dssurvival_bookdown

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

https://github.com/neelsoumya/dssurvival_bookdown

Science Score: 41.0%

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    Links to: biorxiv.org
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Keywords

cox-regression datashield dssurvival dssurvivalclient r survival-analysis survival-models
Last synced: 6 months ago · JSON representation ·

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

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Topics
cox-regression datashield dssurvival dssurvivalclient r survival-analysis survival-models
Created over 4 years ago · Last pushed over 3 years ago
Metadata Files
Readme Contributing Funding License Citation

README.md

Introduction

License

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/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/dsSurvival_bookdown/

Full Installation

  • Install R and R Studio

  • In R, install the following packages

```r

install.packages('devtools') library(devtools) devtools::installgithub('neelsoumya/dsSurvivalClient') install.packages('bookdown') devtools::installgithub('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

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} }

Owner

  • Name: Soumya Banerjee
  • Login: neelsoumya
  • Kind: user
  • Location: Cambridge, UK
  • Company: University of Cambridge

My research interests are in complex systems data science, machine learning, computational biology, computational immunology and computational immunogenomics.

Citation (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}
}

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Dependencies

DESCRIPTION cran
  • DSI * imports
  • DSOpal * imports
  • bookdown * imports
  • dsBaseClient * imports
  • knitr * imports
  • meta * imports
  • metafor * imports
  • opalr * imports
  • rmarkdown * imports
  • survival * imports
  • tinytex * imports