Abstract
Previously we showed that a statistically robust version of the sib-pair method greatly increased power to detect linkage in the presence of outliers. In this paper we report on M-estimation to accommodate outliers in the variance-components approach to linkage analysis developed by Amos. Simulations show that in the presence of outliers the robust variance-components approach provides substantially greater power, more precise estimation of heritabilities, and better false-positive rates than the original Gaussian based approach. In the absence of outliers the performance of the robust variance-components approach is similar to that of the Gaussian based approach. For illustration we apply the method to two well characterized lipoprotein systems.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 249-262 |
| Number of pages | 14 |
| Journal | Annals of Human Genetics |
| Volume | 63 |
| Issue number | 3 |
| DOIs | |
| State | Published - May 1999 |
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ASJC Scopus subject areas
- Genetics(clinical)
- Genetics
Cite this
A statistically robust variance-components approach for quantitative trait linkage analysis. / Wang, J.; Guerra, R.; Cohen, J.
In: Annals of Human Genetics, Vol. 63, No. 3, 05.1999, p. 249-262.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - A statistically robust variance-components approach for quantitative trait linkage analysis
AU - Wang, J.
AU - Guerra, R.
AU - Cohen, J.
PY - 1999/5
Y1 - 1999/5
N2 - Previously we showed that a statistically robust version of the sib-pair method greatly increased power to detect linkage in the presence of outliers. In this paper we report on M-estimation to accommodate outliers in the variance-components approach to linkage analysis developed by Amos. Simulations show that in the presence of outliers the robust variance-components approach provides substantially greater power, more precise estimation of heritabilities, and better false-positive rates than the original Gaussian based approach. In the absence of outliers the performance of the robust variance-components approach is similar to that of the Gaussian based approach. For illustration we apply the method to two well characterized lipoprotein systems.
AB - Previously we showed that a statistically robust version of the sib-pair method greatly increased power to detect linkage in the presence of outliers. In this paper we report on M-estimation to accommodate outliers in the variance-components approach to linkage analysis developed by Amos. Simulations show that in the presence of outliers the robust variance-components approach provides substantially greater power, more precise estimation of heritabilities, and better false-positive rates than the original Gaussian based approach. In the absence of outliers the performance of the robust variance-components approach is similar to that of the Gaussian based approach. For illustration we apply the method to two well characterized lipoprotein systems.
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U2 - 10.1017/S0003480099007514
DO - 10.1017/S0003480099007514
M3 - Article
C2 - 10738537
AN - SCOPUS:0032873304
VL - 63
SP - 249
EP - 262
JO - Annals of Human Genetics
JF - Annals of Human Genetics
SN - 0003-4800
IS - 3
ER -