statTarget: A streamlined tool for signal drift correction and interpretations of quantitative mass spectrometry-based omics data

Luan, Hemi1,2; Ji, Fenfen1; Chen, Yu3,4; Cai, Zongwei1

2018-12-07

10.1016/j.aca.2018.08.002

ANALYTICA CHIMICA ACTA   影响因子和分区

0003-2670

1873-4324

Large-scale quantitative mass spectrometry-based metabolomics and proteomics study requires the longterm analysis of multiple batches of biological samples, which often accompanied with significant signal drift and various inter- and intra-batch variations. The unwanted variations can lead to poor inter- and intra-day reproducibility, which is a hindrance to discover real significance. The use of quality control samples and data treatment strategies in the quality assurance procedure provides a mechanism to evaluate the quality and remove the analytical variance of the data. The statTarget we developed is a streamlined tool with an easy-to-use graphical user interface and an integrated suite of algorithms specifically developed for the evaluation of data quality and removal of unwanted variations for quantitative mass spectrometry-based omics data. A novel quality control-based random forest signal correction algorithm, which can remove inter- and intra-batch unwanted variations at feature-level was implanted in the statTarget. Our evaluation based on real samples showed the developed algorithm could improve the data precision and statistical accuracy for mass spectrometry-based metabolomics and proteomics data. Additionally, the statTarget offers the streamlined procedures for data imputation, data normalization, univariate analysis, multivariate analysis, and feature selection. To conclude, the statTarget allows user-friendly the improvement of the data precision for uncovering the biologically differences, which largely facilitates quantitative mass spectrometry-based omics data processing and statistical analysis. (C) 2018 Elsevier B.V. All rights reserved.

SCI ; EI

英语

通讯

National Natural Science Foundation of China[NSFC21675176] ; National Natural Science Foundation of China[NSFC91543202]

Chemistry

Chemistry, Analytical

WOS:000445197900007

ELSEVIER SCIENCE BV

20183305686560

Data handling ; Decision trees ; Graphical user interfaces ; Mass spectrometry ; Molecular biology ; Multivariant analysis ; Quality assurance

Biology:461.9 ; Computer Peripheral Equipment:722.2 ; Data Processing and Image Processing:723.2 ; Chemistry:801 ; Quality Assurance and Control:913.3 ; Statistical Methods:922 ; Systems Science:961

CHEMISTRY

Web of Science

1.Hong Kong Baptist Univ, SKLEBA, Kowloon Tong, Hong Kong, Peoples R China
2.Southern Univ Sci & Technol, SUSTech Acad Adv Interdisciplinary Studies, Shenzhen 518055, Peoples R China
3.Max Planck Inst Terr Microbiol, Marburg, Germany
4.LOEWE Res Ctr Synthet Microbiol SYNMIKRO, Marburg, Germany

Luan, Hemi,Ji, Fenfen,Chen, Yu,et al. statTarget: A streamlined tool for signal drift correction and interpretations of quantitative mass spectrometry-based omics data[J]. ANALYTICA CHIMICA ACTA,2018,1036:66-72.

Luan, Hemi,Ji, Fenfen,Chen, Yu,&Cai, Zongwei.(2018).statTarget: A streamlined tool for signal drift correction and interpretations of quantitative mass spectrometry-based omics data.ANALYTICA CHIMICA ACTA,1036,66-72.

Luan, Hemi,et al."statTarget: A streamlined tool for signal drift correction and interpretations of quantitative mass spectrometry-based omics data".ANALYTICA CHIMICA ACTA 1036(2018):66-72.