Interactive Web Tool for Standardizing Proteomics Workflow for Liquid Chromatography-Mass Spectrometry Data.

Coefficient of variation Imputation Peptides Proteins Sum of squares Technical variability

Journal

Journal of proteomics & bioinformatics
ISSN: 0974-276X
Titre abrégé: J Proteomics Bioinform
Pays: United States
ID NLM: 101479045

Informations de publication

Date de publication:
2019
Historique:
entrez: 10 3 2020
pubmed: 1 1 2019
medline: 1 1 2019
Statut: ppublish

Résumé

The proteomics experiments involve several steps and there are many choices available for each step in the workflow. Therefore, standardization of proteomics workflow is an essential task for design of proteomics experiments. However, there are challenges associated with the quantitative measurements based on liquid chromatography-mass spectrometry such as heterogeneity due to technical variability and missing values. We introduce a web application, Proteomics Workflow Standardization Tool (PWST) to standardize the proteomics workflow. The tool will be helpful in deciding the most suitable choice for each step of the experimentation. This is based on identifying steps/choices with least variability such as comparing Coefficient of Variation (CV). We demonstrate the tool on data with categorical and continuous variables. We have used the special cases of general linear model, analysis of covariance and analysis of variance with fixed effects to study the effects due to various sources of variability. We have provided various options that will aid in finding the contribution of sum of squares for each variable and the CV. The user can analyze the data variability at protein and peptide level even in the presence of missing values. The source code for "PWST" is written in R and implemented as shiny web application that can be accessed freely from https://ulbbf.shinyapps.io/pwst/.

Identifiants

pubmed: 32148360
pmc: PMC7059686
mid: NIHMS1034721

Types de publication

Journal Article

Langues

eng

Pagination

85-88

Subventions

Organisme : NIGMS NIH HHS
ID : P20 GM113226
Pays : United States
Organisme : NIEHS NIH HHS
ID : P42 ES023716
Pays : United States
Organisme : NIAAA NIH HHS
ID : P50 AA024337
Pays : United States

Déclaration de conflit d'intérêts

All authors have no conflict or disclosures and provide consent for publication.

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Auteurs

Sudhir Srivastava (S)

Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India.
Department of Bioinformatics & Biostatistics, University of Louisville, Louisville, Kentucky, United States of America.

Michael Merchant (M)

Department of Medicine, University of Louisville, Louisville, Kentucky, United States of America.
Department of Pharmacology & Toxicology, University of Louisville, Louisville, Kentucky, United States of America.

Anil Rai (A)

Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India.

Shesh N Rai (SN)

Department of Bioinformatics & Biostatistics, University of Louisville, Louisville, Kentucky, United States of America.
Biostatistics and Bioinformatics Facility, James Graham Brown Cancer Center, University of Louisville, Louisville, Kentucky, United States of America.

Classifications MeSH