Monte Carlo simulations on marker grouping and ordering

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik
J WuC Watson

Abstract

Four global algorithms, maximum likelihood (ML), sum of adjacent LOD score (SALOD), sum of adjacent recombinant fractions (SARF) and product of adjacent recombinant fraction (PARF), and one approximation algorithm, seriation (SER), were used to compare the marker ordering efficiencies for correctly given linkage groups based on doubled haploid (DH) populations. The Monte Carlo simulation results indicated the marker ordering powers for the five methods were almost identical. High correlation coefficients were greater than 0.99 between grouping power and ordering power, indicating that all these methods for marker ordering were reliable. Therefore, the main problem for linkage analysis was how to improve the grouping power. Since the SER approach provided the advantage of speed without losing ordering power, this approach was used for detailed simulations. For more generality, multiple linkage groups were employed, and population size, linkage cutoff criterion, marker spacing pattern (even or uneven), and marker spacing distance (close or loose) were considered for obtaining acceptable grouping powers. Simulation results indicated that the grouping power was related to population size, marker spacing distance, and cutoff criteri...Continue Reading

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Citations

Jun 29, 2004·TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik·Xin-Sheng HuKermit M Ritland
May 26, 2011·TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik·Jixiang WuXiang-Yang Lou
Aug 31, 2010·Molecular Genetics and Genomics : MGG·Haobing LiRené E Vaillancourt
Jul 30, 2009·Heredity·M MollinariA A F Garcia
Nov 27, 2004·Bioinformatics·Charles F Crane, Yan M Crane
Jan 24, 2007·Bioinformatics·T FarautT Schiex
Feb 9, 2017·TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik·Sameer KhanalAndrew H Paterson

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