ArticleBioinformatics (Oxford, England)2017
SNP interaction pattern identifier (SIPI): an intensive search for SNP-SNP interaction patterns.
Article in Bioinformatics (Oxford, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 17 citations in OpenAlex.
- Polygenic risk score with KLK3 SNP-SNP interaction pairs for predicting prostate cancer aggressiveness.Communications medicine · 2026Article
- Association of DNA methyltransferase polymorphisms with breast cancer: a nested case‒control study of the Arkansas Rural Community Health study.BMC cancer · 2026Article
- Natural variations inProceedings of the National Academy of Sciences of the United States of America · 2025Article
- LINC00461 SNPs rs933647 and rs201864123 modify the risk of adenoid hypertrophy susceptibility for children in South China.Frontiers in genetics · 2025Article
- Cluster effect for SNP-SNP interaction pairs for predicting complex traits.Scientific reports · 2024Article
- The role of longevity-related genetic variant interactions as predictors of survival after 85 years of age.Mechanisms of ageing and development · 2024Article
- Identification of environment-insensitive genes for oil content by combination of transcriptome and genome-wide association analysis in rapeseed.Biotechnology for biofuels and bioproducts · 2024Article
- Article
- SNPxE: SNP-environment interaction pattern identifier.BMC bioinformatics · 2021Article
- KLK3 SNP-SNP interactions for prediction of prostate cancer aggressiveness.Scientific reports · 2021Article
- Roles of interacting stress-related genes in lifespan regulation: insights for translating experimental findings to humans.Journal of translational genetics and genomics · 2021Article
- Interactions ofCancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2019Article
- Post-GWAS in prostate cancer: from genetic association to biological contribution.Nature reviews. Cancer · 2019Review
- AA9int: SNP interaction pattern search using non-hierarchical additive model set.Bioinformatics (Oxford, England) · 2018Article
Corrections and comments
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Authors and funding
42 authors at 20 institutions in 11 countries.
Funding
Abstract
Motivation: Testing SNP-SNP interactions is considered as a key for overcoming bottlenecks of genetic association studies. However, related statistical methods for testing SNP-SNP interactions are underdeveloped. Results: We propose the SNP Interaction Pattern Identifier (SIPI), which tests 45 biologically meaningful interaction patterns for a binary outcome. SIPI takes non-hierarchical models, inheritance modes and mode coding direction into consideration. The simulation results show that SIPI has higher power than MDR (Multifactor Dimensionality Reduction), AA_Full, Geno_Full (full interaction model with additive or genotypic mode) and SNPassoc in detecting interactions. Applying SIPI to the prostate cancer PRACTICAL consortium data with approximately 21 000 patients, the four SNP pairs in EGFR-EGFR , EGFR-MMP16 and EGFR-CSF1 were found to be associated with prostate cancer aggressiveness with the exact or similar pattern in the discovery and validation sets. A similar match for external validation of SNP-SNP interaction studies is suggested. We demonstrated that SIPI not only searches for more meaningful interaction patterns but can also overcome the unstable nature of interaction patterns. Availability and Implementation: The SIPI software is freely available at http://publichealth.lsuhsc.edu/LinSoftware/ . Contact: hlin1@lsuhsc.edu. Supplementary information: Supplementary data are available at Bioinformatics online.
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