The Hitchhiker’s Guide to Statistical Analysis of Feature-based Molecular Networks from Non-Targeted Metabolomics Data

计算机科学 脚本语言 数据库规范化 协议(科学) Python(编程语言) 工具箱 瓶颈 数据挖掘 机器学习 程序设计语言 聚类分析 医学 病理 嵌入式系统 替代医学
作者
Abzer K. Pakkir Shah,Axel Walter,Filip Ottosson,Francesco Russo,Marcelo Navarro-Díaz,Judith Boldt,Jarmo-Charles Kalinski,Eftychia E. Kontou,James Elofson,Alexandros Polyzois,Carolina González-Marín,Stephanie Farrell,Marie Rønne Aggerbeck,Thapanee Pruksatrakul,Ngai Hang Chan,Yunshu Wang,Magdalena Pöchhacker,Corinna Brungs,Beatríz Cámara,Andrés Mauricio Caraballo‐Rodríguez,Andrés Cumsille,Fernanda de Oliveira,Kai Dührkop,Yasin El Abiead,Christian Geibel,Lana G Graves,Martin Hansen,Steffen Heuckeroth,Simon Knoblauch,Anastasiia Kostenko,Mirte C. M. Kuijpers,Kevin Mildau,Stilianos Papadopoulos Lambidis,Paulo Wender Portal Gomes,T Schramm,Karoline Steuer-Lodd,Paolo Stincone,Sibgha Tayyab,Giovanni Andrea Vitale,Berenike Wagner,Shipei Xing,Marquis T. Yazzie,Simone Zuffa,Martinus de Kruijff,Christine Beemelmanns,Hannes Link,Christoph Mayer,Justin J. J. van der Hooft,Tito Damiani,Tomáš Pluskal,Pieter C. Dorrestein,Jan Stanstrup,Robin Schmid,Mingxun Wang,Allegra T. Aron,Madeleine Ernst,Daniel Petras
标识
DOI:10.26434/chemrxiv-2023-wwbt0
摘要

Feature-Based Molecular Networking (FBMN) is a popular analysis approach for LC-MS/MS-based non-targeted metabolomics data. While processing LC-MS/MS data through FBMN is fairly streamlined, downstream data handling and statistical interrogation is often a key bottleneck. Especially, users new to statistical analysis struggle to effectively handle and analyze complex data matrices. In this protocol, we provide a comprehensive guide for the statistical analysis of FBMN results. We explain the data structure and principles of data clean-up and normalization, as well as uni- and multivariate statistical analysis of FBMN results. We provide explanations and code in two scripting languages (R and Python) as well as the QIIME2 framework for all protocol steps, from data clean-up to statistical analysis. Additionally, the protocol is accompanied by a web application with a graphical user interface (https://fbmn-statsguide.gnps2.org/), to lower the barrier of entry for new users. Together, the protocol, code, and web app provide a complete guide and toolbox for FBMN data integration, clean-up, and advanced statistical analysis, enabling new users to uncover molecular insights from their non-targeted metabolomics data. Our protocol is tailored for the seamless analysis of FBMN results from Global Natural Products Social Molecular Networking (GNPS and GNPS2) and can be adapted to other MS feature detection, annotation, and networking tools.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
聪慧的小土豆完成签到 ,获得积分10
2秒前
2秒前
自觉的凌青完成签到,获得积分10
2秒前
4秒前
6秒前
畅快芝麻发布了新的文献求助10
6秒前
zriverm发布了新的文献求助10
8秒前
干煸鸡发布了新的文献求助10
9秒前
10秒前
11秒前
11秒前
12秒前
量子星尘发布了新的文献求助10
12秒前
呸呸晓鹏发布了新的文献求助10
16秒前
枫之林发布了新的文献求助10
17秒前
小蘑菇应助zriverm采纳,获得10
19秒前
19秒前
19秒前
SciGPT应助小鱼采纳,获得10
20秒前
学术渣渣发布了新的文献求助30
20秒前
渡劫完成签到,获得积分10
21秒前
21秒前
24秒前
靓丽雨梅完成签到 ,获得积分10
24秒前
等待的花生完成签到,获得积分10
24秒前
26秒前
Mangues发布了新的文献求助30
26秒前
呸呸晓鹏完成签到,获得积分20
26秒前
搜集达人应助xuxu采纳,获得10
27秒前
111111关注了科研通微信公众号
28秒前
28秒前
28秒前
小唐尼发布了新的文献求助30
32秒前
32秒前
36秒前
彭于晏应助gewenxue采纳,获得10
37秒前
幸福大白发布了新的文献求助10
39秒前
yyyy完成签到,获得积分10
40秒前
zx完成签到,获得积分10
40秒前
高分求助中
A new approach to the extrapolation of accelerated life test data 1000
ACSM’s Guidelines for Exercise Testing and Prescription, 12th edition 500
‘Unruly’ Children: Historical Fieldnotes and Learning Morality in a Taiwan Village (New Departures in Anthropology) 400
Indomethacinのヒトにおける経皮吸収 400
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 370
基于可调谐半导体激光吸收光谱技术泄漏气体检测系统的研究 350
Robot-supported joining of reinforcement textiles with one-sided sewing heads 320
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3989069
求助须知:如何正确求助?哪些是违规求助? 3531351
关于积分的说明 11253589
捐赠科研通 3269939
什么是DOI,文献DOI怎么找? 1804851
邀请新用户注册赠送积分活动 882074
科研通“疑难数据库(出版商)”最低求助积分说明 809073