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FAM-MDR: a flexible family-based multifactor dimensionality reduction technique to detect epistasis using related individuals

(2010) PLOS ONE. 5(4).
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Abstract
We propose a novel multifactor dimensionality reduction method for epistasis detection in small or extended pedigrees, FAM-MDR. It combines features of the Genome-wide Rapid Association using Mixed Model And Regression approach (GRAMMAR) with Model-Based MDR (MB-MDR). We focus on continuous traits, although the method is general and can be used for outcomes of any type, including binary and censored traits. When comparing FAM-MDR with Pedigree-based Generalized MDR (PGMDR), which is a generalization of Multifactor Dimensionality Reduction (MDR) to continuous traits and related individuals, FAM-MDR was found to outperform PGMDR in terms of power, in most of the considered simulated scenarios. Additional simulations revealed that PGMDR does not appropriately deal with multiple testing and consequently gives rise to overly optimistic results. FAM-MDR adequately deals with multiple testing in epistasis screens and is in contrast rather conservative, by construction. Furthermore, simulations show that correcting for lower order (main) effects is of utmost importance when claiming epistasis. As Type 2 Diabetes Mellitus (T2DM) is a complex phenotype likely influenced by gene-gene interactions, we applied FAM-MDR to examine data on glucose area-under-the-curve (GAUC), an endophenotype of T2DM for which multiple independent genetic associations have been observed, in the Amish Family Diabetes Study (AFDS). This application reveals that FAM-MDR makes more efficient use of the available data than PGMDR and can deal with multi-generational pedigrees more easily. In conclusion, we have validated FAM-MDR and compared it to PGMDR, the current state-of-the-art MDR method for family data, using both simulations and a practical dataset. FAM-MDR is found to outperform PGMDR in that it handles the multiple testing issue more correctly, has increased power, and efficiently uses all available information.
Keywords
OLD ORDER AMISH, GENOME-WIDE ASSOCIATION, GENE-ENVIRONMENT INTERACTIONS, BETA(3)-ADRENERGIC RECEPTOR GENE, QUANTITATIVE TRAIT LOCI, DROSOPHILA-MERCATORUM, ECOLOGICAL GENETICS, INSULIN-RESISTANCE, ABNORMAL-ABDOMEN, HUMAN-DISEASES

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Citation

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Chicago
Cattaert, Tom, Victor Urrea, Adam C Naj, Lizzy De Lobel, Vanessa De Wit, Mao Fu, Jestinah M Mahachie John, et al. 2010. “FAM-MDR: a Flexible Family-based Multifactor Dimensionality Reduction Technique to Detect Epistasis Using Related Individuals.” Plos One 5 (4).
APA
Cattaert, Tom, Urrea, V., Naj, A. C., De Lobel, L., De Wit, V., Fu, M., John, J. M. M., et al. (2010). FAM-MDR: a flexible family-based multifactor dimensionality reduction technique to detect epistasis using related individuals. PLOS ONE, 5(4).
Vancouver
1.
Cattaert T, Urrea V, Naj AC, De Lobel L, De Wit V, Fu M, et al. FAM-MDR: a flexible family-based multifactor dimensionality reduction technique to detect epistasis using related individuals. PLOS ONE. 2010;5(4).
MLA
Cattaert, Tom, Victor Urrea, Adam C Naj, et al. “FAM-MDR: a Flexible Family-based Multifactor Dimensionality Reduction Technique to Detect Epistasis Using Related Individuals.” PLOS ONE 5.4 (2010): n. pag. Print.
@article{946644,
  abstract     = {We propose a novel multifactor dimensionality reduction method for epistasis detection in small or extended pedigrees, FAM-MDR. It combines features of the Genome-wide Rapid Association using Mixed Model And Regression approach (GRAMMAR) with Model-Based MDR (MB-MDR). We focus on continuous traits, although the method is general and can be used for outcomes of any type, including binary and censored traits. When comparing FAM-MDR with Pedigree-based Generalized MDR (PGMDR), which is a generalization of Multifactor Dimensionality Reduction (MDR) to continuous traits and related individuals, FAM-MDR was found to outperform PGMDR in terms of power, in most of the considered simulated scenarios. Additional simulations revealed that PGMDR does not appropriately deal with multiple testing and consequently gives rise to overly optimistic results. FAM-MDR adequately deals with multiple testing in epistasis screens and is in contrast rather conservative, by construction. Furthermore, simulations show that correcting for lower order (main) effects is of utmost importance when claiming epistasis. As Type 2 Diabetes Mellitus (T2DM) is a complex phenotype likely influenced by gene-gene interactions, we applied FAM-MDR to examine data on glucose area-under-the-curve (GAUC), an endophenotype of T2DM for which multiple independent genetic associations have been observed, in the Amish Family Diabetes Study (AFDS). This application reveals that FAM-MDR makes more efficient use of the available data than PGMDR and can deal with multi-generational pedigrees more easily. In conclusion, we have validated FAM-MDR and compared it to PGMDR, the current state-of-the-art MDR method for family data, using both simulations and a practical dataset. FAM-MDR is found to outperform PGMDR in that it handles the multiple testing issue more correctly, has increased power, and efficiently uses all available information.},
  author       = {Cattaert, Tom and Urrea, Victor and Naj, Adam C and De Lobel, Lizzy and De Wit, Vanessa and Fu, Mao and John, Jestinah M Mahachie and Shen, HaiQing and Calle, M Luz and Ritchie, Marylyn D and Edwards, Todd L and Van Steen, Kristel},
  issn         = {1932-6203},
  journal      = {PLOS ONE},
  keyword      = {OLD ORDER AMISH,GENOME-WIDE ASSOCIATION,GENE-ENVIRONMENT INTERACTIONS,BETA(3)-ADRENERGIC RECEPTOR GENE,QUANTITATIVE TRAIT LOCI,DROSOPHILA-MERCATORUM,ECOLOGICAL GENETICS,INSULIN-RESISTANCE,ABNORMAL-ABDOMEN,HUMAN-DISEASES},
  language     = {eng},
  number       = {4},
  title        = {FAM-MDR: a flexible family-based multifactor dimensionality reduction technique to detect epistasis using related individuals},
  url          = {http://dx.doi.org/10.1371/journal.pone.0010304},
  volume       = {5},
  year         = {2010},
}

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