Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/neelsoumya/dssurvival_bookdown

A bookdown demonstrating how to build survival models using the dsSurvival package in DataSHIELD
https://github.com/neelsoumya/dssurvival_bookdown

cox-regression datashield dssurvival dssurvivalclient r survival-analysis survival-models

Last synced: about 1 month ago
JSON representation

A bookdown demonstrating how to build survival models using the dsSurvival package in DataSHIELD

Host: GitHub
URL: https://github.com/neelsoumya/dssurvival_bookdown
Owner: neelsoumya
License: gpl-3.0
Created: 2021-08-04T07:35:30.000Z (over 3 years ago)
Default Branch: main
Last Pushed: 2022-06-27T05:40:27.000Z (over 2 years ago)
Last Synced: 2023-03-06T18:17:50.095Z (almost 2 years ago)
Topics: cox-regression, datashield, dssurvival, dssurvivalclient, r, survival-analysis, survival-models
Language: TeX
Homepage: https://neelsoumya.github.io/dsSurvival_bookdown
Size: 911 KB
Stars: 3
Watchers: 3
Forks: 0
Open Issues: 7
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- Funding: .github/FUNDING.yml
- License: LICENSE.md
- Citation: CITATION.bib

Awesome Lists containing this project

README

        
## Introduction

[![License](https://img.shields.io/badge/license-GPLv3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0.html)

This is a bookdown with executable code demonstrating how to use the dsSurvival package to create privacy preserving survival models in DataSHIELD. `dsSurvival` builds privacy preserving survival models.

DataSHIELD is a platform for federated analysis of private data. This package can be used to build survival models, Cox proportional hazards models or Cox regression models.

The complete bookdown is available here:

https://neelsoumya.github.io/dsSurvival_bookdown

DataSHIELD has a client-server architecture and this package has a client side and server side component.

  * The server side package is called `dsSurvival`:

      

      https://github.com/neelsoumya/dsSurvival

  * The client side package is called `dsSurvivalClient`:

      

      https://github.com/neelsoumya/dsSurvivalClient

If you use the code, please cite the following manuscript:

Banerjee S, Sofack G, Papakonstantinou T, Avraam D, Burton P, et al. (2022), dsSurvival: Privacy preserving survival models for federated individual patient meta-analysis in DataSHIELD, bioRxiv: 2022.01.04.471418.

https://www.biorxiv.org/content/10.1101/2022.01.04.471418v2

https://doi.org/10.1101/2022.01.04.471418

https://bmcresnotes.biomedcentral.com/articles/10.1186/s13104-022-06085-1

A bib file is available here:

https://github.com/neelsoumya/dsSurvival/blob/main/CITATION.bib

```bibtex

@article{Banerjee2022,

author = {Banerjee, Soumya and Sofack, Ghislain and Papakonstantinou, Thodoris and Avraam, Demetris and Burton, Paul and Z{\"{o}}ller, Daniela and Bishop, Tom RP},

doi = {10.1101/2022.01.04.471418},

journal = {bioRxiv},

month = {jan},

pages = {2022.01.04.471418},

publisher = {Cold Spring Harbor Laboratory},

title = {{dsSurvival: Privacy preserving survival models for federated individual patient meta-analysis in DataSHIELD}},

year = {2022}

}

```

## Bookdown

The complete bookdown, tutorial, vignette with executable code and synthetic data is available here:

https://neelsoumya.github.io/dsSurvival_bookdown

## Quick start

Please install R and R Studio 

   https://www.rstudio.com/products/rstudio/download/preview/

Install the following packages:

```r 

install.packages('devtools')

library(devtools)

devtools::install_github('neelsoumya/dsSurvivalClient')

devtools::install_github('datashield/[email protected]')

install.packages('rmarkdown')

install.packages('knitr')

install.packages('tinytex')

install.packages('metafor')

install.packages('DSOpal')

install.packages('DSI')

install.packages('opalr')

```

Follow the tutorial in bookdown format with executable code:

https://neelsoumya.github.io/dsSurvival_bookdown/

## Full Installation

* Install R and R Studio 

* In R, install the following packages

```r 

  

  install.packages('devtools')

  library(devtools)

  devtools::install_github('neelsoumya/dsSurvivalClient')

  install.packages('bookdown')

  devtools::install_github('datashield/[email protected]')

  install.packages('rmarkdown')

  install.packages('knitr')

  install.packages('tinytex')

  install.packages('metafor')

  install.packages('DSOpal')

  install.packages('DSI')

  install.packages('opalr')

  

  ```

  or

  ```r 

  R --no-save < installer_R.R

  

  ```

  

  or

  

  run the following script in R `installer_R.R`

  

 

 

 Install R Studio and the development environment as described below:

    https://data2knowledge.atlassian.net/wiki/spaces/DSDEV/pages/12943461/Getting+started

 Install the virtual machines as described below:

    https://data2knowledge.atlassian.net/wiki/spaces/DSDEV/pages/931069953/Installation+Training+Hub-+DataSHIELD+v6

    https://data2knowledge.atlassian.net/wiki/spaces/DSDEV/pages/1657634881/Testing+100+VM

    https://data2knowledge.atlassian.net/wiki/spaces/DSDEV/pages/1657634898/Tutorial+6.1.0+100+VM

 Install dsBase and dsSurvival on Opal server in the Virtual Machine (type neelsoumya/dsSurvival and main in the textboxes)

  

 

  

  

## Usage

See the bookdown below for a complete tutorial:

https://neelsoumya.github.io/dsSurvival_bookdown

A minimal example of a book based on R Markdown and **bookdown** (https://github.com/rstudio/bookdown). Please see the page "Get Started" at https://bookdown.org/home/about/ for how to compile this example.

The bookdown can be compiled by typing the following commands:

  ```r 

  

  library(bookdown)

  bookdown::serve_book()

  

  ```

## Contact

Soumya Banerjee and Tom R.P. Bishop

## Citation

If you use the code, please cite the following manuscript:

Banerjee S, Sofack G, Papakonstantinou T, Avraam D, Burton P, et al. (2022), dsSurvival: Privacy preserving survival models for federated individual patient meta-analysis in DataSHIELD, bioRxiv: 2022.01.04.471418.

https://www.biorxiv.org/content/10.1101/2022.01.04.471418v2

https://doi.org/10.1101/2022.01.04.471418

https://bmcresnotes.biomedcentral.com/articles/10.1186/s13104-022-06085-1

A bib file is available here:

https://github.com/neelsoumya/dsSurvival/blob/main/CITATION.bib

```bibtex

@article{Banerjee2022,

author = {Banerjee, Soumya and Sofack, Ghislain and Papakonstantinou, Thodoris and Avraam, Demetris and Burton, Paul and Z{\"{o}}ller, Daniela and Bishop, Tom RP},

doi = {10.1101/2022.01.04.471418},

journal = {bioRxiv},

month = {jan},

pages = {2022.01.04.471418},

publisher = {Cold Spring Harbor Laboratory},

title = {{dsSurvival: Privacy preserving survival models for federated individual patient meta-analysis in DataSHIELD}},

year = {2022}

}

```