@InProceedings{8902725,
  author = {D. Uminsky and M. Banuelos and L. González-Albino and R. Garza and S. A. Nwakanma},
  booktitle = {2019 27th European Signal Processing Conference (EUSIPCO)},
  title = {Detecting Higher Order Genomic Variant Interactions with Spectral Analysis},
  year = {2019},
  pages = {1-5},
  abstract = {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.},
  keywords = {bioinformatics;cellular biophysics;genetics;genomics;molecular biophysics;polymorphism;spectral analysis;statistical analysis;higher order genomic variant interactions;spectral analysis;genomic variations;nucleotide change;single nucleotide polymorphisms;phenotype;higher order interaction;multiple SNPs;interacting SNPs;quantitative phenotypic response;statistically significant higher order SNP interaction phenotypes;muscle mice genomic variants;Fourier transforms;Signal processing;Genomics;Bioinformatics;Mice;Europe;Spectral analysis;Fourier transform;algebraic signal processing;epistasis;genomic variation},
  doi = {10.23919/EUSIPCO.2019.8902725},
  issn = {2076-1465},
  month = {Sep.},
  url = {https://www.eurasip.org/proceedings/eusipco/eusipco2019/proceedings/papers/1570534029.pdf},
}

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A."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"firstnames":["D."],"propositions":[],"lastnames":["Uminsky"],"suffixes":[]},{"firstnames":["M."],"propositions":[],"lastnames":["Banuelos"],"suffixes":[]},{"firstnames":["L."],"propositions":[],"lastnames":["González-Albino"],"suffixes":[]},{"firstnames":["R."],"propositions":[],"lastnames":["Garza"],"suffixes":[]},{"firstnames":["S.","A."],"propositions":[],"lastnames":["Nwakanma"],"suffixes":[]}],"booktitle":"2019 27th European Signal Processing Conference (EUSIPCO)","title":"Detecting Higher Order Genomic Variant Interactions with Spectral Analysis","year":"2019","pages":"1-5","abstract":"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. 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Uminsky and M. Banuelos and L. González-Albino and R. Garza and S. A. Nwakanma},\n booktitle = {2019 27th European Signal Processing Conference (EUSIPCO)},\n title = {Detecting Higher Order Genomic Variant Interactions with Spectral Analysis},\n year = {2019},\n pages = {1-5},\n abstract = {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. 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