Abstract
While extensive analyses have been conducted to test for, no formal analyses have been conducted to test against, the importance of candidate genes with random population samples. We develop a LOD score approach for exclusion analyses of candidate genes with random population samples. Under this approach, specific genetic effects and inheritance models at candidate genes can be analysed and if a LOD score is ≤ - 2.0, the locus can be excluded from having an effect larger than that specified. Computer simulations show that, with sample sizes often employed in association studies, this approach has high power to exclude a gene from having moderate genetic effects. In contrast to regular association analyses, population admixture will not affect the robustness of our analyses; in fact, it renders our analyses more conservative and thus any significant exclusion result is robust. Our exclusion analysis complements association analysis for candidate genes in random population samples and is parallel to the exclusion mapping analyses that may be conducted in linkage analyses with pedigrees or relative pairs. The usefulness of the approach is demonstrated by an application to test the importance of vitamin D receptor and estrogen receptor genes underlying the differential risk to osteoporotic fractures.
| Original language | English |
|---|---|
| Pages (from-to) | 313-329 |
| Number of pages | 17 |
| Journal | Annals of Human Genetics |
| Volume | 65 |
| Issue number | 3 |
| DOIs | |
| State | Published - 2001 |
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All Science Journal Classification (ASJC) codes
- Genetics(clinical)
- Genetics
Cite this
LOD score exclusion analyses for candidate genes using random population samples. / Deng, H. W.; Li, J.; Recker, Robert R.
In: Annals of Human Genetics, Vol. 65, No. 3, 2001, p. 313-329.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - LOD score exclusion analyses for candidate genes using random population samples
AU - Deng, H. W.
AU - Li, J.
AU - Recker, Robert R.
PY - 2001
Y1 - 2001
N2 - While extensive analyses have been conducted to test for, no formal analyses have been conducted to test against, the importance of candidate genes with random population samples. We develop a LOD score approach for exclusion analyses of candidate genes with random population samples. Under this approach, specific genetic effects and inheritance models at candidate genes can be analysed and if a LOD score is ≤ - 2.0, the locus can be excluded from having an effect larger than that specified. Computer simulations show that, with sample sizes often employed in association studies, this approach has high power to exclude a gene from having moderate genetic effects. In contrast to regular association analyses, population admixture will not affect the robustness of our analyses; in fact, it renders our analyses more conservative and thus any significant exclusion result is robust. Our exclusion analysis complements association analysis for candidate genes in random population samples and is parallel to the exclusion mapping analyses that may be conducted in linkage analyses with pedigrees or relative pairs. The usefulness of the approach is demonstrated by an application to test the importance of vitamin D receptor and estrogen receptor genes underlying the differential risk to osteoporotic fractures.
AB - While extensive analyses have been conducted to test for, no formal analyses have been conducted to test against, the importance of candidate genes with random population samples. We develop a LOD score approach for exclusion analyses of candidate genes with random population samples. Under this approach, specific genetic effects and inheritance models at candidate genes can be analysed and if a LOD score is ≤ - 2.0, the locus can be excluded from having an effect larger than that specified. Computer simulations show that, with sample sizes often employed in association studies, this approach has high power to exclude a gene from having moderate genetic effects. In contrast to regular association analyses, population admixture will not affect the robustness of our analyses; in fact, it renders our analyses more conservative and thus any significant exclusion result is robust. Our exclusion analysis complements association analysis for candidate genes in random population samples and is parallel to the exclusion mapping analyses that may be conducted in linkage analyses with pedigrees or relative pairs. The usefulness of the approach is demonstrated by an application to test the importance of vitamin D receptor and estrogen receptor genes underlying the differential risk to osteoporotic fractures.
UR - http://www.scopus.com/inward/record.url?scp=0034943926&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0034943926&partnerID=8YFLogxK
U2 - 10.1017/S0003480001008673
DO - 10.1017/S0003480001008673
M3 - Article
C2 - 11427187
AN - SCOPUS:0034943926
VL - 65
SP - 313
EP - 329
JO - Annals of Human Genetics
JF - Annals of Human Genetics
SN - 0003-4800
IS - 3
ER -