dssurvivalbookdown
A bookdown demonstrating how to build survival models using the dsSurvival package in DataSHIELD
Science Score: 67.0%
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Keywords
Repository
A bookdown demonstrating how to build survival models using the dsSurvival package in DataSHIELD
Basic Info
- Host: GitHub
- Owner: neelsoumya
- License: gpl-3.0
- Language: TeX
- Default Branch: main
- Homepage: https://neelsoumya.github.io/dsSurvivalbookdown/
- Size: 829 KB
Statistics
- Stars: 3
- Watchers: 3
- Forks: 0
- Open Issues: 0
- Releases: 4
Topics
Metadata Files
README.md
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
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
- Website: https://sites.google.com/site/neelsoumya/
- Repositories: 249
- Profile: https://github.com/neelsoumya
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
- DSI * imports
- DSOpal * imports
- bookdown * imports
- dsBaseClient * imports
- knitr * imports
- meta * imports
- metafor * imports
- opalr * imports
- rmarkdown * imports
- survival * imports
- tinytex * imports