Volume 1 Supplement 1
Genetic Analysis Workshop 15: Gene Expression Analysis and Approaches to Detecting Multiple Functional Loci. Go to conference site.
St. Pete Beach, Florida, USA11-15 November 2006
Page 1 of 4
Here we describe the data provided for Problem 1 of Genetic Analysis Workshop 15. The data provided for Problem 1 were unusual in two ways. First, the phenotype was the level of gene expression for each gene, ...
For Genetic Analysis Workshop 15 Problem 2, we organized data from several ongoing studies designed to identify genetic and environmental risk factors for rheumatoid arthritis. Data were derived from the North...
Data for Problem 3 of the Genetic Analysis Workshop 15 were generated by computer simulation in an attempt to mimic some of the genetic and epidemiological features of rheumatoid arthritis (RA) such as its pop...
While genome-wide linkage studies have been successful in mapping variants underlying rare monogenic disorders, genome-wide association studies may be more appropriate for detecting common variants of modest e...
Several methods to identify tagging single-nucleotide polymorphisms (SNPs) are in common use for genetic epidemiologic studies; however, there may be loss of information when using only a subset of SNPs. We so...
Assuming multiple loci play a role in regulating the expression level of a single phenotype, we propose a new approach to identify cis- and trans-acting loci that regulate gene expression. Using the Problem 1 dat...
Genotype-expression association analysis using linear regression may produce different test results depending on whether founders only or all pedigreed members are used. This difference is not due to the corre...
Mutual information (MI) is a robust nonparametric statistical approach for identifying associations between genotypes and gene expression levels. Using the data of Problem 1 provided for the Genetic Analysis W...
The mRNA expression levels of genes have been shown to have discriminating power for the classification of breast cancer. Studying the heritability of gene expression levels on breast cancer related transcript...
The Genetic Analysis Workshop 15 rheumatoid arthritis data included a set of 460 cases and 460 controls genotyped at 2300 closely spaced markers on a 10 megabase region of chromosome 18q. We conducted a multil...
PedGenie beta version 2.1 is a unique, flexible, and easily implemented analysis software tool that is enhanced significantly by incorporation of meta-statistics to allow valid combined analysis of multiple st...
Rheumatoid arthritis (RA, MIM 180300) is a common and complex inflammatory disorder. The North American Rheumatoid Arthritis Consortium (NARAC) data, as part of the Genetic Analysis Workshop 15 data, consists ...
In the present paper, we used the North American Rheumatoid Arthritis Consortium data provided for Genetic Analysis Workshop 15 Problem 2 to: 1) estimate the penetrances of PTPN22 and HLA-DRB1 and, 2) test the...
We analyzed a case-control data set for chromosome 18q from the Genetic Analysis Workshop 15 to detect susceptibility loci for rheumatoid arthritis (RA). A total number of 460 cases and 460 unaffected controls...
As genome-wide association studies grow in popularity for the identification of genetic factors for common and rare diseases, analytical methods to comb through large numbers of genetic variants efficiently to...
We examined the potential gene × gene interactions and gene × smoking interactions in rheumatoid arthritis (RA) using the candidate gene data sets provided by Genetic Analysis Workshop 15 Problem 2. The multif...
Although single chi-square analysis of the North American Rheumatoid Arthritis Consortium (NARAC) data identifies many single-nucleotide polymorphisms (SNPs) with p-values less than 0.05, none remain significant ...
Rheumatoid arthritis (RA) is an autoimmune disease with a moderately strong genetic component. Previous linkage and candidate gene studies have identified several regions that predispose to RA, including the HLA-...
Rheumatoid arthritis (RA) is a disorder with important public health implications. It is possible that there are clinically distinctive subtypes of the disorder with different genetic etiologies. We used the d...
Haplotype association analysis based on arbitrarily chosen markers might lower statistical power because of the larger number of degrees of freedom caused by irrelevant makers.
We recently described a new method to identify disease susceptibility loci, based on the analysis of the evolutionary relationships between haplotypes of cases and controls. However, haplotypes are often unkno...
We performed linkage and family-based association analysis across chromosomes 1–22 in Replicates 1–5 of the Genetic Analysis Workshop 15 simulated data. Linkage analysis was performed using the Kong and Cox al...
The presence of missing data in association studies is an important problem, particularly with high-density single-nucleotide polymorphism (SNP) maps, because the probability that at least one genotype is miss...
