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

MOTIVATION: In recent years, significant strides have been made in the field of genomics, with the commencement of large-scale studies aimed at collecting host mutational profiles and microbiome data. The amalgamation of host gene mutational profiles in both healthy and diseased subjects with microb...

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Autores principales: Movassagh, Mercedeh, Schiff, Steven J, Paulson, Joseph N
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10516520/
https://www.ncbi.nlm.nih.gov/pubmed/37707523
http://dx.doi.org/10.1093/bioinformatics/btad565
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author Movassagh, Mercedeh
Schiff, Steven J
Paulson, Joseph N
author_facet Movassagh, Mercedeh
Schiff, Steven J
Paulson, Joseph N
author_sort Movassagh, Mercedeh
collection PubMed
description MOTIVATION: In recent years, significant strides have been made in the field of genomics, with the commencement of large-scale studies aimed at collecting host mutational profiles and microbiome data. The amalgamation of host gene mutational profiles in both healthy and diseased subjects with microbial abundance data holds immense promise in providing insights into several crucial research questions, including the development and progression of diseases, as well as individual responses to therapeutic interventions. With the advent of sequencing methods such as 16s ribosomal RNA (rRNA) sequencing and whole genome sequencing, there is increasing evidence of interplay of human genetics and microbial communities. Quantitative trait loci associated with microbial abundance (mbQTLs), are genetic variants that influence the abundance of microbial populations within the host. RESULTS: Here, we introduce mbQTL, the first R package integrating 16S ribosomal RNA (rRNA) sequencing and single-nucleotide variation (SNV) and single-nucleotide polymorphism (SNP) data. We describe various statistical methods implemented for the identification of microbe–SNV pairs, relevant statistical measures, and plot functionality for interpretation. AVAILABILITY AND IMPLEMENTATION: mbQTL is available on bioconductor at https://bioconductor.org/packages/mbQTL/.
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spelling pubmed-105165202023-09-23 mbQTL: an R/Bioconductor package for microbial quantitative trait loci (QTL) estimation Movassagh, Mercedeh Schiff, Steven J Paulson, Joseph N Bioinformatics Applications Note MOTIVATION: In recent years, significant strides have been made in the field of genomics, with the commencement of large-scale studies aimed at collecting host mutational profiles and microbiome data. The amalgamation of host gene mutational profiles in both healthy and diseased subjects with microbial abundance data holds immense promise in providing insights into several crucial research questions, including the development and progression of diseases, as well as individual responses to therapeutic interventions. With the advent of sequencing methods such as 16s ribosomal RNA (rRNA) sequencing and whole genome sequencing, there is increasing evidence of interplay of human genetics and microbial communities. Quantitative trait loci associated with microbial abundance (mbQTLs), are genetic variants that influence the abundance of microbial populations within the host. RESULTS: Here, we introduce mbQTL, the first R package integrating 16S ribosomal RNA (rRNA) sequencing and single-nucleotide variation (SNV) and single-nucleotide polymorphism (SNP) data. We describe various statistical methods implemented for the identification of microbe–SNV pairs, relevant statistical measures, and plot functionality for interpretation. AVAILABILITY AND IMPLEMENTATION: mbQTL is available on bioconductor at https://bioconductor.org/packages/mbQTL/. Oxford University Press 2023-09-14 /pmc/articles/PMC10516520/ /pubmed/37707523 http://dx.doi.org/10.1093/bioinformatics/btad565 Text en © The Author(s) 2023. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Note
Movassagh, Mercedeh
Schiff, Steven J
Paulson, Joseph N
mbQTL: an R/Bioconductor package for microbial quantitative trait loci (QTL) estimation
title mbQTL: an R/Bioconductor package for microbial quantitative trait loci (QTL) estimation
title_full mbQTL: an R/Bioconductor package for microbial quantitative trait loci (QTL) estimation
title_fullStr mbQTL: an R/Bioconductor package for microbial quantitative trait loci (QTL) estimation
title_full_unstemmed mbQTL: an R/Bioconductor package for microbial quantitative trait loci (QTL) estimation
title_short mbQTL: an R/Bioconductor package for microbial quantitative trait loci (QTL) estimation
title_sort mbqtl: an r/bioconductor package for microbial quantitative trait loci (qtl) estimation
topic Applications Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10516520/
https://www.ncbi.nlm.nih.gov/pubmed/37707523
http://dx.doi.org/10.1093/bioinformatics/btad565
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