Joint genotype ‐ and ancestry‐based genome‐wide association studies in admixed populations
ABSTRACT
In genome‐wide association studies (GWAS) genetic loci that influence complex traits are localized by inspecting associations between genotypes of genetic markers and the values of the trait of interest. On the other hand, admixture mapping, which is performed in case of populations consisting of a recent mix of two ancestral groups, relies on the ancestry information at each locus (locus‐specific ancestry). Recently it has been proposed to jointly model genotype and locus‐specific ancestry within the framework of single marker tests. Here, we extend this approach for population‐based GWAS in the direction...
Source: Genetic Epidemiology - June 28, 2017 Category: Epidemiology Authors: Piotr Szulc, Malgorzata Bogdan, Florian Frommlet, Hua Tang Tags: RESEARCH ARTICLE Source Type: research
Integrative eQTL analysis of tumor and host omics data in individuals with bladder cancer
ABSTRACT
Integrative analyses of several omics data are emerging. The data are usually generated from the same source material (i.e., tumor sample) representing one level of regulation. However, integrating different regulatory levels (i.e., blood) with those from tumor may also reveal important knowledge about the human genetic architecture. To model this multilevel structure, an integrative‐expression quantitative trait loci (eQTL) analysis applying two‐stage regression (2SR) was proposed. This approach first regressed tumor gene expression levels with tumor markers and the adjusted residuals from the previous model ...
Source: Genetic Epidemiology - June 23, 2017 Category: Epidemiology Authors: Silvia Pineda, Kristel Steen, N úria Malats Tags: BRIEF REPORT Source Type: research
A genetic stochastic process model for genome ‐wide joint analysis of biomarker dynamics and disease susceptibility with longitudinal data
In conclusion, the proposed GSPM provides a promising and useful tool in GWAS of longitudinal data for interrogating pleiotropic and interaction effects to gain more insights into the relationship between genes, quantitative biomarkers, and risks of complex diseases. (Source: Genetic Epidemiology)
Source: Genetic Epidemiology - June 21, 2017 Category: Epidemiology Authors: Liang He, Ilya Zhbannikov, Konstantin G. Arbeev, Anatoliy I. Yashin, Alexander M. Kulminski Tags: RESEARCH ARTICLE Source Type: research
Detecting genetic association through shortest paths in a bidirected graph
ABSTRACT
Genome‐wide association studies (GWASs) commonly use marginal association tests for each single‐nucleotide polymorphism (SNP). Because these tests treat SNPs as independent, their power will be suboptimal for detecting SNPs hidden by linkage disequilibrium (LD). One way to improve power is to use a multiple regression model. However, the large number of SNPs preclude simultaneous fitting with multiple regression, and subset regression is infeasible because of an exorbitant number of candidate subsets. We therefore propose a new method for detecting hidden SNPs having significant yet weak marginal association i...
Source: Genetic Epidemiology - June 19, 2017 Category: Epidemiology Authors: Masao Ueki, Yoshinori Kawasaki, Gen Tamiya Tags: RESEARCH ARTICLE Source Type: research
Issue Information
(Source: Genetic Epidemiology)
Source: Genetic Epidemiology - June 16, 2017 Category: Epidemiology Tags: Issue Information Source Type: research
Region ‐based association tests for sequencing data on survival traits
ABSTRACT
Family‐based designs enriched with affected subjects and disease associated variants can increase statistical power for identifying functional rare variants. However, few rare variant analysis approaches are available for time‐to‐event traits in family designs and none of them applicable to the X chromosome. We developed novel pedigree‐based burden and kernel association tests for time‐to‐event outcomes with right censoring for pedigree data, referred to FamRATS (family‐based rare variant association tests for survival traits). Cox proportional hazard models were employed to relate a time‐to‐even...
Source: Genetic Epidemiology - June 4, 2017 Category: Epidemiology Authors: Li ‐Chu Chien, Donald W. Bowden, Yen‐Feng Chiu Tags: RESEARCH ARTICLE Source Type: research
Inferring gene regulatory relationships with a high ‐dimensional robust approach
In this study, we develop a high‐dimensional robust regression approach to infer the regulatory relationships between GEs and CNAs. A high‐dimensional regression model is used to accommodate the effects of both cis‐acting and trans‐acting CNAs. A density power divergence loss function is used to accommodate long‐tailed GE distributions and contamination. Penalization is adopted for regularized estimation and selection of relevant CNAs. The proposed approach is effectively realized using a coordinate descent algorithm. Simulation shows that it has competitive performance compared to the nonrobust benchmark and the...
Source: Genetic Epidemiology - May 2, 2017 Category: Epidemiology Authors: Yangguang Zang, Qing Zhao, Qingzhao Zhang, Yang Li, Sanguo Zhang, Shuangge Ma Tags: RESEARCH ARTICLE Source Type: research
Integrative gene set enrichment analysis utilizing isoform ‐specific expression
ABSTRACT
Gene set enrichment analysis (GSEA) aims at identifying essential pathways, or more generally, sets of biologically related genes that are involved in complex human diseases. In the past, many studies have shown that GSEA is a very useful bioinformatics tool that plays critical roles in the innovation of disease prevention and intervention strategies. Despite its tremendous success, it is striking that conclusions of GSEA drawn from isolated studies are often sparse, and different studies may lead to inconsistent and sometimes contradictory results. Further, in the wake of next generation sequencing technologies, ...
