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A Practical Guide to Phylogenetics for Nonexperts
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LDSO: a program to simulate pedigrees and molecular information under various evolutionary forces.

F Ytournel1, S Teyssèdre, D Roldan

  • 1INRA, Génétique Animale et Biologie Intégrative, Jouy-en-Josas, France. Florence.Ytournel@gmail.com

Journal of Animal Breeding and Genetics = Zeitschrift Fur Tierzuchtung Und Zuchtungsbiologie
|September 12, 2012
PubMed
Summary
This summary is machine-generated.

This study introduces ldso, a novel simulation program for genomic studies. It realistically models genetic forces and trait architecture to improve statistical methods and experimental designs.

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Area of Science:

  • Genomics
  • Statistical Genetics
  • Bioinformatics

Background:

  • Simulations are crucial for evaluating statistical methods and experimental designs in genomics.
  • Realistic and diverse simulations are essential for accurate genomic analyses.
  • Modeling forces like mutation, drift, selection, and pedigree structure is key for mapping studies.

Purpose of the Study:

  • To introduce ldso, a computer program for simulating genomic phenomena.
  • To enable realistic simulations of linkage and trait genetic architecture.
  • To facilitate the optimization of experimental designs and statistical methods in genomics.

Main Methods:

  • The ldso program simulates forces generating linkage (mutation, drift, population size changes, selection, pedigree structure).
  • It models mechanisms producing trait genetic architecture (additivity, dominance, epistasis).
  • The program can simulate genomic data within known pedigrees, reflecting recent population history and long-range linkage disequilibrium (LD).

Main Results:

  • ldso generates realistic and diverse genomic simulations.
  • Optional outputs include statistics on linkage disequilibrium (LD) structure and identity by descent.
  • The program aids in optimizing fine-mapping strategies by simulating genomic data in known pedigrees.

Conclusions:

  • ldso provides a powerful tool for creating realistic genomic simulations.
  • It supports the evaluation of statistical methods and the optimization of experimental designs.
  • The program enhances genomic data analysis, particularly for fine-mapping studies.