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

Abstract read

In one paragraph

Article in Proteomes, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

Shotgun Proteomics as a Powerful Tool for the Study of the Proteomes of Plants, Their Pathogens, and Plant-Pathogen Interactions.Proteomes · 2022
Review

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

David C L HandlerDepartment of Molecular Sciences, Macquarie University, North Ryde, NSW 2109, Australia.

Flora ChengFaculty of Medicine, Health and Human Sciences, Macquarie University, North Ryde, NSW 2109, Australia.

Abdulrahman M ShathiliDepartment of Molecular Sciences, Macquarie University, North Ryde, NSW 2109, Australia.

Paul A HaynesDepartment of Molecular Sciences, Macquarie University, North Ryde, NSW 2109, Australia.ORCID 0000-0003-1472-8249

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

data qualityfalse discovery ratelabel-free shotgun proteomicsprotein quantitationspectral counting

Identifiers

PMID32825686

DOI10.3390/proteomes8030021

PMCPMC7564585

What OpenQuestion holds

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LicenceCC BY

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.