Source: Genetic Epidemiology - May 1, 2017 Category: Epidemiology Authors: Lie Li, Xinlei Wang, Guanghua Xiao, Adi Gazdar Tags: RESEARCH ARTICLE Source Type: research
PhredEM: a phred ‐score‐informed genotype‐calling approach for next‐generation sequencing studies
ABSTRACT
A fundamental challenge in analyzing next‐generation sequencing (NGS) data is to determine an individual's genotype accurately, as the accuracy of the inferred genotype is essential to downstream analyses. Correctly estimating the base‐calling error rate is critical to accurate genotype calls. Phred scores that accompany each call can be used to decide which calls are reliable. Some genotype callers, such as GATK and SAMtools, directly calculate the base‐calling error rates from phred scores or recalibrated base quality scores. Others, such as SeqEM, estimate error rates from the read data without using any ...
Source: Genetic Epidemiology - May 1, 2017 Category: Epidemiology Authors: Peizhou Liao, Glen A. Satten, Yi ‐Juan Hu Tags: RESEARCH ARTICLE Source Type: research
Polygenic scores via penalized regression on summary statistics
ABSTRACT
Polygenic scores (PGS) summarize the genetic contribution of a person's genotype to a disease or phenotype. They can be used to group participants into different risk categories for diseases, and are also used as covariates in epidemiological analyses. A number of possible ways of calculating PGS have been proposed, and recently there is much interest in methods that incorporate information available in published summary statistics. As there is no inherent information on linkage disequilibrium (LD) in summary statistics, a pertinent question is how we can use LD information available elsewhere to supplement such a...
Source: Genetic Epidemiology - May 1, 2017 Category: Epidemiology Authors: Timothy Shin Heng Mak, Robert Milan Porsch, Shing Wan Choi, Xueya Zhou, Pak Chung Sham Tags: RESEARCH ARTICLE Source Type: research
Conditional analysis of multiple quantitative traits based on marginal GWAS summary statistics
ABSTRACT
There has been an increasing interest in joint association testing of multiple traits for possible pleiotropic effects. However, even in the presence of pleiotropy, most of the existing methods cannot distinguish direct and indirect effects of a genetic variant, say single‐nucleotide polymorphism (SNP), on multiple traits, and a conditional analysis of a trait adjusting for other traits is perhaps the simplest and most common approach to addressing this question. However, without individual‐level genotypic and phenotypic data but with only genome‐wide association study (GWAS) summary statistics, as typical w...
Source: Genetic Epidemiology - May 1, 2017 Category: Epidemiology Authors: Yangqing Deng, Wei Pan Tags: RESEARCH ARTICLE Source Type: research
Leveraging cell type specific regulatory regions to detect SNPs associated with tissue factor pathway inhibitor plasma levels
ABSTRACT
Tissue factor pathway inhibitor (TFPI) regulates the formation of intravascular blood clots, which manifest clinically as ischemic heart disease, ischemic stroke, and venous thromboembolism (VTE). TFPI plasma levels are heritable, but the genetics underlying TFPI plasma level variability are poorly understood. Herein we report the first genome‐wide association scan (GWAS) of TFPI plasma levels, conducted in 251 individuals from five extended French‐Canadian Families ascertained on VTE. To improve discovery, we also applied a hypothesis‐driven (HD) GWAS approach that prioritized single nucleotide polymorphism...
Source: Genetic Epidemiology - April 19, 2017 Category: Epidemiology Authors: Jessica Dennis, Alejandra Medina ‐Rivera, Vinh Truong, Lina Antounians, Nora Zwingerman, Giovana Carrasco, Lisa Strug, Phil Wells, David‐Alexandre Trégouët, Pierre‐Emmanuel Morange, Michael D. Wilson, France Gagnon Tags: RESEARCH ARTICLE Source Type: research
Issue Information
(Source: Genetic Epidemiology)
Source: Genetic Epidemiology - April 18, 2017 Category: Epidemiology Tags: Issue Information Source Type: research
BinomiRare: A robust test of the association of a rare variant with a disease for pooled analysis and meta ‐analysis, with application to the HCHS/SOL
ABSTRACT
Most regression‐based tests of the association between a low‐count variant and a binary outcome do not protect type 1 error, especially when tests are rejected based on a very low significance threshold. Noted exception is the Firth test. However, it was recently shown that in meta‐analyzing multiple studies all asymptotic, regression‐based tests, including the Firth, may not control type 1 error in some settings, and the Firth test may suffer a substantial loss of power. The problem is exacerbated when the case‐control proportions differ between studies. I propose the BinomiRare exact test that circumve...
Source: Genetic Epidemiology - April 10, 2017 Category: Epidemiology Authors: Tamar Sofer Tags: RESEARCH ARTICLE Source Type: research
A novel association test for multiple secondary phenotypes from a case ‐control GWAS
ABSTRACT
In the past decade, many genome‐wide association studies (GWASs) have been conducted to explore association of single nucleotide polymorphisms (SNPs) with complex diseases using a case‐control design. These GWASs not only collect information on the disease status (primary phenotype, D) and the SNPs (genotypes, X), but also collect extensive data on several risk factors and traits. Recent literature and grant proposals point toward a trend in reusing existing large case‐control data for exploring genetic associations of some additional traits (secondary phenotypes, Y) collected during the study. These seconda...
Source: Genetic Epidemiology - April 10, 2017 Category: Epidemiology Authors: Debashree Ray, Saonli Basu Tags: RESEARCH ARTICLE Source Type: research
