Proteus

an R package for downstream analysis of MaxQuant output

Research output: Contribution to journalArticle

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Abstract

Proteus is a package for downstream analysis of MaxQuant evidence data in the R environment. It provides tools for peptide and protein aggregation, quality checks, data exploration and visualisation. Interactive analysis is implemented in the Shiny framework, where individual peptides or protein may be examined in the context of a volcano plot. Proteus performs differential expression analysis with the well-established tool limma, which offers robust treatment of missing data, frequently encountered in label-free mass-spectrometry experiments. We demonstrate on real and simulated data that limma results in improved sensitivity over random imputation combined with a t-test as implemented in the popular package Perseus. Embedding Proteus in R provides access to a wide selection of statistical and graphical tools for further analysis and reproducibility by scripting. Availability and implementation: The open-source R package, including example data and tutorials, is available to install from GitHub (https://github.com/bartongroup/proteus).

Original languageEnglish
Number of pages10
JournalBioRxiv
DOIs
Publication statusPublished - 20 Sep 2018

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Proteus
Peptides
Mass Spectrometry
Proteins

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@article{64b67417f63a436da67ee50ab6d9331f,
title = "Proteus: an R package for downstream analysis of MaxQuant output",
abstract = "Proteus is a package for downstream analysis of MaxQuant evidence data in the R environment. It provides tools for peptide and protein aggregation, quality checks, data exploration and visualisation. Interactive analysis is implemented in the Shiny framework, where individual peptides or protein may be examined in the context of a volcano plot. Proteus performs differential expression analysis with the well-established tool limma, which offers robust treatment of missing data, frequently encountered in label-free mass-spectrometry experiments. We demonstrate on real and simulated data that limma results in improved sensitivity over random imputation combined with a t-test as implemented in the popular package Perseus. Embedding Proteus in R provides access to a wide selection of statistical and graphical tools for further analysis and reproducibility by scripting. Availability and implementation: The open-source R package, including example data and tutorials, is available to install from GitHub (https://github.com/bartongroup/proteus).",
author = "Marek Gierlinski and Francesco Gastaldello and Christian Cole and Geoffrey Barton",
note = "The School of Life Sciences Data Analysis Group is funded by the Wellcome Trust grant 097945/Z/11/Z.",
year = "2018",
month = "9",
day = "20",
doi = "10.1101/416511",
language = "English",
journal = "BioRxiv",
publisher = "Cold Spring Harbor Laboratory Press",

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Proteus : an R package for downstream analysis of MaxQuant output . / Gierlinski, Marek; Gastaldello, Francesco; Cole, Christian; Barton, Geoffrey.

In: BioRxiv, 20.09.2018.

Research output: Contribution to journalArticle

TY - JOUR

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T2 - an R package for downstream analysis of MaxQuant output

AU - Gierlinski, Marek

AU - Gastaldello, Francesco

AU - Cole, Christian

AU - Barton, Geoffrey

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AB - Proteus is a package for downstream analysis of MaxQuant evidence data in the R environment. It provides tools for peptide and protein aggregation, quality checks, data exploration and visualisation. Interactive analysis is implemented in the Shiny framework, where individual peptides or protein may be examined in the context of a volcano plot. Proteus performs differential expression analysis with the well-established tool limma, which offers robust treatment of missing data, frequently encountered in label-free mass-spectrometry experiments. We demonstrate on real and simulated data that limma results in improved sensitivity over random imputation combined with a t-test as implemented in the popular package Perseus. Embedding Proteus in R provides access to a wide selection of statistical and graphical tools for further analysis and reproducibility by scripting. Availability and implementation: The open-source R package, including example data and tutorials, is available to install from GitHub (https://github.com/bartongroup/proteus).

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