SeqEM

SeqEM is a novel genotype-calling algorithm for next-generation sequencing that estimates parameters underlying the posterior probabilities in an adaptive way. Unlike other methods, it leverages information from the sample to estimate genotype probabilities and the nucleotide-read error rate. The algorithm applies the Expectation-Maximization algorithm to an appropriate likelihood for a sample of unrelated individuals with next-generation sequence data. SeqEM offers an improved, robust and flexible genotype-calling approach that can be widely applied in the next-generation sequencing studies.

Topic

Genotype and phenotype

Detail

  • Operation: Genetic variation analysis

  • Software interface: Command-line user interface

  • Language: -

  • License: -

  • Cost: Free

  • Version name: -

  • Credit: National Human Genome Research Institute, National Institute for Neurology and Stroke.

  • Input: -

  • Output: -

  • Contact: mschmidt@med.miami.edu

  • Collection: -

  • Maturity: -

Publications

  • SeqEM: an adaptive genotype-calling approach for next-generation sequencing studies.
  • Martin ER, et al. SeqEM: an adaptive genotype-calling approach for next-generation sequencing studies. SeqEM: an adaptive genotype-calling approach for next-generation sequencing studies. 2010; 26:2803-10. doi: 10.1093/bioinformatics/btq526
  • https://doi.org/10.1093/bioinformatics/btq526
  • PMID: 20861027
  • PMC: PMC2971572

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