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Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...
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Updated: Feb 28, 2026

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Simplifying Systems Genetics with QTLretrievR: An R Package for Molecular QTL Identification.

Hannah B Dewey1,2, Selcan Aydin1, Samuel J Widmayer1

  • 1The Jackson Laboratory, 600 Main St, Bar Harbor, Maine, USA.

Biorxiv : the Preprint Server for Biology
|February 27, 2026
PubMed
Summary
This summary is machine-generated.

Systems genetics links complex traits to genetic variants but is computationally intensive. We developed QTLretrievR, an R package, to simplify and accelerate the analysis of molecular quantitative trait loci in diverse populations.

Keywords:
Diversity OutbredGenomicsQTL MappingR packageSystems GeneticseQTL

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Area of Science:

  • Genomics
  • Bioinformatics
  • Statistical Genetics

Background:

  • Systems genetics integrates molecular profiling and genetic mapping to link complex disease phenotypes to genetic variants.
  • Computational intensity and inaccessibility of current methods limit their application, especially with multiple tissues or numerous -omics phenotypes.

Purpose of the Study:

  • To develop an R package, QTLretrievR, that simplifies and streamlines the identification and downstream analysis of molecular quantitative trait loci (QTLs).
  • To improve computational efficiency and accessibility for systems genetics studies in genetically diverse populations.

Main Methods:

  • QTLretrievR is an R package building upon existing tools like r/qtl2 and r/intermediate.
  • Incorporates parallelization features for enhanced computational efficiency.
  • Includes functions for QTL peak detection, mediation analysis, and result visualization.

Main Results:

  • QTLretrievR successfully reproduces results from previous QTL studies.
  • Significantly reduces the time required for QTL detection and downstream analyses.
  • Provides visualization tools for downstream analysis results.

Conclusions:

  • QTLretrievR enhances the accessibility and efficiency of systems genetics analyses.
  • Facilitates the identification of genetic variants and regulatory effects underlying complex traits.
  • The R package is available for broader research community use.