Comparison of Full-Scan, Data-Dependent, and Data-Independent Acquisition Modes in Liquid Chromatography–Mass Spectrometry Based Untargeted Metabolomics

化学 数据采集 质谱法 色谱法 尿 代谢组学 预处理器 数据预处理 标准差 分析化学(期刊) 计算机科学 数据挖掘 人工智能 统计 数学 生物化学 操作系统
作者
Jian Guo,Tao Huan
出处
期刊:Analytical Chemistry [American Chemical Society]
卷期号:92 (12): 8072-8080 被引量:210
标识
DOI:10.1021/acs.analchem.9b05135
摘要

Full-scan, data-dependent acquisition (DDA), and data-independent acquisition (DIA) are the three common data acquisition modes in high resolution mass spectrometry-based untargeted metabolomics. It is an important yet underrated research topic on which acquisition mode is more suitable for a given untargeted metabolomics application. In this work, we compared the three data acquisition techniques using a standard mixture of 134 endogenous metabolites and a human urine sample. Both hydrophilic interaction and reversed-phase liquid chromatographic separation along with positive and negative ionization modes were tested. Both the standard mixture and urine sample generated consistent results. Full-scan mode is able to capture the largest number of metabolic features, followed by DIA and DDA (53.7% and 64.8% respective features fewer on average in urine than full-scan). Comparing the MS2 spectra in DIA and DDA, spectra quality is higher in DDA with average dot product score 83.1% higher than DIA in Urine(H), and the number of MS2 spectra (spectra quantity) is larger in DIA (on average 97.8% more than DDA in urine). Moreover, a comparison of relative standard deviation distribution between modes shows consistency in the quantitative precision, with the exception of DDA showing a minor disadvantage (on average 19.8% and 26.8% fewer features in urine with RSD < 5% than full-scan and DIA). In terms of data preprocessing convenience, full-scan and DDA data can be processed by well-established software. In contrast, several bioinformatic issues remain to be addressed in processing DIA data and the development of more effective computational programs is highly demanded.
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
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
hi_traffic完成签到,获得积分10
1秒前
默11完成签到 ,获得积分10
2秒前
kenchilie完成签到 ,获得积分10
9秒前
喜悦的香之完成签到 ,获得积分10
9秒前
一拳一个小欧阳完成签到 ,获得积分10
11秒前
友好的白柏完成签到 ,获得积分10
18秒前
20秒前
zhangjianzeng完成签到 ,获得积分10
21秒前
lhn完成签到 ,获得积分10
21秒前
pterionGao完成签到 ,获得积分10
23秒前
秋迎夏完成签到,获得积分0
26秒前
yujie完成签到 ,获得积分10
27秒前
kyle完成签到 ,获得积分10
33秒前
玉鱼儿完成签到 ,获得积分10
42秒前
水哥完成签到 ,获得积分10
45秒前
46秒前
柒月完成签到,获得积分10
48秒前
心想事成完成签到 ,获得积分10
52秒前
牛奶拌可乐完成签到 ,获得积分10
1分钟前
上官若男应助tuihuo采纳,获得10
1分钟前
乔杰完成签到 ,获得积分10
1分钟前
迟迟完成签到 ,获得积分10
1分钟前
1分钟前
yu_z完成签到 ,获得积分10
1分钟前
CipherSage应助科研通管家采纳,获得10
1分钟前
cdercder应助科研通管家采纳,获得10
1分钟前
小胖完成签到 ,获得积分10
1分钟前
小情绪完成签到 ,获得积分10
1分钟前
缓慢的煎饼完成签到 ,获得积分10
1分钟前
1分钟前
1分钟前
绿色心情完成签到 ,获得积分10
1分钟前
1分钟前
科研通AI2S应助Wan采纳,获得10
1分钟前
tuihuo发布了新的文献求助10
1分钟前
danli完成签到 ,获得积分10
1分钟前
偏偏海完成签到,获得积分10
1分钟前
tuihuo完成签到,获得积分10
1分钟前
丘比特应助巫郁采纳,获得10
2分钟前
健忘的晓小完成签到 ,获得积分10
2分钟前
高分求助中
Les Mantodea de Guyane Insecta, Polyneoptera 2500
Mobilization, center-periphery structures and nation-building 600
Technologies supporting mass customization of apparel: A pilot project 600
Introduction to Strong Mixing Conditions Volumes 1-3 500
China—Art—Modernity: A Critical Introduction to Chinese Visual Expression from the Beginning of the Twentieth Century to the Present Day 430
Multichannel rotary joints-How they work 400
A Field Guide to the Amphibians and Reptiles of Madagascar - Frank Glaw and Miguel Vences - 3rd Edition 400
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 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3795624
求助须知:如何正确求助?哪些是违规求助? 3340681
关于积分的说明 10300957
捐赠科研通 3057185
什么是DOI,文献DOI怎么找? 1677539
邀请新用户注册赠送积分活动 805449
科研通“疑难数据库(出版商)”最低求助积分说明 762626