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Abstract
PeptideWitch is a python-based web module that introduces several key graphical and technical improvements to the Scrappy software platform, which is designed for label-free quantitative shotgun proteomics analysis using normalised spectral abundance factors. The program inputs are low stringency protein identification lists output from peptide-to-spectrum matching search engines for 'control' and 'treated' samples. Through a combination of spectral count summation and inner joins, PeptideWitch processes low stringency data, and outputs high stringency data that are suitable for downstream quantitation. Data quality metrics are generated, and a series of statistical analyses and graphical representations are presented, aimed at defining and presenting the difference between the two sample proteomes.
Original language | English |
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Article number | 21 |
Pages (from-to) | 1-11 |
Number of pages | 11 |
Journal | Proteomes |
Volume | 8 |
Issue number | 3 |
DOIs | |
Publication status | Published - Sep 2020 |
Bibliographical note
Copyright the Author(s) 2020. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.Keywords
- Label-free shotgun proteomics
- False discovery rate
- Data quality
- Protein quantitation
- Spectral counting
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Dive into the research topics of 'PeptideWitch - a software package to produce high-stringency proteomics data visualizations from label-free shotgun proteomics data'. Together they form a unique fingerprint.Projects
- 1 Finished
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Re-engineering rice root architecture to maximise water use efficiency
Haynes, P., Mirzaei, M., Atwell, B., Pascovici, D. & Salekdeh, H.
19/06/19 → 18/06/22
Project: Other