arrow
返回

Label -free proteome quantification and evaluation

delete2022-11-19
delete10
PRE
AI
J
Jianbo Fu
Q
Qingxia Yang
Y
Yongchao Luo
S
Song Zhang
J
Jing Tang
Y
Ying Zhang
H
Hongning Zhang
H
Hanxiang Xu
F
Feng Zhu *
DOI:10.1093/bib/bbac477delete
delete原文链接
delete原文求助
delete分享
delete收藏
摘要

摘要

En 中文
The label -free quantification (LFQ) has emerged as an exceptional technique in proteomics owing to its broad proteome coverage, great dynamic ranges and enhanced analytical reproducibility. Due to the extreme difficulty lying in an in-depth quantification, the LFQ chains incorporating a variety of transformation, pretreatment and imputation methods are required and constructed. However, it remains challenging to determine the well -performing chain, owing to its strong dependence on the studied data and the diverse possibility of integrated chains. In this study, an R package EVALFQ was therefore constructed to enable a performance evaluation on >3000 LFQ chains. This package is unique in (a) automatically evaluating the performance using multiple criteria, (b) exploring the quantification accuracy based on spiking proteins and (c) discovering the well -performing chains by comprehensive assessment. All in all, because of its superiority in assessing from multiple perspectives and scanning among over 3000 chains, this package is expected to attract broad interests from the fields of proteomic quantification. The package is available at https://github.conVidrblab/EVALFQ.
Keyword:
label -free quantification
proteomics
comprehensive evaluation
well -performing chains
R package

期刊

Briefings in Bioinformatics 封面图
Briefings in Bioinformatics
IF:
7.7
论文数:
5.8K
被引数:
2.7W

机构

Z
zhejiang university
学者数:
17.7W
论文数: 12.1W
被引数: 152
引用论文

引用论文

OpenSWATH enables automated, targeted analysis of data-independent acquisition MS data
err2014-03-10
err626
errOAAI
errRoest, Hannes L.; Rosenberger, George; Navarro, Pedro; Gillet, Ludovic; Miladinovic, Sasa M.; Schubert, Olga T.; Wolskit, Witold; Collins, Ben C.; Malmstrom, Johan; Malmstroem, Lars; Aebersold, Ruedi
err分享
err收藏
iProX: an integrated proteome resourceiProX: 一个整合的蛋白质组资源
err2018-09-25
err1.1K
errOAAI
errMa, Jie; Chen, Tao; Wu, Songfeng; Yang, Chunyuan; Bai, Mingze; Shu, Kunxian; Li, Kenli; Zhang, Guoqing; Jin, Zhong; He, Fuchu; Hermjakob, Henning; Zhu, Yunping
err分享
err收藏
Reproducibility, Specificity and Accuracy of Relative Quantification Using Spectral Library-based Data-independent Acquisition
err2020-01-01
err102
errOAAI
errBarkovits, Katalin; Pacharra, Sandra; Pfeiffer, Kathy; Steinbach, Simone; Eisenacher, Martin; Marcus, Katrin; Uszkoreit, Julian
err分享
err收藏
NAguideR: performing and prioritizing missing value imputations for consistent bottom-up proteomic analyses
err2020-06-11
err81
errOAAI
errWang, Shisheng; Li, Wenxue; Hu, Liqiang; Cheng, Jingqiu; Yang, Hao; Liu, Yansheng
err分享
err收藏
Optimization of Statistical Methods Impact on Quantitative Proteomics Data
err2015-09-08
err63
errOAAI
errPursiheimo, Anna; Vehmas, Anni P.; Afzal, Saira; Suomi, Tomi; Chand, Thaman; Strauss, Leena; Poutanen, Matti; Rokka, Anne; Corthals, Garry L.; Elo, Laura L.
err分享
err收藏
err分享
err收藏
DeMix-Q: Quantification-Centered Data Processing Workflow
err2016-04-01
err62
errOAAI
errZhang, Bo; Kall, Lukas; Zubarev, Roman A.
err分享
err收藏
学者 查看更多内容