SILVER
SILVER quantifies stable isotope labeling mass spectrometry (MS) data for quantitative proteomics by providing spectrum-, peptide-, and protein-level measurement with integrated quality control.
Key Features:
- Novel quality control methods: Implements multi-tiered QC at the spectrum, peptide, and protein levels to validate quantification results.
- Quantification confidence filters and indices: Employs multiple confidence filters and indices tailored to refine accuracy of stable isotope-labeling quantification.
- Performance verification: Benchmarked against MaxQuant and Proteome Discoverer using large-scale and standard datasets, demonstrating high accuracy, robustness, and significantly reduced processing time.
Scientific Applications:
- Quantitative proteomics: Provides precise measurement of protein abundance using stable isotope labeling MS.
- Biomarker discovery: Supports identification of differential protein abundance for biomarker studies.
- Pathway analysis: Enables comparative quantification for pathway-level investigations.
- Comparative proteomic studies: Facilitates condition-to-condition comparisons using stable isotope labeling approaches.
Methodology:
Implements spectrum-, peptide-, and protein-level QC methods and quantification confidence filters/indices, and was benchmarked against MaxQuant and Proteome Discoverer on large-scale and standard datasets with measurement of processing time.
Topics
Collections
Details
- Tool Type:
- desktop application
- Operating Systems:
- Windows
- Programming Languages:
- C++
- Added:
- 8/3/2017
- Last Updated:
- 11/25/2024
Operations
Data Inputs & Outputs
SILAC
Outputs
Publications
Chang C, Zhang J, Han M, Ma J, Zhang W, Wu S, Liu K, Xie H, He F, Zhu Y. SILVER: an efficient tool for stable isotope labeling LC-MS data quantitative analysis with quality control methods. Bioinformatics. 2013;30(4):586-587. doi:10.1093/bioinformatics/btt726. PMID:24344194.