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A likelihood-based procedure for obtaining confidence intervals of disease loci with general pedigree data.

Wan S, Lin S - BMC Proc (2007)

Bottom Line: We also proposed asymptotic approaches based on GLRT and GLRT/MA as alternatives that are much more efficient computationally but depends on the reliability of the limiting distributions.Besides its efficiency, the asymptotic procedure based on GLRT/MA also takes model uncertainty into consideration.Applications of these methods to the Genetic Analysis Workshop 15 (GAW15) rheumatoid arthritis data from the French population gave results that successfully captured the well recognized susceptibility gene HLA*DRB1 to a less than 6 cM, 99% confidence interval with the two asymptotic approaches.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Statistics, The Ohio State University, 1958 Neil Avenue, 404 Cockins Hall, Columbus, Ohio 43210, USA. shuyan_wan@merck.com

ABSTRACT
We proposed a confidence interval method for disease gene localization by testing every position on each chromosome of interest for its possibility of being a disease locus and including those not rejected into the interval. Three test statistics were proposed to perform the tests, including one based on LOD and two generalized likelihood ratio tests with or without model averaging (GLRT/MA and GLRT). For the statistic based on LOD, an integrated procedure was proposed with an adaptive and an importance sampling component. We also proposed asymptotic approaches based on GLRT and GLRT/MA as alternatives that are much more efficient computationally but depends on the reliability of the limiting distributions. Besides its efficiency, the asymptotic procedure based on GLRT/MA also takes model uncertainty into consideration. Applications of these methods to the Genetic Analysis Workshop 15 (GAW15) rheumatoid arthritis data from the French population gave results that successfully captured the well recognized susceptibility gene HLA*DRB1 to a less than 6 cM, 99% confidence interval with the two asymptotic approaches.

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99% Confidence intervals of French data. The 99% confidence intervals for rheumatoid arthritis data (French population) analyzed by model FR2. Dashed vertical line is at the HLA*DRB1 locus. *Interval from integrated procedure is a convex set of the original non-contiguous intervals.
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Figure 1: 99% Confidence intervals of French data. The 99% confidence intervals for rheumatoid arthritis data (French population) analyzed by model FR2. Dashed vertical line is at the HLA*DRB1 locus. *Interval from integrated procedure is a convex set of the original non-contiguous intervals.

Mentions: Of all three data sets, the 99% integrated procedure and the asymptotic methods successfully captured the HLA*DRB1 locus with at least one of the disease models. All 99% model averaging methods gave intervals containing the HLA*DRB1 locus. Specifically, when there are strong linkage signals as in the NARAC data (maximum LOD scores around 13), at 99% confidence level, our asymptotic methods gave results with shorter length compared to those from the 3-LOD method. Even when there are only moderate signals as in the FR data (maximum LOD around 2.8), at 99% confidence level, the integrated method and the asymptotic methods with or without model averaging all yielded confidence intervals (from 5 to 20 cM) containing the disease locus compared to the set from the 3-LOD method (Figure 1). Analyses of the UK data also lead to the capturing of the disease locus in all methods, but with lengthier intervals.


A likelihood-based procedure for obtaining confidence intervals of disease loci with general pedigree data.

Wan S, Lin S - BMC Proc (2007)

99% Confidence intervals of French data. The 99% confidence intervals for rheumatoid arthritis data (French population) analyzed by model FR2. Dashed vertical line is at the HLA*DRB1 locus. *Interval from integrated procedure is a convex set of the original non-contiguous intervals.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2367465&req=5

Figure 1: 99% Confidence intervals of French data. The 99% confidence intervals for rheumatoid arthritis data (French population) analyzed by model FR2. Dashed vertical line is at the HLA*DRB1 locus. *Interval from integrated procedure is a convex set of the original non-contiguous intervals.
Mentions: Of all three data sets, the 99% integrated procedure and the asymptotic methods successfully captured the HLA*DRB1 locus with at least one of the disease models. All 99% model averaging methods gave intervals containing the HLA*DRB1 locus. Specifically, when there are strong linkage signals as in the NARAC data (maximum LOD scores around 13), at 99% confidence level, our asymptotic methods gave results with shorter length compared to those from the 3-LOD method. Even when there are only moderate signals as in the FR data (maximum LOD around 2.8), at 99% confidence level, the integrated method and the asymptotic methods with or without model averaging all yielded confidence intervals (from 5 to 20 cM) containing the disease locus compared to the set from the 3-LOD method (Figure 1). Analyses of the UK data also lead to the capturing of the disease locus in all methods, but with lengthier intervals.

Bottom Line: We also proposed asymptotic approaches based on GLRT and GLRT/MA as alternatives that are much more efficient computationally but depends on the reliability of the limiting distributions.Besides its efficiency, the asymptotic procedure based on GLRT/MA also takes model uncertainty into consideration.Applications of these methods to the Genetic Analysis Workshop 15 (GAW15) rheumatoid arthritis data from the French population gave results that successfully captured the well recognized susceptibility gene HLA*DRB1 to a less than 6 cM, 99% confidence interval with the two asymptotic approaches.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Statistics, The Ohio State University, 1958 Neil Avenue, 404 Cockins Hall, Columbus, Ohio 43210, USA. shuyan_wan@merck.com

ABSTRACT
We proposed a confidence interval method for disease gene localization by testing every position on each chromosome of interest for its possibility of being a disease locus and including those not rejected into the interval. Three test statistics were proposed to perform the tests, including one based on LOD and two generalized likelihood ratio tests with or without model averaging (GLRT/MA and GLRT). For the statistic based on LOD, an integrated procedure was proposed with an adaptive and an importance sampling component. We also proposed asymptotic approaches based on GLRT and GLRT/MA as alternatives that are much more efficient computationally but depends on the reliability of the limiting distributions. Besides its efficiency, the asymptotic procedure based on GLRT/MA also takes model uncertainty into consideration. Applications of these methods to the Genetic Analysis Workshop 15 (GAW15) rheumatoid arthritis data from the French population gave results that successfully captured the well recognized susceptibility gene HLA*DRB1 to a less than 6 cM, 99% confidence interval with the two asymptotic approaches.

No MeSH data available.


Related in: MedlinePlus