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pRolocGUI

Interactive visualisation and exploration of spatial proteomics data

https://github.com/lgatto/prolocgui

Science Score: 59.0%

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Keywords from Contributors

bioconductor-packages bioconductor proteomics genomics mass-spectrometry metabolomics visualisation gene bioinformatics proteomics-data
Last synced: 6 months ago · JSON representation

Repository

Interactive visualisation and exploration of spatial proteomics data

Basic Info
Statistics
  • Stars: 8
  • Watchers: 3
  • Forks: 5
  • Open Issues: 12
  • Releases: 0
Created almost 12 years ago · Last pushed 9 months ago
Metadata Files
Readme Changelog

README.md

Bioconductor build status: - Devel: Bioconductor devel build Status - Release: Bioconductor release build Status

Exploring and visualising spatial proteomics data

Introduction

The pRolocGUI package is an interactive interface to explore and visualise experimental mass spectrometry-based spatial proteomics data. It relies on the shiny framework for interactive visualisation, the MSnbase package to handle data and metadata and the pRoloc software for spatial proteomics specific data matters. Example spatial data is available in the pRolocdata experiment package.

The pRoloc suite set of software are distributed as part of the R/Bioconductor project and are developed by Lisa Breckels at the Cambridge Centre for Proteomics at the University of Cambridge and by Laurent Gatto, director of the Computational Biology and Bioinformatics (CBIO) group at UCLouvain, in Belgium.

This document describes the installation of the software, followed by a basic quick start guide for using pRolocGUI to search and visualise spatial proteomics data. Please refer to the respective documentation and vignettes for full details about the software.

If you use these open-source software for your research, please cite:

Gatto L, Breckels LM, Wieczorek S, Burger T, Lilley KS. Mass-spectrometry-based spatial proteomics data analysis using pRoloc and pRolocdata. Bioinformatics. 2014 May 1;30(9):1322-4. doi:10.1093/bioinformatics/btu013. Epub 2014 Jan 11. PMID:24413670; PMCID:PMC3998135.

Breckels LM, Gatto L, Christoforou A, Groen AJ, Lilley KS, Trotter MW. The effect of organelle discovery upon sub-cellular protein localisation. J Proteomics. 2013 Mar 21. doi:pii: S1874-3919(13)00094-8. 10.1016/j.jprot.2013.02.019. PMID:23523639.

Gatto L., Breckels L.M., Burger T, Nightingale D.J.H., Groen A.J., Campbell C., Mulvey C.M., Christoforou A., Ferro M., Lilley K.S. 'A foundation for reliable spatial proteomics data analysis' Mol Cell Proteomics. 2014 May 20.

Installation

pRolocGUI is written in the R programming language. Before installing the software you need to download R and (optionally) RStudio.

1) Download the latest R release for your operating system from the R website and install it.

2) Optional, but recommended. Download and install the RStudio IDE. RStudio provides a good code editor and excellent integration with the R terminal.

3) Start R or RStudio.

4) Install the Bioconductor packages pRoloc, pRolocdata and pRolocGUI:

pRolocGUI requires R >= 3.1.1 and Bioconductor version >= 3.0. In an R console, type

if (!requireNamespace("BiocManager", quietly=TRUE)) install.packages("BiocManager") BiocManager::install(c("pRoloc", "pRolocdata", "pRolocGUI"))

Development version

The development code on github can also be installed using BiocManager::install (or install_github). New pre-release features might not be documented or thoroughly tested and could substantially change prior to release. Use at your own risks.

BiocManager::install("ComputationalProteomicsUnit/pRolocGUI")

Getting started

Before using a package's functionality, it needs to be loaded:

library("pRolocGUI")

We first load data from Christoforou et al 2016 distributed in the pRolocdata package:

library("pRolocdata") data(hyperLOPIT2015)

There are 3 different visualisation applications currently available: explore, compare and aggregate. These apps are launched using the pRolocVis function and passing object, which is an MSnSet containing the data one wishes to interrogate. One may also specify which app they wish to use by using the app argument, see ?pRolocVis for more details. The default app that is loaded if app is not specified is the explore application:

pRolocVis(hyperLOPIT2015)

Screenshot - PCA

The graphical interface is described in details in the package vignette that is included in the package itself (get it by typing vignette("pRolocGUI") in R), available by clicking the ? once the interface is loaded or can be consulted online.

More resources

Support

  • The Bioconductor support forum
  • Open a pRolocGUI GitHub issue (requires a free GitHub account).

Videos (new videos will appear shortly for the new apps)

  1. An introduction to Bioconductor
  2. A brief introduction to pRolocGUI
  3. Downloading and install R
  4. Using RStudio
  5. Installing the pRolocGUI interface
  6. Starting pRolocGUI - This tutorial is for the older legacy applications. New videos will appear shortly for the new applications.
  7. Using pRolocGUI to explore and visualise experimental spatial proteomics data - This tutorial is for the older legacy applications. New videos will appear shortly for the new applications.

