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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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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/. |
format | Online Article Text |
id | pubmed-10516520 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
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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