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Numericware N: Numerator Relationship Matrix Calculator.

Bongsong Kim1, William D Beavis2, Jens Léon2

  • 1From the Department of Agronomy, Iowa State University, Ames, IA 50011 (Kim and Beavis); and INRES-Plant Breeding, University of Bonn, Katzenburgweg 5, 53115 Bonn, Germany (Léon). bkim@noble.org.

The Journal of Heredity
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The new generalized numerator relationship matrix (GNRM) algorithm and Numericware N software efficiently compute the numerator relationship matrix (NRM) using sparse plant pedigrees, significantly reducing computation time and enabling identical by state (IBS) matrix prediction.

Keywords:
Numericware Nidentical by descent coefficientidentical by state coefficientkinship coefficientnumerator relationship matrix

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Area of Science:

  • Quantitative genetics
  • Bioinformatics
  • Plant breeding

Background:

  • Calculating the numerator relationship matrix (NRM) is crucial for genetic analysis.
  • Traditional NRM algorithms require dense, bi-parental pedigree formats.
  • Plant pedigrees are often sparse, presenting computational challenges.

Purpose of the Study:

  • To introduce the generalized numerator relationship matrix (GNRM) algorithm.
  • To present Numericware N, a software tool for NRM calculation.
  • To enable NRM computation directly from sparse plant pedigrees.

Main Methods:

  • Development of the GNRM algorithm for sparse pedigree data.
  • Implementation of the GNRM algorithm in the Numericware N software.
  • Expansion of Numericware N for identical by state (IBS) matrix prediction.

Main Results:

  • The GNRM algorithm successfully computes NRM from sparse plant pedigrees.
  • Numericware N produces smaller NRM dimensions, leading to faster computation.
  • Numericware N facilitates the prediction of IBS matrices.

Conclusions:

  • The GNRM algorithm and Numericware N offer a more efficient approach to NRM calculation.
  • This method overcomes limitations of traditional NRM algorithms with sparse pedigrees.
  • Numericware N enhances genetic analysis capabilities through faster NRM and IBS matrix computation.