetic epidemiology

authors： Gong G,Hannon N,Whittemore AS

更新日期：2010-05-01 00:00:00

abstract：:Haplotype sharing analysis is a well-established option for the investigation of the etiology of complex diseases. The statistical power of haplotype association methods depends strongly on how the information of unobserved haplotypes can be captured by multilocus genotypes. In this study we combine an entropy-based m...

journal_title：Genetic epidemiology

authors： Schulz A,Fischer C,Chang-Claude J,Beckmann L

更新日期：2010-05-01 00:00:00

abstract：:Genome-wide association (GWA) studies have proved extremely successful in identifying novel genetic loci contributing effects to complex human diseases. In doing so, they have highlighted the fact that many potential loci of modest effect remain undetected, partly due to the need for samples consisting of many thousan...

journal_title：Genetic epidemiology

authors： Zhuang JJ,Zondervan K,Nyberg F,Harbron C,Jawaid A,Cardon LR,Barratt BJ,Morris AP

更新日期：2010-05-01 00:00:00

abstract：:Case-only studies are often used to identify interactions between a genetic factor and an environmental factor under the assumption both factors are independent in the population. However, interpreting a statistical association between the genetic and the environmental factors among the cases, as evidence of a mechani...

journal_title：Genetic epidemiology

authors： VanderWeele TJ,Hernández-Díaz S,Hernán MA

更新日期：2010-05-01 00:00:00

abstract：:Investigators interested in whether a disease aggregates in families often collect case-control family data, which consist of disease status and covariate information for members of families selected via case or control probands. Here, we focus on the use of case-control family data to investigate the relative contrib...

journal_title：Genetic epidemiology

authors： Javaras KN,Hudson JI,Laird NM

更新日期：2010-04-01 00:00:00

abstract：:When testing for genetic effects, failure to account for a gene-environment interaction can mask the true association effects of a genetic marker with disease. Family-based association tests are popular because they are completely robust to population substructure and model misspecification. However, when testing for ...

journal_title：Genetic epidemiology

authors： Hoffmann TJ,Lange C,Vansteelandt S,Laird NM

更新日期：2009-12-01 00:00:00

abstract：:Gene-gene interaction is believed to play an important role in understanding complex traits. Multifactor dimensionality reduction (MDR) was proposed by Ritchie et al. [2001. Am J Hum Genet 69:138-147] to identify multiple loci that simultaneously affect disease susceptibility. Although the MDR method has been widely u...

journal_title：Genetic epidemiology

authors： Namkung J,Elston RC,Yang JM,Park T

更新日期：2009-11-01 00:00:00