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PolySTest

PolySTest: Statistical testing with missing values

https://github.com/computproteomics/polystest

Science Score: 26.0%

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    CITATION.cff file
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    Found 2 DOI reference(s) in README
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    Low similarity (13.9%) to scientific vocabulary
Last synced: 7 months ago · JSON representation

Repository

PolySTest: Statistical testing with missing values

Basic Info
Statistics
  • Stars: 0
  • Watchers: 2
  • Forks: 0
  • Open Issues: 2
  • Releases: 0
Created about 2 years ago · Last pushed 7 months ago
Metadata Files
Readme Changelog License

README.md

Conda Version bio.tools

Welcome to the repository of PolySTest developed at the Protein Research Group
Department of Biochemistry and Molecular Biology
University of Southern Denmark

Citation

When using PolySTest, please cite our paper:
Veit Schwämmle, Christina E Hagensen, Adelina Rogowska-Wrzesinska, and Ole N. Jensen, doi: https://doi.org/10.1074/mcp.RA119.001777

PolySTest can be run as shiny app on our server or using the docker version of the tool to avoid installation issues and computational bottlenecks.

A command-line version is available to run PolySTest as workflow component (see below).

Shiny app

Web service

You can use our web server http://computproteomics.bmb.sdu.dk:

http://computproteomics.bmb.sdu.dk/Apps/PolySTest

Be aware that the tool does allow only one user to run the background R calculations at a time. Therefore the app might become temporarily irresponsive. However, multiple sessions are separated and your data won't be shared between sessions or overwritten.

Implementation on own computer

The easiest option is to use the docker image or as bioconda package.

Docker

docker pull veitveit/polystest

docker run -t -i -p 3838:3838 veitveit/polystest

and access the shiny app through http://localhost:3838

Bioconda

Install the package

conda install -c bioconda polystest

run_app.sh

and access the shiny app through http://localhost:3838

Installation

Download the files from this repository

Install the following R libraries in R: library(BiocManager) BiocManager::install(c('matrixStats','fdrtool','parallel','qvalue','circlize','DT','UpSetR','heatmaply','gplots','shinyBS','shinydashboard','limma'),ask=F)

You can run the shiny app from the server.R or ui.R files using Rstudio or run the app on a shiny-server

Alternatively, just (in Linux) call the script run_app.sh and access the app through http://localhost:3838

Be aware that you need to have all files and all necessary R libraries described in the Installation

Build and use Docker image

A Dockerfile has been created on the basis of an OpenSuse distribution. Copy the repository to a folder and carry out the following command to build the images (takes a while)

docker build -t veitveit/polystest .

You can run the image by

docker run -t -i -p 3838:3838 veitveit/polystest

and access the server through http://localhost:3838

Command-line version

You can run PolySTest via the file runPolySTestCLI.R. You need to specify a parameter file (yaml) to set parameters and the input file. See polystest.yml for an example and extensive description of the parameters

Installation

The command-line version comes with all version of PolySTest.

Contact

For software issues and general questions, please submit an issue.

License

GPL-2 or higher

Owner

  • Name: Computational Proteomics Group at University of Southern Denmark
  • Login: computproteomics
  • Kind: organization

Here organize our tool development.

GitHub Events

Total
  • Issues event: 2
  • Issue comment event: 1
  • Push event: 22
  • Pull request event: 2
  • Create event: 1
Last Year
  • Issues event: 2
  • Issue comment event: 1
  • Push event: 22
  • Pull request event: 2
  • Create event: 1

Issues and Pull Requests

Last synced: 7 months ago

All Time
  • Total issues: 2
  • Total pull requests: 2
  • Average time to close issues: N/A
  • Average time to close pull requests: 1 minute
  • Total issue authors: 2
  • Total pull request authors: 1
  • Average comments per issue: 0.5
  • Average comments per pull request: 0.0
  • Merged pull requests: 2
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 2
  • Pull requests: 2
  • Average time to close issues: N/A
  • Average time to close pull requests: 1 minute
  • Issue authors: 2
  • Pull request authors: 1
  • Average comments per issue: 0.5
  • Average comments per pull request: 0.0
  • Merged pull requests: 2
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • santoshdbhosale (1)
  • Arthfael (1)
Pull Request Authors
  • veitveit (3)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • bioconductor 2,211 total
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 3
  • Total maintainers: 1
bioconductor.org: PolySTest

PolySTest: Detection of differentially regulated features. Combined statistical testing for data with few replicates and missing values

  • Versions: 3
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 2,211 Total
Rankings
Dependent repos count: 0.0%
Dependent packages count: 31.5%
Average: 42.3%
Downloads: 95.5%
Maintainers (1)
veits@bmb.sdu.dk
Last synced: 7 months ago

Dependencies

.github/workflows/R-CMD-check.yaml actions
  • actions/checkout v4 composite
  • r-lib/actions/check-r-package v2 composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite
.github/workflows/docker-image.yml actions
  • actions/checkout v2 composite
  • docker 19.03.12 docker
.github/workflows/test-coverage.yaml actions
  • actions/checkout v4 composite
  • actions/upload-artifact v4 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite
DESCRIPTION cran
  • R >= 4.3.0 depends
  • S4Vectors >= 0.30.0 imports
  • SummarizedExperiment >= 1.20.0 imports
  • UpSetR >= 1.4.0 imports
  • circlize >= 0.4.12 imports
  • fdrtool >= 1.2.15 imports
  • gplots >= 3.1.1 imports
  • heatmaply >= 1.1.1 imports
  • knitr >= 1.33 imports
  • limma >= 3.44.3 imports
  • matrixStats >= 0.57.0 imports
  • parallel >= 4.1.0 imports
  • plotly >= 4.9.4 imports
  • qvalue >= 2.22.0 imports
  • shiny >= 1.5.0 imports
  • knitr >= 1.33 suggests
  • testthat >= 3.0.0 suggests
Dockerfile docker
  • rocker/shiny latest build