The challenge of detecting epistasis (G x G interactions): Genetic analysis workshop 16

Ping An; Odity Mukherjee; Pritam Chanda; Li Yao; Corinne D. Engelman; Chien Hsun Huang; Tian Zheng; Ilija P. Kovac; Marie Pierre Dubé; Xueying Liang; Jia Li; Mariza De Andrade; Robert Culverhouse; Doerthe Malzahn; Alisa K. Manning; Geraldine M. Clarke; Jeesun Jung; Michael A. Province

doi:10.1002/gepi.20474

The challenge of detecting epistasis (G x G interactions): Genetic analysis workshop 16

Ping An, Odity Mukherjee, Pritam Chanda, Li Yao, Corinne D. Engelman, Chien Hsun Huang, Tian Zheng, Ilija P. Kovac, Marie Pierre Dubé, Xueying Liang, Jia Li, Mariza De Andrade, Robert Culverhouse, Doerthe Malzahn, Alisa K. Manning, Geraldine M. Clarke, Jeesun Jung, Michael A. Province

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Abstract

Interest is increasing in epistasis as a possible source of the unexplained variance missed by genome-wide association studies. The Genetic Analysis Workshop 16 Group 9 participants evaluated a wide variety of classical and novel analytical methods for detecting epistasis, in both the statistical and machine learning paradigms, applied to both real and simulated data. Because the magnitude of epistasis is clearly relative to scale of penetrance, and therefore to some extent, to the choice of model framework, it is not surprising that strong interactions under one model might be minimized or even disappear entirely under a different modeling framework.

Original language	English
Pages (from-to)	S58-S67
Journal	Genetic Epidemiology
Volume	33
Issue number	SUPPL. 1
DOIs	https://doi.org/10.1002/gepi.20474
State	Published - 2009

Keywords

Generalized linear model
Machine learning methods

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An, P., Mukherjee, O., Chanda, P., Yao, L., Engelman, C. D., Huang, C. H., Zheng, T., Kovac, I. P., Dubé, M. P., Liang, X., Li, J., De Andrade, M., Culverhouse, R., Malzahn, D., Manning, A. K., Clarke, G. M., Jung, J., & Province, M. A. (2009). The challenge of detecting epistasis (G x G interactions): Genetic analysis workshop 16. Genetic Epidemiology, 33(SUPPL. 1), S58-S67. https://doi.org/10.1002/gepi.20474

@article{a235e2823ed1461995dd752ddfd08aa6,

title = "The challenge of detecting epistasis (G x G interactions): Genetic analysis workshop 16",

abstract = "Interest is increasing in epistasis as a possible source of the unexplained variance missed by genome-wide association studies. The Genetic Analysis Workshop 16 Group 9 participants evaluated a wide variety of classical and novel analytical methods for detecting epistasis, in both the statistical and machine learning paradigms, applied to both real and simulated data. Because the magnitude of epistasis is clearly relative to scale of penetrance, and therefore to some extent, to the choice of model framework, it is not surprising that strong interactions under one model might be minimized or even disappear entirely under a different modeling framework.",

keywords = "Generalized linear model, Machine learning methods",

author = "Ping An and Odity Mukherjee and Pritam Chanda and Li Yao and Engelman, {Corinne D.} and Huang, {Chien Hsun} and Tian Zheng and Kovac, {Ilija P.} and Dub{\'e}, {Marie Pierre} and Xueying Liang and Jia Li and {De Andrade}, Mariza and Robert Culverhouse and Doerthe Malzahn and Manning, {Alisa K.} and Clarke, {Geraldine M.} and Jeesun Jung and Province, {Michael A.}",

year = "2009",

doi = "10.1002/gepi.20474",

language = "English",

volume = "33",

pages = "S58--S67",

journal = "Genetic Epidemiology",

issn = "0741-0395",

number = "SUPPL. 1",

}

An, P, Mukherjee, O, Chanda, P, Yao, L, Engelman, CD, Huang, CH, Zheng, T, Kovac, IP, Dubé, MP, Liang, X, Li, J, De Andrade, M, Culverhouse, R, Malzahn, D, Manning, AK, Clarke, GM, Jung, J & Province, MA 2009, 'The challenge of detecting epistasis (G x G interactions): Genetic analysis workshop 16', Genetic Epidemiology, vol. 33, no. SUPPL. 1, pp. S58-S67. https://doi.org/10.1002/gepi.20474

TY - JOUR

T1 - The challenge of detecting epistasis (G x G interactions)

T2 - Genetic analysis workshop 16

AU - An, Ping

AU - Mukherjee, Odity

AU - Chanda, Pritam

AU - Yao, Li

AU - Engelman, Corinne D.

AU - Huang, Chien Hsun

AU - Zheng, Tian

AU - Kovac, Ilija P.

AU - Dubé, Marie Pierre

AU - Liang, Xueying

AU - Li, Jia

AU - De Andrade, Mariza

AU - Culverhouse, Robert

AU - Malzahn, Doerthe

AU - Manning, Alisa K.

AU - Clarke, Geraldine M.

AU - Jung, Jeesun

AU - Province, Michael A.

PY - 2009

Y1 - 2009

N2 - Interest is increasing in epistasis as a possible source of the unexplained variance missed by genome-wide association studies. The Genetic Analysis Workshop 16 Group 9 participants evaluated a wide variety of classical and novel analytical methods for detecting epistasis, in both the statistical and machine learning paradigms, applied to both real and simulated data. Because the magnitude of epistasis is clearly relative to scale of penetrance, and therefore to some extent, to the choice of model framework, it is not surprising that strong interactions under one model might be minimized or even disappear entirely under a different modeling framework.

AB - Interest is increasing in epistasis as a possible source of the unexplained variance missed by genome-wide association studies. The Genetic Analysis Workshop 16 Group 9 participants evaluated a wide variety of classical and novel analytical methods for detecting epistasis, in both the statistical and machine learning paradigms, applied to both real and simulated data. Because the magnitude of epistasis is clearly relative to scale of penetrance, and therefore to some extent, to the choice of model framework, it is not surprising that strong interactions under one model might be minimized or even disappear entirely under a different modeling framework.

KW - Generalized linear model

KW - Machine learning methods

UR - http://www.scopus.com/inward/record.url?scp=71249091726&partnerID=8YFLogxK

U2 - 10.1002/gepi.20474

DO - 10.1002/gepi.20474

M3 - Article

C2 - 19924703

AN - SCOPUS:71249091726

SN - 0741-0395

VL - 33

SP - S58-S67

JO - Genetic Epidemiology

JF - Genetic Epidemiology

IS - SUPPL. 1

ER -

The challenge of detecting epistasis (G x G interactions): Genetic analysis workshop 16

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Keywords

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