Genetic Analysis Workshop 18: Human sequence data in extended pedigrees
Proceedings
Edited by H Bickeböller, JN Bailey, J Beyene, RM Cantor, HJ Cordell, RC Culverhouse, CD Engelman, DW Fardo, S Ghosh, IR König, J Lorenzo Bermejo, PE Melton, SA Santorico, GA Satten, L Sun, NL Tintle, A Ziegler, JW MacCluer and L Almasy
Publication charges for this supplement were funded by the Texas Biomedical Research Institute. Articles have undergone the journal's standard review process for supplements. AZ received intramural funding from the University of Lübeck, Germany. The remaining Supplement Editors declare that they have no competing interests.
Genetic Analysis Workshop 18 provided a platform for developing and evaluating statistical methods to analyze whole-genome sequence data from a pedigree-based sample. In this article we present an overview of ...
Authors: Heike Bickeböller, Julia N Bailey, Joseph Beyene, Rita M Cantor, Heather J Cordell, Robert C Culverhouse, Corinne D Engelman, David W Fardo, Saurabh Ghosh, Inke R König, Justo Lorenzo Bermejo, Phillip E Melton, Stephanie A Santorico, Glen A Satten, Lei Sun, Nathan L Tintle…
Genetic Analysis Workshop 18 (GAW18) focused on identification of genes and functional variants that influence complex phenotypes in human sequence data. Data for the workshop were donated by the T2D-GENES Con...
Authors: Laura Almasy, Thomas D Dyer, Juan M Peralta, Goo Jun, Andrew R Wood, Christian Fuchsberger, Marcio A Almeida, Jack W Kent Jr, Sharon Fowler, Tom W Blackwell, Sobha Puppala, Satish Kumar, Joanne E Curran, Donna Lehman, Goncalo Abecasis, Ravindranath Duggirala…
Admixture mapping is a disease-mapping strategy to identify disease susceptibility variants in an admixed population that is a result of mating between 2 historically separated populations differing in allele ...
Authors: Mengjie Chen, Can Yang, Cong Li, Lin Hou, Xiaowei Chen and Hongyu Zhao
Cryptic population structure can increase both type I and type II errors. This is particularly problematic in case-control association studies of unrelated individuals. Some researchers believe that these prob...
Authors: Robert C Culverhouse, Anthony L Hinrichs and Brian K Suarez
It is well known that genetic association studies are not robust to population stratification. Two widely used approaches for the detection and correction of population structure are principal component analys...
Authors: Timothy Thornton, Matthew P Conomos, Serge Sverdlov, Elizabeth M Blue, Charles YK Cheung, Christopher G Glazner, Steven M Lewis and Ellen M Wijsman
Admixture mapping and association testing have been successfully applied to the detection of genes for complex diseases. Methods have also been developed to combine these approaches. As an initial step to dete...
Authors: Daniel Yorgov, Karen L Edwards and Stephanie A Santorico
In this study, we analyze the Genetic Analysis Workshop 18 (GAW18) data to identify regions of single-nucleotide polymorphisms (SNPs), which significantly influence hypertension status among individuals. We ha...
Authors: Michael Agne, Chien-Hsun Huang, Inchi Hu, Haitian Wang, Tian Zheng and Shaw-Hwa Lo
Sequencing technologies have enabled the investigation of whole genomes of many individuals in parallel. Studies have shown that the joint consideration of multiple rare variants may explain a relevant proport...
Authors: Carmen Dering, Arne Schillert, Inke R König and Andreas Ziegler
The focus of our work is to evaluate several recently developed pooled association tests for rare variants and assess the impact of different gene annotation methods and binning strategies on the analyses of r...
Authors: Andriy Derkach, Jerry F Lawless, Daniele Merico, Andrew D Paterson and Lei Sun
Sequence kernel association test (SKAT) has become one of the most commonly used nonburden tests for analyzing rare variants. Performance of burden tests depends on the weighting of rare and common variants wh...
Grouping variants based on gene mapping can augment the power of rare variant association tests. Weighting or sorting variants based on their expected functional impact can provide additional benefit. We defin...
Authors: Thomas Nalpathamkalam, Andriy Derkach, Andrew D Paterson and Daniele Merico
Analysis of longitudinal family data is challenging because of 2 sources of correlations: correlations across longitudinal measurements and correlations among related individuals. We investigated whether analy...
Authors: Yun Ju Sung, Jacob Basson and Dabeeru C Rao
We are now well into the sequencing era of genetic analysis, and methods to investigate rare variants associated with disease remain in high demand. Currently, the more common rare variant analysis methods are...
