title: Auto-validation of fluorescent primer extension genotyping assay using signal clustering and neural networks.
abstract: BACKGROUND
  SNP genotyping typically incorporates a review step to ensure that the genotype calls for a particular SNP are correct. For high-throughput genotyping, such as that provided by the GenomeLab SNPstream instrument from Beckman Coulter, Inc., the manual review used for low-volume genotyping becomes a major bottleneck. The work reported here describes the application of a neural network to automate the review of results.
  
  
  RESULTS
  We describe an approach to reviewing the quality of primer extension 2-color fluorescent reactions by clustering optical signals obtained from multiple samples and a single reaction set-up. The method evaluates the quality of the signal clusters from the genotyping results. We developed 64 scores to measure the geometry and position of the signal clusters. The expected signal distribution was represented by a distribution of a 64-component parametric vector obtained by training the two-layer neural network onto a set of 10,968 manually reviewed 2D plots containing the signal clusters.
  
  
  CONCLUSIONS
  The neural network approach described in this paper may be used with results from the GenomeLab SNPstream instrument for high-throughput SNP genotyping. The overall correlation with manual revision was 0.844. The approach can be applied to a quality review of results from other high-throughput fluorescent-based biochemical assays in a high-throughput mode.
authors.affiliation: Center for Pharmacogenomics and Complex Disease Research, Newark, NJ 07101, USA. austin.huang@umdnj.edu
authors.forename: Ching Yu Austin
authors.initials: CY
authors.lastname: Huang
authors.forename: Joel
authors.initials: J
authors.lastname: Studebaker
authors.forename: Anton
authors.initials: A
authors.lastname: Yuryev
authors.forename: Jianping
authors.initials: J
authors.lastname: Huang
authors.forename: Kathryn E
authors.initials: KE
authors.lastname: Scott
authors.forename: Jennifer
authors.initials: J
authors.lastname: Kuebler
authors.forename: Shobha
authors.initials: S
authors.lastname: Varde
authors.forename: Steven
authors.initials: S
authors.lastname: Alfisi
authors.forename: Craig A
authors.initials: CA
authors.lastname: Gelfand
authors.forename: Mark
authors.initials: M
authors.lastname: Pohl
authors.forename: Michael T
authors.initials: MT
authors.lastname: Boyce-Jacino
mesh_terms: D001185:Artificial Intelligence; D001331:Automation; D016000:Cluster Analysis; D017931:DNA Primers / Q000235:genetics* / Q000378:metabolism*; D005456:Fluorescent Dyes / Q000378:metabolism*; D005838:Genotype; D006801:Humans; D016133:Polymerase Chain Reaction / Q000379:methods / Q000706:statistics & numerical data; D020641:Polymorphism, Single Nucleotide / Q000235:genetics; D011237:Predictive Value of Tests; D011786:Quality Control; D015203:Reproducibility of Results; D012984:Software / Q000706:statistics & numerical data
chemical_list: D017931:DNA Primers; D005456:Fluorescent Dyes