Tutorial playlist.

General resources

Owner

  • Name: Laurent Gatto
  • Login: lgatto
  • Kind: user
  • Location: Belgium
  • Company: de Duve Institute, UCLouvain

Open science, reproducible research, bioinformatics, computational biology, proteomics, more omics, emacs, a lot of R, running and parenting.

GitHub Events

Total
  • Issues event: 1
  • Watch event: 1
  • Delete event: 2
  • Push event: 10
  • Pull request event: 1
  • Create event: 1
Last Year
  • Issues event: 1
  • Watch event: 1
  • Delete event: 2
  • Push event: 10
  • Pull request event: 1
  • Create event: 1

Committers

Last synced: 9 months ago

All Time
  • Total Commits: 1,209
  • Total Committers: 24
  • Avg Commits per committer: 50.375
  • Development Distribution Score (DDS): 0.688
Past Year
  • Commits: 13
  • Committers: 4
  • Avg Commits per committer: 3.25
  • Development Distribution Score (DDS): 0.538
Top Committers
Name Email Commits
*tnaake* t****e@g****e 377
Laurent l****0@c****k 233
lmsimp l****p@g****m 214
l.gatto l****o@b****8 128
Laurent Gatto l****o@d****e 120
Laurent Gatto l****o@u****e 44
Lisa Breckels l****a@L****e 21
Nitesh Turaga n****a@g****m 14
d.tenenbaum d****m@b****8 14
Dan Tenenbaum d****a@f****g 11
J Wokaty j****y@s****u 10
hpages@fhcrc.org h****s@f****g@b****8 4
Herve Pages h****s@f****g 4
vobencha v****a@g****m 2
Hervé Pagès h****s@f****g 2
vobencha v****n@r****g 2
A Wokaty a****y@s****u 2
pierremj p****j@p****u 1
m.carlson m****n@b****8 1
Marc Carlson m****n@f****g 1
James Hester j****r@f****g 1
*tnaake* *****e@g****e 1
LiNk-NY m****9@g****m 1
j.hester j****r@b****8 1
Committer Domains (Top 20 + Academic)
fhcrc.org: 4 fredhutch.org: 2 sph.cuny.edu: 2 gmx.de: 2 princeton.edu: 1 roswellpark.org: 1 lisas-air.home: 1 uclouvain.be: 1 dnavision.be: 1 cam.ac.uk: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 114
  • Total pull requests: 7
  • Average time to close issues: 6 months
  • Average time to close pull requests: about 2 hours
  • Total issue authors: 9
  • Total pull request authors: 2
  • Average comments per issue: 2.11
  • Average comments per pull request: 0.86
  • Merged pull requests: 6
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 2
  • Pull requests: 1
  • Average time to close issues: 20 days
  • Average time to close pull requests: less than a minute
  • Issue authors: 2
  • Pull request authors: 1
  • Average comments per issue: 1.5
  • Average comments per pull request: 0.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • lmsimp (64)
  • lgatto (34)
  • Kohze (4)
  • tnaake (3)
  • blue-moon22 (3)
  • dan-night-89 (2)
  • kbarylyuk (2)
  • rdogra8 (1)
  • TomSmithCGAT (1)
Pull Request Authors
  • lmsimp (6)
  • pierremj (2)
Top Labels
Issue Labels
bug (14) enhancement (8) feature request (1)
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • bioconductor 24,801 total
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 5
  • Total maintainers: 1
bioconductor.org: pRolocGUI

Interactive visualisation of spatial proteomics data

  • Versions: 5
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 24,801 Total
Rankings
Dependent repos count: 0.0%
Dependent packages count: 0.0%
Average: 12.7%
Downloads: 38.1%
Maintainers (1)
lms79@cam.ac.uk
Last synced: 6 months ago

Dependencies

DESCRIPTION cran
  • Biobase * depends
  • MSnbase >= 2.1.11 depends
  • R >= 3.1.0 depends
  • methods * depends
  • pRoloc >= 1.27.6 depends
  • BiocGenerics * imports
  • DT >= 0.1.40 imports
  • colorspace * imports
  • colourpicker * imports
  • dplyr * imports
  • ggplot2 * imports
  • grDevices * imports
  • graphics * imports
  • grid * imports
  • scales * imports
  • shiny >= 0.9.1 imports
  • shinyWidgets * imports
  • shinydashboard * imports
  • shinydashboardPlus >= 2.0.0 imports
  • shinyhelper * imports
  • shinyjs * imports
  • stats * imports
  • utils * imports
  • BiocStyle >= 2.5.19 suggests
  • knitr * suggests
  • pRolocdata * suggests
  • rmarkdown * suggests