Authors: Michael D Swartz, Taebeom Kim, Jiangong Niu, Robert K Yu, Sanjay Shete and Iuliana Ionita-Laza
Because of low statistical power of single-variant tests for whole genome sequencing (WGS) data, the association test for variant groups is a key approach for genetic mapping. To address the features of sparse...
Homozygosity disequilibrium (HD), a nonrandom sizable run of homozygosity in the genome, may be related to the evolution of populations and may also confer susceptibility to disease. No studies have investigat...
Whole genome sequencing (WGS) remains prohibitively expensive, which has encouraged the development of methods to impute WGS data into nonsequenced individuals using a framework of single nucleotide polymorphi...
Authors: August N Blackburn, Angela K Dean and Donna M Lehman
The ideal genetic analysis of family data would include whole genome sequence on all family members. A strategy of combining sequence data from a subset of key individuals with inexpensive, genome-wide associa...
Authors: Anthony L Hinrichs, Robert C Culverhouse and Brian K Suarez
We derive the analytical mean and variance of the score test statistic in gene-dropping simulations and approximate the null distribution of the test statistic by a normal distribution. We provide insights int...
Authors: Yuan Jiang, Sarah Emerson, Lu Wang, Lujing Li and Yanming Di
We demonstrate the flexibility of identity-by-descent (IBD) graphs for genotype imputation and testing relationships between genotype and phenotype. We analyzed chromosome 3 and the first replicate of simulate...
Authors: Elizabeth Marchani Blue, Charles YK Cheung, Christopher G Glazner, Matthew P Conomos, Steven M Lewis, Serge Sverdlov, Timothy Thornton and Ellen M Wijsman
We developed a general framework for family-based imputation using single-nucleotide polymorphism data and sequence data distributed by Genetic Analysis Workshop 18. By using PedIBD, we first inferred haplotyp...
Authors: Sunah Song, Robert Shields, Xin Li and Jing Li
Although the technical and analytic complexity of whole genome sequencing is generally appreciated, best practices for data cleaning and quality control have not been defined. Family based data can be used to ...
Authors: Valentina V Pilipenko, Hua He, Brad G Kurowski, Eileen S Alexander, Xue Zhang, Lili Ding, Tesfaye B Mersha, Leah Kottyan, David W Fardo and Lisa J Martin
Genotype errors are well known to increase type I errors and/or decrease power in related tests of genotype-phenotype association, depending on whether the genotype error mechanism is associated with the pheno...
Authors: Ally Rogers, Andrew Beck and Nathan L Tintle
Pedigree errors and cryptic relatedness often appear in families or population samples collected for genetic studies. If not identified, these issues can lead to either increased false negatives or false posit...
De novo mutations enrich the sequence diversity and carry the clue of evolutional selection. Recent studies suggest the de novo mutations could be one of the risk factors for complex diseases. We conducted a surv...
Large-scale genetic studies are often composed of related participants, and utilizing familial relationships can be cumbersome and computationally challenging. We present an approach to efficiently handle sequ...
Authors: Xiuhua Ding, Shaoyong Su, Kannabiran Nandakumar, Xiaoling Wang and David W Fardo
Family based association studies are employed less often than case-control designs in the search for disease-predisposing genes. The optimal statistical genetic approach for complex pedigrees is unclear when e...
Authors: David W Fardo, Xue Zhang, Lili Ding, Hua He, Brad Kurowski, Eileen S Alexander, Tesfaye B Mersha, Valentina Pilipenko, Leah Kottyan, Kannabiran Nandakumar and Lisa Martin
We apply a family-based extension of the sequence kernel association test (SKAT) to 93 trios extracted from the 20 pedigrees in the Genetic Analysis Workshop 18 simulated data. Each extracted trio includes a u...
Authors: Jing Huang, Yong Chen, Michael D Swartz and Iuliana Ionita-Laza
Rare variants may, in part, explain some of the hereditability missing in current genome-wide association studies. Many gene-based rare-variant analysis approaches proposed in recent years are aimed at populat...
Authors: Dalin Li, Jerome I Rotter, and Xiuqing Guo
Because the genotype-phenotype correlation information is investigated differently by linkage and association analyses, various efforts have been made to model linkage and association jointly. However, joint m...
Authors: Yi Li, Jia Nee Foo, Herty Liany, Hui-Qi Low and Jianjun Liu
Identifying genetic variants associated with complex diseases is an important task in genetic research. Although association studies based on unrelated individuals (ie, case-control genome-wide association stu...
