PeptideWitch - a software package to produce high-stringency proteomics data visualizations from label-free shotgun proteomics data

David C. L. Handler; Flora Cheng; Abdulrahman M. Shathili; Paul A. Haynes

doi:10.3390/PROTEOMES8030021

PeptideWitch - a software package to produce high-stringency proteomics data visualizations from label-free shotgun proteomics data

David C. L. Handler, Flora Cheng, Abdulrahman M. Shathili, Paul A. Haynes^*

^*Corresponding author for this work

Faculty of Medicine, Health and Human Sciences

Research output: Contribution to journal › Article › peer-review

2 Citations (Scopus)

6 Downloads (Pure)

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
Article number	21
Pages (from-to)	1-11
Number of pages	11
Journal	Proteomes
Volume	8
Issue number	3
DOIs	https://doi.org/10.3390/PROTEOMES8030021
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

Access to Document

10.3390/PROTEOMES8030021

Publisher version (open access)Final published version, 1.02 MBLicence: CC BY

Cite this

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title = "PeptideWitch - a software package to produce high-stringency proteomics data visualizations from label-free shotgun proteomics data",

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.",

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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. ",

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AU - Cheng, Flora

AU - Shathili, Abdulrahman M.

AU - Haynes, Paul A.

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AB - 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.

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KW - False discovery rate

KW - Data quality

KW - Protein quantitation

KW - Spectral counting

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UR - http://purl.org/au-research/grants/arc/DP190103140

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PeptideWitch - a software package to produce high-stringency proteomics data visualizations from label-free shotgun proteomics data

Abstract

Bibliographical note

Keywords

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Re-engineering rice root architecture to maximise water use efficiency

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PeptideWitch - a software package to produce high-stringency proteomics data visualizations from label-free shotgun proteomics data

Abstract

Bibliographical note

Keywords

Access to Document

Other files and links

Fingerprint

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Re-engineering rice root architecture to maximise water use efficiency

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