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Searching for epistatic interactions in nuclear families using conditional linkage analysis.

Publication ,  Journal Article
Shah, SH; Schmidt, MA; Mei, H; Scott, WK; Hauser, ER; Schmidt, S
Published in: BMC Genet
December 30, 2005

BACKGROUND: Genomic screens generally employ a single-locus strategy for linkage analysis, but this may have low power in the presence of epistasis. Ordered subsets analysis (OSA) is a method for conditional linkage analysis using continuous covariates. METHODS: We used OSA to evaluate two-locus interactions in the simulated Genetic Analysis Workshop 14 dataset. We used all nuclear families ascertained by Aipotu, Karangar, and Danacaa. Using the single-nucleotide polymorphism map, multipoint affected-sibling-pair (ASP) linkage analysis was performed on all 100 replicates for each chromosome using SIBLINK. OSA was used to examine linkage on each chromosome using LOD scores at each 3-cM location on every other chromosome as covariates. Two methods were used to identify positive results: one searching across the entire covariate chromosome, the other conditioning on location of known disease loci. RESULTS: Single-locus linkage analysis revealed very high LOD scores for disease loci D1 through D4, with mean LOD scores over 100 replicates ranging from 4.0 to 7.8. Although OSA did not obscure this linkage evidence, it did not detect the simulated interactions between any of the locus pairs. We found inflated type I error rates using the first OSA method, highlighting the need to correct for multiple comparisons. Therefore, using "null chromosome pairs" without simulated disease loci, we calculated a corrected alpha-level. CONCLUSION: We were unable to detect two-locus interactions using OSA. This may have been due to lack of incorporation of phenotypic subgroups, or because linkage evidence as summarized by LOD scores performs poorly as an OSA covariate. We found inflated type I error rates, but were able to calculate a corrected alpha-level for future analyses employing this strategy to search for two-locus interactions.

Duke Scholars

Published In

BMC Genet

DOI

EISSN

1471-2156

Publication Date

December 30, 2005

Volume

6 Suppl 1

Issue

Suppl 1

Start / End Page

S148

Location

England

Related Subject Headings

  • Reproducibility of Results
  • Nuclear Family
  • Humans
  • Genetics & Heredity
  • Epistasis, Genetic
  • Disease
  • Chromosomes, Human
  • Chromosome Mapping
  • 3105 Genetics
  • 0604 Genetics
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Shah, S. H., Schmidt, M. A., Mei, H., Scott, W. K., Hauser, E. R., & Schmidt, S. (2005). Searching for epistatic interactions in nuclear families using conditional linkage analysis. BMC Genet, 6 Suppl 1(Suppl 1), S148. https://doi.org/10.1186/1471-2156-6-S1-S148
Shah, Svati H., Michael A. Schmidt, Hao Mei, William K. Scott, Elizabeth R. Hauser, and Silke Schmidt. “Searching for epistatic interactions in nuclear families using conditional linkage analysis.BMC Genet 6 Suppl 1, no. Suppl 1 (December 30, 2005): S148. https://doi.org/10.1186/1471-2156-6-S1-S148.
Shah SH, Schmidt MA, Mei H, Scott WK, Hauser ER, Schmidt S. Searching for epistatic interactions in nuclear families using conditional linkage analysis. BMC Genet. 2005 Dec 30;6 Suppl 1(Suppl 1):S148.
Shah, Svati H., et al. “Searching for epistatic interactions in nuclear families using conditional linkage analysis.BMC Genet, vol. 6 Suppl 1, no. Suppl 1, Dec. 2005, p. S148. Pubmed, doi:10.1186/1471-2156-6-S1-S148.
Shah SH, Schmidt MA, Mei H, Scott WK, Hauser ER, Schmidt S. Searching for epistatic interactions in nuclear families using conditional linkage analysis. BMC Genet. 2005 Dec 30;6 Suppl 1(Suppl 1):S148.
Journal cover image

Published In

BMC Genet

DOI

EISSN

1471-2156

Publication Date

December 30, 2005

Volume

6 Suppl 1

Issue

Suppl 1

Start / End Page

S148

Location

England

Related Subject Headings

  • Reproducibility of Results
  • Nuclear Family
  • Humans
  • Genetics & Heredity
  • Epistasis, Genetic
  • Disease
  • Chromosomes, Human
  • Chromosome Mapping
  • 3105 Genetics
  • 0604 Genetics