Genetic Analysis Workshop II: sib pair screening tests for linkage

For each marker locus and for every pair of sibs with data available in the 1983 workshop data, the proportion of genes identical by descent was estimated. The mean proportions were compared between concordant and discordant sib pairs, and the mean proportion for concordantly affected pairs was compared with one half. Together with standard tests of association, these found to be sensitive screening tests for linkage.     

Haplotype sharing analysis in affected individuals from nuclear families with at least one affected offspring

In diseases with a complex mode of inheritance, families with multiple affected individuals are difficult to ascertain. The haplotype sharing statistic (HSS) uses (hidden) co-ancestry between affected individuals from a founder population. These affected individuals will likely not only share the same mutation(s), but also the surrounding haplotype. We show that this method gives a low false positive rate, but does not detect genes in the nuclear families of Problem 2A of the GAW data. We also give evidence based on simulations and empirical studies in real population based data that the HSS method has statistical power. © 1997 Wiley-Liss, Inc.     

Model-free age-of-onset methods applied to the linkage of bipolar disorder

We performed Haseman-Elston regression on a set of bipolar pedigrees using each of three dependent variables: a binary trait indicating disease concordance or discordance, a binary trait adjusted for age-of-onset, and the residuals from a survival analysis. The latter two methods, which both adjust for age-of-onset, gave smaller p-values when previous analyses suggested linkage between disease and marker, but not when previous analyses were not suggestive of linkage. © 1997 Wiley-Liss, Inc.     

Calculation of IBD probabilities with dense SNP or sequence data

The probabilities that two individuals share 0, 1, or 2 alleles identical by descent (IBD) at a given genotyped marker locus are quantities of fundamental importance for disease gene and quantitative trait mapping and in family-based tests of association. Until recently, genotyped markers were sufficiently sparse that founder haplotypes could be modelled as having been drawn from a population in linkage equilibrium for the purpose of estimating IBD probabilities. However, with the advent of high-throughput single nucleotide polymorphism genotyping assays, this is no longer a reasonable assumption. Indeed, the imminent arrival of individual sequencing will enable high-density single nucleotide polymorphism genotyping on a scale for which current algorithms are not equipped. In this paper, we present a simple new model in which founder haplotypes are modelled as a Markov chain. Another important innovation is that genotyping errors are explicitly incorporated into the model. We compare results obtained using the new model to those obtained using the popular genetic linkage analysis package Merlin, with and without using the cluster model of linkage disequilibrium that is incorporated into that program. We find that the new model results in accuracy approaching that of Merlin with haplotype blocks, but achieves this with orders of magnitude faster run times. Moreover, the new algorithm scales linearly with number of markers, irrespective of density, whereas Merlin scales supralinearly. We also confirm a previous finding that ignoring linkage disequilibrium in founder haplotypes can cause errors in the calculation of IBD probabilities.     

Genetic analysis workshop III: Sib pair analyses to determine linkage groups and to order loci

The methods proposed by Haseman and Elston [1972] were used to estimate the proportion of genes identical by descent shared by each sib pair at each locus. These estimates were then used as a basis for obtaining all possible locus-locus correlations. The 12 significant correlations (P < .01) and their rank order indicated the correct linkage groups and the order of the loci.     

Genomic sharing surrounding alleles identical by descent: Effects of genetic drift and population growth

The number of identical deleterious mutations present in a population may become very large, depending on the combined effect of genetic drift, population growth and limited negative selection. The distribution of the length of the shared area between two random chromosomes carrying the mutations has been investigated for a number of generations varying from 20-100 since introduction. The consequences for investigations using association and haplotype sharing methods are discussed. © 1997 Wiley-Liss, Inc.     

Screening for linkage using a multipoint identity-by-descent method

The multipoint identity-by-descent method (MIM) was used to analyze simulated data for quantitative traits from GAW9. A two-stage method of implementation was used. First, polymorphic markers spaced 6-12 cM apart were used to identify chromosomes of interest for each trait Q1-Q4; and second, for each of these chromosomes, markers spaced 2 cM apart were used to confirm the linkage detected and refine the region for the susceptibility loci. MIM performed well at both levels of mapping, correctly detecting major genes for trait Q3 on chromosome 2, trait Q2 on chromosome 1, and trait Q4 on chromosome 5. © 1995 Wiley-Liss, Inc.     

