A DSI implementation for the MOLGENIS Armadillo DataSHIELD Service.

Overview

You can use DSMolgenisArmadillo to analyse data shared in MOLGENIS Armadillo servers using DataSHIELD. DataSHIELD allows execution of a subset of analysis methods available in R. Methods such as:

ds.mean() ds.glm() ds.lmerSLMA()

For more detailed documentation check: https://cran.datashield.org/.

Installation

You can install the released version of DSMolgenisArmadillo from CRAN with:

install.packages("DSI")
install.packages("DSMolgenisArmadillo")

Make sure you install the DataSHIELD client (dsBaseClient) to perform the actual analysis. This needs to be a client which is version 6.0.0 or higher.

# install the DataSHIELD client
install.packages("dsBaseClient", repos = c("http://cran.datashield.org", "https://cloud.r-project.org/"), dependencies = TRUE)

Usage

To use the DataSHIELD Armadillo client and perform analysis in DataSHIELD there a few basic steps you need to take.

Get a token from the ID server

# Load the necessary packages.
library(dsBaseClient)
library(DSMolgenisArmadillo)

# specify server url
armadillo_url <- "https://armadillo.dev.molgenis.org"

# get token from central authentication server
token <- armadillo.get_token(armadillo_url)

Build the login frame

You need to specify the project, the folder and the table name(s) you want to access.

# build the login dataframe
builder <- DSI::newDSLoginBuilder()
builder$append(server = "armadillo",
               url = armadillo_url,
               token = token,
               table = "gecko/2_1-core-1_0/nonrep",
               driver = "ArmadilloDriver")

# create loginframe
logindata <- builder$build()

Login and assign the data

Assigning the data means that you will assign the data to a symbol in the analysis environment.

# login into server
conns <- datashield.login(logins = logindata, symbol = "core_nonrep", variables = c("coh_country"), assign = TRUE)

Perform an analysis

DataSHIELD has a range of methods you can use to perform analysis. Check: the dsBaseClient documentation to see which methods are available.

# calculate the mean
ds.mean("core_nonrep$coh_country", datasources = conns)
# create a histogram
ds.histogram(x = "core_nonrep$coh_country", datasources = conns)

Documentation

Check the package documentation for details.

Armadillo 2

The newest version (2.x) of DSMolgenisArmadillo will be only compatible with Armadillo version 3. If you still use Armadillo 2, you should use the 1.4.1 version of DSMolgenisArmadillo You can install this specific version the following commands:

For windows:

packageurl <- "https://cran.rstudio.com/bin/windows/contrib/4.2/DSMolgenisArmadillo_1.4.1.zip"
install.packages(packageurl, repos=NULL, type="source")

For Mac:

packageurl <- "hhttps://cran.rstudio.com/bin/macosx/contrib/4.2/DSMolgenisArmadillo_1.4.1.tgz"
install.packages(packageurl, repos=NULL, type="source")

For Linux:

packageurl <- "https://cran.rstudio.com/src/contrib/DSMolgenisArmadillo_1.4.1.tar.gz"
install.packages(packageurl, repos=NULL, type="source")