Abstract
Three variants of the confidence set inference (CSI) procedure were proposed and applied to both the simulated and the Collaborative Study on the Genetics of Alcoholism (COGA) data. For each of the two applications, we first performed a preliminary genome scan study based on the microsatellite markers using the GENEHUNTER+ software to identify regions that potentially harbor disease loci. For each such region, we estimated the sibling identity-by-descent sharing probability distribution at the putative disease locus. Based on these estimated probabilities, the CSI procedures were employed to further localize the disease loci using the single-nucleotide polymorphism markers, leading to confidence intervals/regions for their locations. For our analysis with the simulated data, we had knowledge of the simulating models at the time we performed the analysis.
Highlights
A frequently used strategy in linkage analysis is to first screen the entire genome using microsatellite (MS) markers, and to follow up on preliminary linkage regions using densely saturated (often single-nucleotide polymorphisms (SNP)) markers
We decided to focus on those 4 chromosomes for obtaining confidence regions using confidence set inference (CSI) and its variants based on the 3-cM-density SNPs
The four confidence regions plotted below the curve are the results from the four CSI procedures using the SNPs, as identified in the legend of the figure
Summary
A frequently used strategy in linkage analysis is to first screen the entire genome using microsatellite (MS) markers, and to follow up on preliminary linkage regions using densely saturated (often single-nucleotide polymorphisms (SNP)) markers. The confidence set inference (CSI) procedure [2] can be used to obtain confidence estimates using affected sibpair (ASP) data, and avoids the multiple testing problem. Unlike the approach of Liang et al [1], it is not based on the asymptotic distribution of the estimator of the location of the trait locus Instead, it indirectly deduces a confidence region for the trait locus based upon a set of markers that are inferred to be within a pre-specified distance from the trait locus. It indirectly deduces a confidence region for the trait locus based upon a set of markers that are inferred to be within a pre-specified distance from the trait locus Note that this is a non-directional procedure that makes no distinction between loci symmetrically located around a marker. The last is a multipoint approach, but the identity-by-descent (IBD) sharing statistic is calculated at each hypothesized disease locus rather than at its nearest marker locus
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