AutoMethyc:用于大规模并行测序数据的自动甲基化分析。

IF 7.7 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Fernando Ambriz-Barrera, Miguel Ruiz-De La Cruz, Héctor Martínez-Gregorio, Clara E Díaz-Velásquez, Aldo H De La Cruz-Montoya, Felipe Vaca-Paniagua
{"title":"AutoMethyc:用于大规模并行测序数据的自动甲基化分析。","authors":"Fernando Ambriz-Barrera, Miguel Ruiz-De La Cruz, Héctor Martínez-Gregorio, Clara E Díaz-Velásquez, Aldo H De La Cruz-Montoya, Felipe Vaca-Paniagua","doi":"10.1093/bib/bbaf416","DOIUrl":null,"url":null,"abstract":"<p><strong>Motivation: </strong>Bisulfite sequencing (BS-Seq) enables a comprehensive and detailed analysis of DNA methylation patterns at single-nucleotide resolution. While methylation differences can contribute to various diseases, their sincronous occurrence at distinct loci complicates understanding. Therefore, advanced tools are essential to facilitate the identification and analysis of methylation programs and patterns.</p><p><strong>Results: </strong>AutoMethyc provides a comparative approach by integrating different algorithms coordinated and optimized for use on desktop computers and servers. The workflow evaluates the methylation status from different perspectives, facilitating interpretation in an interactive HTML report, incorporating new co-methylation analyses for marker identification, as well as exploratory complex workflows with dimension reduction techniques and identification of unsupervised groups between samples or sites. AutoMethyc was tested in a breast cancer study ($n=389$; 233 cases and 156 controls) using BS-Seq data from the Illumina MiSeq platform, mapping 330 methylation-prone citocine (CpG) sites in 20 genes. The analysis was performed on a desktop with 64 GB RAM, 16 cores (4.673 GHz), and 326 KB/s internet, running Fedora 39 with i3wm. The tool processed the dataset in 48 h, showcasing its efficiency and scalability.</p>","PeriodicalId":9209,"journal":{"name":"Briefings in bioinformatics","volume":"26 4","pages":""},"PeriodicalIF":7.7000,"publicationDate":"2025-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12357496/pdf/","citationCount":"0","resultStr":"{\"title\":\"AutoMethyc: an automated methylation analysis for massively parallel sequencing data.\",\"authors\":\"Fernando Ambriz-Barrera, Miguel Ruiz-De La Cruz, Héctor Martínez-Gregorio, Clara E Díaz-Velásquez, Aldo H De La Cruz-Montoya, Felipe Vaca-Paniagua\",\"doi\":\"10.1093/bib/bbaf416\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Motivation: </strong>Bisulfite sequencing (BS-Seq) enables a comprehensive and detailed analysis of DNA methylation patterns at single-nucleotide resolution. While methylation differences can contribute to various diseases, their sincronous occurrence at distinct loci complicates understanding. Therefore, advanced tools are essential to facilitate the identification and analysis of methylation programs and patterns.</p><p><strong>Results: </strong>AutoMethyc provides a comparative approach by integrating different algorithms coordinated and optimized for use on desktop computers and servers. The workflow evaluates the methylation status from different perspectives, facilitating interpretation in an interactive HTML report, incorporating new co-methylation analyses for marker identification, as well as exploratory complex workflows with dimension reduction techniques and identification of unsupervised groups between samples or sites. AutoMethyc was tested in a breast cancer study ($n=389$; 233 cases and 156 controls) using BS-Seq data from the Illumina MiSeq platform, mapping 330 methylation-prone citocine (CpG) sites in 20 genes. The analysis was performed on a desktop with 64 GB RAM, 16 cores (4.673 GHz), and 326 KB/s internet, running Fedora 39 with i3wm. The tool processed the dataset in 48 h, showcasing its efficiency and scalability.</p>\",\"PeriodicalId\":9209,\"journal\":{\"name\":\"Briefings in bioinformatics\",\"volume\":\"26 4\",\"pages\":\"\"},\"PeriodicalIF\":7.7000,\"publicationDate\":\"2025-07-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12357496/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Briefings in bioinformatics\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1093/bib/bbaf416\",\"RegionNum\":2,\"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":"Briefings in bioinformatics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1093/bib/bbaf416","RegionNum":2,"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

亚硫酸氢盐测序(BS-Seq)能够在单核苷酸分辨率下对DNA甲基化模式进行全面和详细的分析。虽然甲基化差异可以导致各种疾病,但它们在不同位点的共同发生使理解复杂化。因此,先进的工具对于促进甲基化程序和模式的识别和分析是必不可少的。结果:AutoMethyc提供了一种比较的方法,通过整合不同的算法来协调和优化桌面计算机和服务器的使用。该工作流程从不同的角度评估甲基化状态,促进在交互式HTML报告中的解释,结合新的共甲基化分析用于标记识别,以及使用降维技术探索复杂的工作流程,并识别样本或站点之间的无监督组。AutoMethyc在一项乳腺癌研究中进行了测试(n=389;使用Illumina MiSeq平台的BS-Seq数据,绘制了20个基因中330个甲基化倾向的柠檬酸(CpG)位点。分析是在具有64 GB RAM、16核(4.673 GHz)和326 KB/s internet、运行Fedora 39和i3wm的台式机上进行的。该工具在48小时内处理了数据集,显示了其效率和可扩展性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
AutoMethyc: an automated methylation analysis for massively parallel sequencing data.

Motivation: Bisulfite sequencing (BS-Seq) enables a comprehensive and detailed analysis of DNA methylation patterns at single-nucleotide resolution. While methylation differences can contribute to various diseases, their sincronous occurrence at distinct loci complicates understanding. Therefore, advanced tools are essential to facilitate the identification and analysis of methylation programs and patterns.

Results: AutoMethyc provides a comparative approach by integrating different algorithms coordinated and optimized for use on desktop computers and servers. The workflow evaluates the methylation status from different perspectives, facilitating interpretation in an interactive HTML report, incorporating new co-methylation analyses for marker identification, as well as exploratory complex workflows with dimension reduction techniques and identification of unsupervised groups between samples or sites. AutoMethyc was tested in a breast cancer study ($n=389$; 233 cases and 156 controls) using BS-Seq data from the Illumina MiSeq platform, mapping 330 methylation-prone citocine (CpG) sites in 20 genes. The analysis was performed on a desktop with 64 GB RAM, 16 cores (4.673 GHz), and 326 KB/s internet, running Fedora 39 with i3wm. The tool processed the dataset in 48 h, showcasing its efficiency and scalability.

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
Briefings in bioinformatics
Briefings in bioinformatics 生物-生化研究方法
CiteScore
13.20
自引率
13.70%
发文量
549
审稿时长
6 months
期刊介绍: Briefings in Bioinformatics is an international journal serving as a platform for researchers and educators in the life sciences. It also appeals to mathematicians, statisticians, and computer scientists applying their expertise to biological challenges. The journal focuses on reviews tailored for users of databases and analytical tools in contemporary genetics, molecular and systems biology. It stands out by offering practical assistance and guidance to non-specialists in computerized methodologies. Covering a wide range from introductory concepts to specific protocols and analyses, the papers address bacterial, plant, fungal, animal, and human data. The journal's detailed subject areas include genetic studies of phenotypes and genotypes, mapping, DNA sequencing, expression profiling, gene expression studies, microarrays, alignment methods, protein profiles and HMMs, lipids, metabolic and signaling pathways, structure determination and function prediction, phylogenetic studies, and education and training.
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信