DOSCHEDA: a web application for interactive chemoproteomics data analysis

Background Mass Spectrometry (MS) based chemoproteomics has recently become a main tool to identify and quantify cellular target protein interactions with ligands/drugs in drug discovery. The complexity associated with these new types of data requires scientists with a limited computational backgrou...

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Main Authors: Bruno Contrino, Eric Miele, Ronald Tomlinson, M. Paola Castaldi, Piero Ricchiuto
Format: Article
Language:English
Published: PeerJ Inc. 2017-08-01
Series:PeerJ Computer Science
Subjects:
TMT
Online Access:https://peerj.com/articles/cs-129.pdf
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spelling doaj-c8ac7cc546754c1b905b13912f8d19012020-11-24T23:24:38ZengPeerJ Inc.PeerJ Computer Science2376-59922017-08-013e12910.7717/peerj-cs.129DOSCHEDA: a web application for interactive chemoproteomics data analysisBruno Contrino0Eric Miele1Ronald Tomlinson2M. Paola Castaldi3Piero Ricchiuto4Department of Quantitative Biology, Discovery Sciences, AstraZeneca, Cambridge, United KingdomDepartment of Chemical Biology, Discovery Biology, Discovery Sciences, AstraZeneca, Waltham, MA, United States of AmericaDepartment of Chemical Biology, Discovery Biology, Discovery Sciences, AstraZeneca, Waltham, MA, United States of AmericaDepartment of Chemical Biology, Discovery Biology, Discovery Sciences, AstraZeneca, Waltham, MA, United States of AmericaDepartment of Quantitative Biology, Discovery Sciences, AstraZeneca, Cambridge, United KingdomBackground Mass Spectrometry (MS) based chemoproteomics has recently become a main tool to identify and quantify cellular target protein interactions with ligands/drugs in drug discovery. The complexity associated with these new types of data requires scientists with a limited computational background to perform systematic data quality controls as well as to visualize the results derived from the analysis to enable rapid decision making. To date, there are no readily accessible platforms specifically designed for chemoproteomics data analysis. Results We developed a Shiny-based web application named DOSCHEDA (Down Stream Chemoproteomics Data Analysis) to assess the quality of chemoproteomics experiments, to filter peptide intensities based on linear correlations between replicates, and to perform statistical analysis based on the experimental design. In order to increase its accessibility, DOSCHEDA is designed to be used with minimal user input and it does not require programming knowledge. Typical inputs can be protein fold changes or peptide intensities obtained from Proteome Discover, MaxQuant or other similar software. DOSCHEDA aggregates results from bioinformatics analyses performed on the input dataset into a dynamic interface, it encompasses interactive graphics and enables customized output reports. Conclusions DOSCHEDA is implemented entirely in R language. It can be launched by any system with R installed, including Windows, Mac OS and Linux distributions. DOSCHEDA is hosted on a shiny-server at https://doscheda.shinyapps.io/doscheda and is also available as a Bioconductor package (http://www.bioconductor.org/).https://peerj.com/articles/cs-129.pdfQuantitative ChemoproteomicsStatistical ModelsWeb interfaceShinyTMTiTRAQ
collection DOAJ
language English
format Article
sources DOAJ
author Bruno Contrino
Eric Miele
Ronald Tomlinson
M. Paola Castaldi
Piero Ricchiuto
spellingShingle Bruno Contrino
Eric Miele
Ronald Tomlinson
M. Paola Castaldi
Piero Ricchiuto
DOSCHEDA: a web application for interactive chemoproteomics data analysis
PeerJ Computer Science
Quantitative Chemoproteomics
Statistical Models
Web interface
Shiny
TMT
iTRAQ
author_facet Bruno Contrino
Eric Miele
Ronald Tomlinson
M. Paola Castaldi
Piero Ricchiuto
author_sort Bruno Contrino
title DOSCHEDA: a web application for interactive chemoproteomics data analysis
title_short DOSCHEDA: a web application for interactive chemoproteomics data analysis
title_full DOSCHEDA: a web application for interactive chemoproteomics data analysis
title_fullStr DOSCHEDA: a web application for interactive chemoproteomics data analysis
title_full_unstemmed DOSCHEDA: a web application for interactive chemoproteomics data analysis
title_sort doscheda: a web application for interactive chemoproteomics data analysis
publisher PeerJ Inc.
series PeerJ Computer Science
issn 2376-5992
publishDate 2017-08-01
description Background Mass Spectrometry (MS) based chemoproteomics has recently become a main tool to identify and quantify cellular target protein interactions with ligands/drugs in drug discovery. The complexity associated with these new types of data requires scientists with a limited computational background to perform systematic data quality controls as well as to visualize the results derived from the analysis to enable rapid decision making. To date, there are no readily accessible platforms specifically designed for chemoproteomics data analysis. Results We developed a Shiny-based web application named DOSCHEDA (Down Stream Chemoproteomics Data Analysis) to assess the quality of chemoproteomics experiments, to filter peptide intensities based on linear correlations between replicates, and to perform statistical analysis based on the experimental design. In order to increase its accessibility, DOSCHEDA is designed to be used with minimal user input and it does not require programming knowledge. Typical inputs can be protein fold changes or peptide intensities obtained from Proteome Discover, MaxQuant or other similar software. DOSCHEDA aggregates results from bioinformatics analyses performed on the input dataset into a dynamic interface, it encompasses interactive graphics and enables customized output reports. Conclusions DOSCHEDA is implemented entirely in R language. It can be launched by any system with R installed, including Windows, Mac OS and Linux distributions. DOSCHEDA is hosted on a shiny-server at https://doscheda.shinyapps.io/doscheda and is also available as a Bioconductor package (http://www.bioconductor.org/).
topic Quantitative Chemoproteomics
Statistical Models
Web interface
Shiny
TMT
iTRAQ
url https://peerj.com/articles/cs-129.pdf
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