Cheng Chang1, Jiyang Zhang, Mingfei Han, Jie Ma, Wei Zhang, Songfeng Wu, Kehui Liu, Hongwei Xie, Fuchu He, Yunping Zhu. 1. Department of Bioinformatics, State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences Beijing, Institute of Radiation Medicine and Department of Bioinformatics, National Engineering Research Center for Protein Drugs, Beijing 102206, Department of Automatic Control, College of Mechatronics and Automation, National University of Defense Technology, Changsha, Hunan 410073 and Department of Chemistry, Institutes of Biomedical Sciences, 130 DongAn Road, Fudan University, Shanghai 200032, P.R. China.
Abstract
SUMMARY: With the advance of experimental technologies, different stable isotope labeling methods have been widely applied to quantitative proteomics. Here, we present an efficient tool named SILVER for processing the stable isotope labeling mass spectrometry data. SILVER implements novel methods for quality control of quantification at spectrum, peptide and protein levels, respectively. Several new quantification confidence filters and indices are used to improve the accuracy of quantification results. The performance of SILVER was verified and compared with MaxQuant and Proteome Discoverer using a large-scale dataset and two standard datasets. The results suggest that SILVER shows high accuracy and robustness while consuming much less processing time. Additionally, SILVER provides user-friendly interfaces for parameter setting, result visualization, manual validation and some useful statistics analyses. AVAILABILITY AND IMPLEMENTATION: SILVER and its source codes are freely available under the GNU General Public License v3.0 at http://bioinfo.hupo.org.cn/silver.
SUMMARY: With the advance of experimental technologies, different stable isotope labeling methods have been widely applied to quantitative proteomics. Here, we present an efficient tool named SILVER for processing the stable isotope labeling mass spectrometry data. SILVER implements novel methods for quality control of quantification at spectrum, peptide and protein levels, respectively. Several new quantification confidence filters and indices are used to improve the accuracy of quantification results. The performance of SILVER was verified and compared with MaxQuant and Proteome Discoverer using a large-scale dataset and two standard datasets. The results suggest that SILVER shows high accuracy and robustness while consuming much less processing time. Additionally, SILVER provides user-friendly interfaces for parameter setting, result visualization, manual validation and some useful statistics analyses. AVAILABILITY AND IMPLEMENTATION:SILVER and its source codes are freely available under the GNU General Public License v3.0 at http://bioinfo.hupo.org.cn/silver.
Authors: Robin Mathew; Sinan Khor; Sean R Hackett; Joshua D Rabinowitz; David H Perlman; Eileen White Journal: Mol Cell Date: 2014-08-28 Impact factor: 17.970
Authors: Galina Smolikova; Daria Gorbach; Elena Lukasheva; Gregory Mavropolo-Stolyarenko; Tatiana Bilova; Alena Soboleva; Alexander Tsarev; Ekaterina Romanovskaya; Ekaterina Podolskaya; Vladimir Zhukov; Igor Tikhonovich; Sergei Medvedev; Wolfgang Hoehenwarter; Andrej Frolov Journal: Int J Mol Sci Date: 2020-12-01 Impact factor: 5.923