Several recent papers have suggested that two-locus tests of association that incorporate gene × gene interaction can be more powerful than marginal, single-locus tests across a broad range of multilocus inter...
The transmission/disequilibrium test was introduced to test for linkage and association between a marker and a putative disease locus using case-parent triads. Several extensions have been proposed to accommod...
Clustering of related haplotypes in haplotype-based association mapping has the potential to improve power by reducing the degrees of freedom without sacrificing important information about the underlying gene...
We present a new method for testing association when data from both case-parents trios and unrelated controls are available. Our method combines test statistics for case-parents trio and unrelated case-control...
Related cases may be included in case-control association studies if correlations between related individuals due to identity-by-descent (IBD) sharing are taken into account. We derived a framework to test for...
The simulated data set of the Genetic Analysis Workshop 15 provided affection status, four quantitative traits, and a covariate. After studying the relationship between these variables, linkage analysis was un...
The goal of this analysis is to compare different test strategies for genetic association in case-control studies using related individuals. The first test is the trend test that is corrected for related indiv...
Family-based association approaches such as the transmission-disequilibrium test (TDT) are used extensively in the study of genetic traits because they are generally robust to the presence of population struct...
We performed a case-control association analysis of rheumatoid arthritis (RA) for several candidate genes using the North American Rheumatoid Arthritis Consortium (NARAC) data provided in Genetic Analysis Work...
We compared and evaluated several variable and model selection methods using Bayesian and non-Bayesian approaches for three replicates of the Genetic Analysis Workshop 15 (GAW15) simulated data. In doing so, t...
We propose a nonparametric association analysis combining both family and unrelated case-control genotype data. Under the assumption of Hardy-Weinberg equilibrium, we formed an affected group to compare with a...
In a small chromosomal region, a number of polymorphisms may be both linked to and associated with a disease. Potentially directly associated causal loci may be distinguished from indirectly associated loci by...
In order to model the effect of PTPN22 on rheumatoid arthritis (RA), we determined the combination of single-nucleotide-polymorphisms (SNPs) showing the strongest association with RA. Three SNPs (rs2476601-rs1273...
There has been a growing interest in developing strategies for identifying single-nucleotide polymorphisms (SNPs) that explain a linkage signal by joint modeling of linkage and association. We compare several ...
To detect association of the DR1 allele with rheumatoid arthritis (RA) given linkage in the affected sibling pairs of the replicates of Problem 3 of Genetic Analysis Workshop 15 (GAW15), we propose a new score...
This study evaluated the utility of unrelated controls and flanking markers when performing joint modeling of linkage and association by the LAMP software (version 0.0.6) [Am J Hum Genet 2005, 76:934–949; Am J Hu...
After genetic linkage has been identified for a complex disease, the next step is often fine-mapping by association analysis, using single-nucleotide polymorphisms (SNPs) within a linkage region. If a SNP show...
The influence of certain alleles of the HLA-DRB1 locus on risk for rheumatoid arthritis has been well established through linkage and association studies. In addition, other loci in the HLA region on 6p21 may ...
We carried out an analysis of the Genetic Analysis Workshop 15 simulated Problem 3 data. We restricted ourselves to the present/absent phenotype. Linkage analysis revealed a very strong signal on chromosome 6....
A family-based association study design is not only able to localize causative genes more precisely than linkage analysis, but it also helps explain the genetic mechanism underlying the trait under study. Ther...
Gene expression profiles and single-nucleotide polymorphism (SNP) profiles are modern data for genetic analysis. It is possible to use the two types of information to analyze the relationships among genes by s...
Performing linkage and association analyses on a large set of correlated data presents an interesting set of problems. In the current setting, we have 3554 expression levels from lymphoblastoid cell lines in 1...
Using single-nucleotide polymorphism (SNP) genotypes and selected gene expression phenotypes from 14 CEPH (Centre d'Etude du Polymorphisme Humain) pedigrees provided for Genetic Analysis Workshop 15 (GAW15), w...
Extensive studies have been performed to analyze variation in gene expression data by using multistage approaches, including a combination of microarray and linkage analysis. Such a method was recently used in...
Traditional studies of familial aggregation are aimed at defining the genetic (and non-genetic) causes of a disease from physiological or clinical traits. However, there has been little attempt to use genome-w...
About 28% of genes appear to have an expression pattern that follows a mixture distribution. We use first- and second-order partial correlation coefficients to identify trios and quartets of non-sex-linked gen...
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