dssurvivalbookdown

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

https://github.com/neelsoumya/dssurvivalbookdown

Science Score: 67.0%

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    Links to: biorxiv.org
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Keywords

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

Repository

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

Basic Info
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  • Stars: 3
  • Watchers: 3
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  • Releases: 4
Topics
cox-regression datashield dssurvival dssurvivalclient privacy-protection r survival-models
Created about 4 years ago · Last pushed over 3 years ago
Metadata Files
Readme Changelog 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/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

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/dsSurvivalbookdown

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::installgithub('neelsoumya/dsSurvivalClient') 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')

```

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

```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/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:

```r

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

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.cff)

# YAML 1.2
---
authors: 
  -
    family-names: Banerjee
    given-names: Soumya
    orcid: "https://orcid.org/0000-0001-7748-9885"
  -
    family-names: Sofack
    given-names: Ghislain
  -
    family-names: Papakonstantinou
    given-names: Thodoris
  -
    family-names: Avraam
    given-names: Demetris  
  -
    family-names: Paul
    given-names: Burton   
  -
    family-names: Daniella
    given-names: Zoeller  
  -
    family-names: Bishop
    given-names: Tom
cff-version: "1.0.0"
doi: "10.1101/2022.01.04.471418"
message: "If you use this software, please cite it using these metadata: dsSurvival: Privacy preserving survival models for federated individual patient meta-analysis in DataSHIELD, Soumya Banerjee, Ghislain Sofack, Thosoris Papakonstantinou, Demetris Avraam, Paul Burton et al., BMC Research Notes, 15(1), 2022 "
title: "dsSurvival: Privacy preserving survival models for federated individual patient meta-analysis in DataSHIELD"
...

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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