Detecting Higher Order Genomic Variant Interactions with Spectral Analysis
| Autor: | Rosa Garza, David Uminsky, Mario Banuelos, Sylvia Akueze Nwakanma, Lillian Gonzalez-Albino |
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| Rok vydání: | 2019 |
| Předmět: |
020206 networking & telecommunications
Single-nucleotide polymorphism 02 engineering and technology Computational biology Biology Phenotype symbols.namesake Order (biology) Bonferroni correction 0202 electrical engineering electronic engineering information engineering symbols Epistasis SNP 020201 artificial intelligence & image processing Spectral analysis Combinatorial explosion |
| Zdroj: | EUSIPCO |
| DOI: | 10.23919/eusipco.2019.8902725 |
| Popis: | Genomic variations among a species consisting of one nucleotide change are known as single nucleotide polymorphisms (SNPs). Often these mutations result in a change in phenotype, but detecting higher order interaction of multiple SNPs remains a challenging problem. Common approaches to find groups of interacting SNPs associated with a phenotypic response, a problem under the umbrella of epistasis, often suffers from a combinatorial explosion and require Bonferroni or similar corrections. In this work, we develop and apply a novel Fourier transformation on the symmetric group to uncover higher order interactions of SNPs associated with a quantitative phenotypic response. We present results for simulated data and then apply our method to previously published data to detect, for the first time using a signal processing approach, new and statistically significant higher order SNP interaction phenotypes related to muscle mice genomic variants. |
| Databáze: | OpenAIRE |
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