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mbQTL: an R/Bioconductor package for microbial quantitative trait loci (QTL) estimation.

Mercedeh Movassagh1,2, Steven J Schiff2, Joseph N Paulson3

  • 1Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, United States.

Bioinformatics (Oxford, England)
|September 14, 2023
PubMed
Summary

The mbQTL R package links host genetic variants to microbial abundance using 16S rRNA and SNV/SNP data. This tool aids in understanding the human microbiome and its role in health and disease.

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Area of Science:

  • Genomics
  • Microbiome research
  • Bioinformatics

Background:

  • Large-scale studies collect host mutational profiles and microbiome data.
  • Integrating host genetics and microbial data offers insights into disease development and treatment responses.
  • 16S ribosomal RNA (rRNA) sequencing and whole genome sequencing reveal the interplay between human genetics and microbial communities.

Purpose of the Study:

  • Introduce mbQTL, the first R package for integrating 16S rRNA sequencing with single-nucleotide variation (SNV) and single-nucleotide polymorphism (SNP) data.
  • Facilitate the identification of microbe-SNV pairs and their association with microbial abundance.

Main Methods:

  • The mbQTL package implements statistical methods for identifying microbe-SNV associations.
  • It includes relevant statistical measures and plotting functionalities for data interpretation.

Main Results:

  • The study introduces the mbQTL R package, a novel tool for analyzing host genetic variation and microbial communities.
  • The package integrates diverse data types, including 16S rRNA sequencing and SNV/SNP data.

Conclusions:

  • The mbQTL package provides a comprehensive framework for exploring microbe-quantitative trait loci (mbQTLs).
  • This tool is expected to advance research into the genetic underpinnings of the human microbiome and its impact on health and disease.