MassWiz
MassWiz is an open source software for protein identification from mass spectrometry data.[1] It is developed and maintained at Institute of Genomics and Integrative Biology. It was developed to better the existing methods by finding semi and non-enzymatic peptides to enhance the confidence in protein identifications. The Software aims at easy usability by automating the downstream analysis by integrating significance assessment by integrating FDR analysis which uses a target-decoy database search approach.
Features
MassWiz has a Windows 32 command line version for high throughput data analyses. The FDR analysis is directly plugged into the algorithm and the users can choose the type of target-decoy strategy they want to follow (i.e. either concatenated or separate target-decoy search).[1][2]
It has been shown that MassWiz performs better than commonly used search algorithms and identifies highest number of consensus peptides which are of high confidence.[1] Because of the comprehensive comparison of Spectra(PSMs-peptide spectrum matches) and peptides across various MS platforms with four other algorithms - Mascot, OMSSA, X!Tandem and Sequest, the MassWiz benchmarks can be used for deciding on choice of algorithms in analysis pipelines.
Webserver Algorithms and Tools
- Probability and intensity based PMF search
- Intensity and ion abundance based MS/MS search identifying semi+non-enzymatic peptides
- Candidate peptide validation
- Mass and pI calculator
- mzXML file converter
- Custom Database for targeted studies
- Customized local BLAST in the custom database
- Graphical representation of the matches found.
See also
- mass spectrometry
- mass spectrometry software
- proteomics
References
- ↑ 1.0 1.1 1.2 Yadav, Amit Kumar; Kumar, Dhirendra; Dash, Debasis (2011). "MassWiz: A Novel Scoring Algorithm with Target-Decoy Based Analysis Pipeline for Tandem Mass Spectrometry". Journal of Proteome Research 10 (5): 2154–2160. doi:10.1021/pr200031z. ISSN 1535-3893.
- ↑ Yadav AK, Bhardwaj G, Basak T, Kumar D, Ahmad S, et al. 2011 A Systematic Analysis of Eluted Fraction of Plasma Post Immunoaffinity Depletion: Implications in Biomarker Discovery. PLoS ONE 6(9): e24442. doi:10.1371/journal.pone.0024442