Introduction

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/dsSurvivalbookdown

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

@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/dsSurvivalbookdown

Quick start

Please install R and R Studio

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

Install the following packages:

install.packages('devtools')
library(devtools)
devtools::install_github('neelsoumya/dsSurvivalClient')
devtools::install_github('datashield/dsBaseClient@6.1.1')
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/dsSurvivalbookdown/

Full Installation

• Install R and R Studio

• In R, install the following packages

  
  install.packages('devtools')
  library(devtools)
  devtools::install_github('neelsoumya/dsSurvivalClient')
  install.packages('bookdown')
  devtools::install_github('datashield/dsBaseClient@6.1.1')
  install.packages('rmarkdown')
  install.packages('knitr')
  install.packages('tinytex')
  install.packages('metafor')  
  install.packages('DSOpal')
  install.packages('DSI')
  install.packages('opalr')
  

or

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/dsSurvivalbookdown

A minimal example of a book based on R Markdown and bookdown (https://github.com/rstudio/bookdown).

The bookdown can be compiled by typing the following commands:

library(bookdown)

bookdown::serve_book()

Contact

Soumya Banerjee and Tom R.P. Bishop

sb2333@cam.ac.uk

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

@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}
}