mbQTL:一个用于微生物数量性状基因座(QTL)估计的R/Bioconductor软件包。

IF 4.4 3区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS Bioinformatics Pub Date : 2023-09-02 DOI:10.1093/bioinformatics/btad565
Mercedeh Movassagh, Steven J Schiff, Joseph N Paulson
{"title":"mbQTL:一个用于微生物数量性状基因座(QTL)估计的R/Bioconductor软件包。","authors":"Mercedeh Movassagh,&nbsp;Steven J Schiff,&nbsp;Joseph N Paulson","doi":"10.1093/bioinformatics/btad565","DOIUrl":null,"url":null,"abstract":"<p><strong>Motivation: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Availability and implementation: </strong>mbQTL is available on bioconductor at https://bioconductor.org/packages/mbQTL/.</p>","PeriodicalId":8903,"journal":{"name":"Bioinformatics","volume":" ","pages":""},"PeriodicalIF":4.4000,"publicationDate":"2023-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10516520/pdf/","citationCount":"0","resultStr":"{\"title\":\"mbQTL: an R/Bioconductor package for microbial quantitative trait loci (QTL) estimation.\",\"authors\":\"Mercedeh Movassagh,&nbsp;Steven J Schiff,&nbsp;Joseph N Paulson\",\"doi\":\"10.1093/bioinformatics/btad565\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Motivation: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Availability and implementation: </strong>mbQTL is available on bioconductor at https://bioconductor.org/packages/mbQTL/.</p>\",\"PeriodicalId\":8903,\"journal\":{\"name\":\"Bioinformatics\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":4.4000,\"publicationDate\":\"2023-09-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10516520/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Bioinformatics\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1093/bioinformatics/btad565\",\"RegionNum\":3,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOCHEMICAL RESEARCH METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bioinformatics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1093/bioinformatics/btad565","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0

摘要

动机:近年来,随着旨在收集宿主突变谱和微生物组数据的大规模研究的开始,基因组学领域取得了重大进展。将健康和患病受试者的宿主基因突变谱与微生物丰度数据相结合,有望深入了解几个关键的研究问题,包括疾病的发展和进展,以及个体对治疗干预的反应。随着16s核糖体RNA(rRNA)测序和全基因组测序等测序方法的出现,越来越多的证据表明人类遗传学和微生物群落之间存在相互作用。与微生物丰度相关的数量性状基因座(mbQTL)是影响宿主内微生物种群丰度的遗传变异。结果:在这里,我们介绍了第一个整合16S核糖体RNA(rRNA)测序、单核苷酸变异(SNV)和单核苷酸多态性(SNP)数据的R包mbQTL。我们描述了用于鉴定微生物SNV对的各种统计方法、相关统计测量以及用于解释的绘图功能。可用性和实施:mbQTL可在生物导管上获得,网址为https://bioconductor.org/packages/mbQTL/.
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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 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/.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Bioinformatics
Bioinformatics 生物-生化研究方法
CiteScore
11.20
自引率
5.20%
发文量
753
审稿时长
2.1 months
期刊介绍: The leading journal in its field, Bioinformatics publishes the highest quality scientific papers and review articles of interest to academic and industrial researchers. Its main focus is on new developments in genome bioinformatics and computational biology. Two distinct sections within the journal - Discovery Notes and Application Notes- focus on shorter papers; the former reporting biologically interesting discoveries using computational methods, the latter exploring the applications used for experiments.
期刊最新文献
MEHunter: Transformer-based mobile element variant detection from long reads Metabolic syndrome may be more frequent in treatment-naive sarcoidosis patients. Coracle—A Machine Learning Framework to Identify Bacteria Associated with Continuous Variables CoSIA: an R Bioconductor package for CrOss Species Investigation and Analysis LncLocFormer: a Transformer-based deep learning model for multi-label lncRNA subcellular localization prediction by using localization-specific attention mechanism
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1