Identification of SNP barcode biomarkers for genes associated with facial emotion perception using particle swarm optimization algorithm.

Background Facial emotion perception (FEP) can affect social function. We previously reported that parts of five tested single-nucleotide polymorphisms (SNPs) in the MET and AKT1 genes may individually affect FEP performance. However, the effects of SNP-SNP interactions on FEP performance remain unc...

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Publicado en:Annals of General Psychiatry Vol. 13; no. 1; pp. 1 - 17
Autores principales: Li-Yeh Chuang, Hsien-Yuan Lane, Yu-Da Lin, Ming-Teng Lin, Cheng-Hong Yang, Hsueh-Wei Chang
Formato: algorithm equations & formulas research tables/charts Journal Article
Publicado: BioMed Central 2014
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 2014
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      pub: BioMed Central
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        10.1186/1744-859X-13-15
        96398891
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        atl: Identification of SNP barcode biomarkers for genes associated with facial emotion perception using particle swarm optimization algorithm.
      aug:
        au:
          Li-Yeh Chuang
          Hsien-Yuan Lane
          Yu-Da Lin
          Ming-Teng Lin
          Cheng-Hong Yang
          Hsueh-Wei Chang
        affil: Department of Chemical Engineering & Institute of Biotechnology and Chemical Engineering, I-Shou University, Kaohsiung 84001, Taiwan
      sug:
        subj:
          Polymorphism, Single Nucleotide
          Facial Expression
          Social Behavior Disorders Familial and Genetic
          Cognition
          Particle Swarm Optimization Utilization
          Human
          Taiwan
          Data Analysis Software
          Confidence Intervals
          Odds Ratio
          Male
          Female
          Clinical Assessment Tools
          Genotype
          Male
          Female
      ab: Background Facial emotion perception (FEP) can affect social function. We previously reported that parts of five tested single-nucleotide polymorphisms (SNPs) in the MET and AKT1 genes may individually affect FEP performance. However, the effects of SNP-SNP interactions on FEP performance remain unclear. Methods This study compared patients with high and low FEP performances (n = 89 and 93, respectively). A particle swarm optimization (PSO) algorithm was used to identify the best SNP barcodes (i.e., the SNP combinations and genotypes that revealed the largest differences between the high and low FEP groups). Results The analyses of individual SNPs showed no significant differences between the high and low FEP groups. However, comparisons of multiple SNP-SNP interactions involving different combinations of two to five SNPs showed that the best PSO-generated SNP barcodes were significantly associated with high FEP score. The analyses of the joint effects of the best SNP barcodes for two to five interacting SNPs also showed that the best SNP barcodes had significantly higher odds ratios (2.119 to 3.138; P < 0.05) compared to other SNP barcodes. In conclusion, the proposed PSO algorithm effectively identifies the best SNP barcodes that have the strongest associations with FEP performance. Conclusions This study also proposes a computational methodology for analyzing complex SNP-SNP interactions in social cognition domains such as recognition of facial emotion.
      pubtype: Academic Journal
      doctype:
        algorithm
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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