Covariates in Linkage Analysis Using Sibling and Cousin Pairs

Using simulated data from GAW 12, problem 2, we further develop a novel technique to detect and use significant covariates in linkage analysis. The method, first introduced by Rice et al. [Genet Epidemiol 17(Suppl. 1):S691–5, 19991, uses logistic regression to model perturbation in sharing as a function of covariate levels. The original method allows use of all sib pairs (concordant affected, concordant unaffected, and discordant). Here we extend this method to include cousin pairs in analysis. © 2001 Wiley‐Liss, Inc.     

Affected-only multiplex pedigree analysis of GAW10 problem 2

From a single extended pedigree simulation replicate, high density, affected only subpedigrees were isolated, based on the T > 40 affected status for the disease trait, Q1. On this sample of 14 pedigrees, with a range of two to six affected members (48 total), we conducted a haplotype based, multilocus, nonparametric genome-wide search of the provided data (367 markers) using the computer program GENEHUNTER. As with most genome screens in complex diseases, the objective of this strategy was to identify regions (hot-spots) which breached our predetermined threshold (p < 0.05), requiring confirmation by other groups or consortia. Of the six regions with threshold breaching scores (p < 0.05), the most promising, on chromosome 8 and chromosome 4, corresponded to the locations of MG2 and MG3. Both of these regions have multiple, consecutive markers above threshold and contained the only scores that exceeded p < 0.01. In addition, a fourth hot-spot consisting of a single marker above threshold, was less than 15 cm from MG1 on chromosome 5. The positions of the remaining three hot-spots did not correspond to the any of the major genes and are therefore false positives. An additional analysis of a single nuclear pedigree simulation replicate, using the extended transmission disequilibrium test (ETDT), was applied to markers in each of the above hot-spot regions to look for evidence of disequilibrium with the disease trait. This analysis provided weak additional support for the chromosome 8 finding, even though the sample was very small (36 pedigrees containing 44 affected offspring). © 1997 Wiley-Liss, Inc.     

Identifying Susceptibility Genes Using Linkage and Linkage Disequilibrium Analysis in Large Pedigrees

Linkage and linkage disequilibrium tests are powerful tools for mapping complex disease genes. We investigated two approaches to identifying markers associated with disease. One method applied linkage analysis and then linkage disequilibrium tests to markers within linked regions. The other method looked for linkage disequilibrium with disease using all markers. Additionally, we investigated using Simes’ test to combine p‐values from linkage disequilibrium tests for nearby markers. We applied both approaches to all replicates of the Genetic Analysis Workshop 12 problem 2 isolated population data set. We reported results from the 25^th replicate as if it were a real problem and assessed the power of our methods using all replicates. Using all replicates, we found that testing all markers for linkage disequilibrium with disease was more powerful than identifying markers that were in linkage with disease and then testing markers within those regions for linkage disequilibrium with the implementations that we chose. Using Simes’ test to combine p‐values for linkage disequilibrium tests on correlated markers seemed to be of marginal value. © 2001 Wiley‐Liss, Inc.     

Impact of parental relationships in maximum lod score affected sib-pair method

Many studies are done in small isolated populations and populations where marriages between relatives are encouraged. In this paper, we point out some problems with applying the maximum lod score (MLS) method (Risch, [1990] Am. J. Hum. Genet. 46:242-253) in these populations where relationships exist between the two parents of the affected sib-pairs. Characterizing the parental relationships by the kinship coefficient between the parents (f), the maternal inbreeding coefficient (alpha(m), and the paternal inbreeding coefficient (alpha(p)), we explored the relationship between the identity by descent (IBD) vector expected under the null hypothesis of no linkage and these quantities. We find that the expected IBD vector is no longer (0.25, 0.5, 0.25) when f, alpha(m), and alpha(p) differ from zero. In addition, the expected IBD vector does not always follow the triangle constraints recommended by Holmans ([1993] Am. J. Hum. Genet. 52:362-374). So the classically used MLS statistic needs to be adapted to the presence of parental relationships. We modified the software GENEHUNTER (Kruglyak et al. [1996] Am. J. Hum. Genet. 58: 1347-1363) to do so. Indeed, the current version of the software does not compute the likelihood properly under the null hypothesis. We studied the adapted statistic by simulating data on three different family structures: (1) parents are double first cousins (f=0.125, alpha(m)=alpha(p)=0), (2) each parent is the offspring of first cousins (f=0, alpha(m)=alpha(p)=0.0625), and (3) parents are related as in the pedigree from Goddard et al. ([1996] Am. J. Hum. Genet. 58:1286-1302) (f=0.109, alpha(m)=alpha(p)=0.0625). The appropriate threshold needs to be derived for each case in order to get the correct type I error. And using the classical statistic in the presence of both parental kinship and parental inbreeding almost always leads to false conclusions.