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Author Spotlight: Investigating the Role of Repetitive DNA Misregulation in Cancer Initiation and Immunotherapy Resistance
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NGSphy: phylogenomic simulation of next-generation sequencing data.

Merly Escalona1, Sara Rocha1, David Posada1,2,3

  • 1Department of Biochemistry, Genetics and Immunology.

Bioinformatics (Oxford, England)
|March 14, 2018
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Summary

NGSphy simulates next-generation sequencing (NGS) data for phylogenomic analysis, helping researchers understand how sequencing variables impact phylogenetic tree accuracy. This tool aids in optimizing complex computational pipelines for large-scale genomic datasets.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Evolutionary Biology

Background:

  • Next-generation sequencing (NGS) generates massive datasets for phylogenomic inference.
  • Phylogenomic analysis involves complex computational pipelines with critical methodological decisions.
  • Variables like coverage, assembly, mapping, and variant calling influence phylogenetic tree outcomes.

Purpose of the Study:

  • To introduce NGSphy, an open-source tool for simulating NGS data.
  • To assess the influence of sequencing variables on phylogenomic inference.
  • To provide a flexible simulation environment for various evolutionary scenarios.

Main Methods:

  • NGSphy simulates Illumina reads/read counts from haploid/diploid genomes.
  • It models sequencing coverage heterogeneity across species, individuals, and loci.
  • User-defined statistical distributions can sample parameter values for comprehensive simulations.

Main Results:

  • NGSphy facilitates the assessment of technical and methodological impacts on phylogenetic trees.
  • The tool supports simulations resembling real-world NGS experiments, including off-target loci.
  • It enables exploration of multiple evolutionary scenarios through customizable parameter sampling.

Conclusions:

  • NGSphy is a valuable open-source tool for researchers in phylogenomics.
  • It aids in understanding and mitigating biases in phylogenomic analyses from NGS data.
  • The tool supports the development of more robust and accurate phylogenetic inference methods.