Journal Article

DKFZ-2019-00190

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png AA9int: SNP interaction pattern search using non-hierarchical additive model set.

Lin, H.-Y. ; Huang, P.-Y. ; Chen, D.-T. ; Tung, H.-Y. ; Sellers, T. A. ; Pow-Sang, J. M. ; Eeles, R. ; Easton, D. ; Kote-Jarai, Z. ; Amin Al Olama, A. ; Benlloch, S. ; Muir, K. ; Giles, G. G. ; Wiklund, F. ; Gronberg, H. ; Haiman, C. A. ; Schleutker, J. ; Nordestgaard, B. G. ; Travis, R. C. ; Hamdy, F. ; Neal, D. E. ; Pashayan, N. ; Khaw, K.-T. ; Stanford, J. L. ; Blot, W. J. ; Thibodeau, S. N. ; Maier, C. ; Kibel, A. S. ; Cybulski, C. ; Cannon-Albright, L. ; Brenner, H.DKFZ* ; Kaneva, R. ; Batra, J. ; Teixeira, M. R. ; Pandha, H. ; Lu, Y.-J. ; Consortium, P. (Collaboration Author) ; Park, J. Y.

2018
Oxford Univ. Press Oxford

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Please use a persistent id in citations: doi:10.1093/bioinformatics/bty461

Abstract: The use of single nucleotide polymorphism (SNP) interactions to predict complex diseases is getting more attention during the past decade, but related statistical methods are still immature. We previously proposed the SNP Interaction Pattern Identifier (SIPI) approach to evaluate 45 SNP interaction patterns/patterns. SIPI is statistically powerful but suffers from a large computation burden. For large-scale studies, it is necessary to use a powerful and computation-efficient method. The objective of this study is to develop an evidence-based mini-version of SIPI as the screening tool or solitary use and to evaluate the impact of inheritance mode and model structure on detecting SNP-SNP interactions.We tested two candidate approaches: the Five-Full and AA9int method. The Five-Full approach is composed of the five full interaction models considering three inheritance modes (additive, dominant and recessive). The AA9int approach is composed of nine interaction models by considering non-hierarchical model structure and the additive mode. Our simulation results show that AA9int has similar statistical power compared to SIPI and is superior to the Five-Full approach, and the impact of the non-hierarchical model structure is greater than that of the inheritance mode in detecting SNP-SNP interactions. In summary, it is recommended that AA9int is a powerful tool to be used either alone or as the screening stage of a two-stage approach (AA9int+SIPI) for detecting SNP-SNP interactions in large-scale studies.The AA9int and parAA9int functions (standard and parallel computing version) are added in the SIPI R package, which is freely available at https://linhuiyi.github.io/LinHY_Software/.Supplementary data are available at Bioinformatics online.

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Contributing Institute(s):

1. C070 Klinische Epidemiologie und Alternf. (C070)
2. Präventive Onkologie (G110)
3. DKTK Heidelberg (L101)

Research Program(s):

1. 313 - Cancer risk factors and prevention (POF3-313) (POF3-313)

Appears in the scientific report 2018

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Database coverage:
; BIOSIS Previews ; Clarivate Analytics Master Journal List ; Current Contents - Life Sciences ; Ebsco Academic Search ; IF >= 5 ; JCR ; NCBI Molecular Biology Database ; Nationallizenz ; PubMed Central ; SCOPUS ; Science Citation Index ; Science Citation Index Expanded ; Web of Science Core Collection

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