https://github.com/noedemange/nspcaview

App Shiny : Optimised matrix visualization of Non-negative Sparse PCA components.
https://github.com/noedemange/nspcaview

nspca pca pca-analysis r rstats shiny shiny-apps visualization

Last synced: 15 days ago
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App Shiny : Optimised matrix visualization of Non-negative Sparse PCA components.

• Host: GitHub
• URL: https://github.com/noedemange/nspcaview
• Owner: NoeDemange
• License: other
• Created: 2022-12-22T10:50:49.000Z (about 2 years ago)
• Default Branch: main
• Last Pushed: 2023-10-29T20:18:34.000Z (about 1 year ago)
• Last Synced: 2024-11-11T21:34:50.458Z (2 months ago)
• Topics: nspca, pca, pca-analysis, r, rstats, shiny, shiny-apps, visualization
• Language: R
• Homepage:
• Size: 229 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.Rmd
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md

Awesome Lists containing this project

README

        
---

output: github_document

---

```{r, include = FALSE}

knitr::opts_chunk$set(

  collapse = TRUE,

  comment = "#>",

  fig.path = "man/figures/README-",

  out.width = "100%"

)

```

# nspcaview

[![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#experimental)

Optimised matrix visualization of Non-negative Sparse PCA components.

## Installation

You can install the development version of nspcaview from [GitHub](https://github.com/) with:

``` r

# install.packages("devtools")

devtools::install_github("NoeDemange/NSPCAview")

```

## Example

This is a basic example which shows you how to run the app:

```{r example}

library(nspcaview)

nspcaview::run_app(options=list("launch.browser"=TRUE))

```

## Credits

This app was developed by [Noe Demange](https://github.com/NoeDemange).

It was developed for and is maintained by [Guillaume Sapriel](https://orcid.org/0000-0003-0549-9376).

It is deployed on the [MIGALE platform](https://migale.inrae.fr/) by [Cédric Midoux](https://orcid.org/0000-0002-7964-0929). We are grateful to the INRAE MIGALE bioinformatics facility (MIGALE, INRAE, 2020. Migale bioinformatics Facility, doi: 10.15454/1.5572390655343293E12) for providing help and storage resources.