The application of family-based tests to whole-genome sequenced data provides a new window on the role of rare variant alleles in the etiology of disease. By applying family-based tests to these data, we can n...
Authors: Mengyuan Xu, Harold Z Wang, Wei Guo, Haide Qin and Yin Y Shugart
The cost of next-generation sequencing is now approaching that of the first generation of genome-wide single-nucleotide genotyping panels, but this is still out of reach for large-scale epidemiologic studies w...
The revolution in next-generation sequencing has made obtaining both common and rare high-quality sequence variants across the entire genome feasible. Because researchers are now faced with the analytical chal...
Authors: Jin J Zhou, Wai-Ki Yip, Michael H Cho, Dandi Qiao, Merry-Lynn N McDonald and Nan M Laird
In this analysis, we investigate the contributions that linkage-based methods, such as identical-by-descent mapping, can make to association mapping to identify rare variants in next-generation sequencing data...
Authors: Brunilda Balliu, Hae-Won Uh, Roula Tsonaka, Stefan Boehringer, Quinta Helmer and Jeanine J Houwing-Duistermaat
The genetic variants associated with blood pressure identified so far explain only a small proportion of the total heritability of this trait. With recent advances in sequencing technology and statistical meth...
Authors: Han Chen, Seung Hoan Choi, Jaeyoung Hong, Chen Lu, Jacqueline N Milton, Catherine Allard, Sean M Lacey, Honghuang Lin and Josée Dupuis
Until very recently, few methods existed to analyze rare-variant association with binary phenotypes in complex pedigrees. We consider a set of recently proposed methods applied to the simulated and real hypert...
Authors: Allison Hainline, Carolina Alvarez, Alexander Luedtke, Brian Greco, Andrew Beck and Nathan L Tintle
In this study, we analyze the Genetic Analysis Workshop 18 data to identify the genes and underlying single-nucleotide polymorphisms on 11 chromosomes that exhibit significant association with systolic blood p...
As the cost of DNA sequencing decreases, association studies based on whole genome sequencing are now becoming feasible. It is still unclear, however, how much more we could gain from whole genome sequencing c...
Authors: Sean Lacey, Jae Yoon Chung and Honghuang Lin
High-throughput sequencing technology allows researchers to test associations between phenotypes and all the variants identified throughout the genome, and is especially useful for analyzing rare variants. How...
Authors: Cong Li, Can Yang, Mengjie Chen, Xiaowei Chen, Lin Hou and Hongyu Zhao
Family data and rare variants are two key features of whole genome sequencing analysis for hunting the missing heritability of common human diseases. Recently, Zhu and Xiong proposed the generalized T2 tests that...
The kernel score statistic is a global covariance component test over a set of genetic markers. It provides a flexible modeling framework and does not collapse marker information. We generalize the kernel scor...
Authors: Dörthe Malzahn, Stefanie Friedrichs, Albert Rosenberger and Heike Bickeböller
To avoid inflated type I error and reduced power in genetic association studies, it is necessary to adjust properly for population stratification and known/unknown subject relatedness. It would be interesting ...
Under the premise that multiple causal variants exist within a disease gene and that we are underpowered to detect these variants individually, a variety of methods have been developed that attempt to cluster ...
Next-generation sequencing technologies have been designed to discover rare and de novo variants and are an important tool for identifying rare disease variants. Many statistical methods have been developed to te...
The primary goal of genome-wide association studies is to determine which genetic markers are associated with genetic traits, most commonly human diseases. As a result of the "large p, small n" nature of genome-w...
Systolic blood pressure and diastolic blood pressure are known risk factors for cardiovascular diseases and understanding their genetic basis will have important public health implications. For rare variants, ...
Current sequencing technology enables generation of whole genome sequencing data sets that contain a high density of rare variants, each of which is carried by, at most, 5% of the sampled subjects. Such varian...
Authors: Ying Liu, ChienHsun Huang, Inchi Hu, Shaw-Hwa Lo and Tian Zheng
Genome-wide association studies are very powerful in determining the genetic variants affecting complex diseases. Most of the available methods are very useful in detecting association between common variants ...
Authors: George Mathew, Varghese George and Hongyan Xu
We propose a novel variance component approach for the analysis of next-generation sequencing data. Our method is based on the detection of the proportion of the trait phenotypic variance that can be explained...
Authors: Juan M Peralta, Marcio Almeida, Jack W Kent Jr and John Blangero
Advances in next-generation sequencing technology have made it possible to comprehensively interrogate the entire spectrum of genomic variations including rare variants. They may help capture the remaining gen...
