If you want to perform “omics”-like analyses you probably need to upload data (resources). By default Armadillo supports file uploads up to 500MB. If you need to upload larger resources, please contact molgenis-support@umcg.nl.
There are 2 roles you can assume using the package. The datamanager role and the researcher role.
Datamanager
The datamanager needs to make the data available to the researchers. Besides this you need to create the resources to access the data.
Researcher
The researcher can call DataSHIELD analysis methods on the data uploaded by the datamanager.
Upload the data
As a datamanager you need to access the Armadillo webinterface to be able to access the resource.
- We are using data from the following sources:
- https://github.com/isglobal-brge/brge_data_large/blob/master/data/gse66351_1.rda
- https://github.com/isglobal-brge/brge_data_large/blob/master/data/gse66351_2.rda
- Login with your institute account.
- Create a project. For example
omics. - Click on the edit project button to the right of the name of your project.
- Create a new folder for your data. For example
ewas. - Click on the “Select a file to upload” button or drag your file to upload to the box and click on “Upload”. Upload the omics data.
Upload the resources (in Rstudio)
A second option to upload data (resources) is on the Central Analysis Server
(CAS) within Rstudio As datamanager you first need to login to
Armadillo (as superuser)
armadillo.login("https://armadillo-demo.molgenis.net/")Install prerequisites
If you want to install a package on the Armadillo Rserver you can
execute the following. The selected profile is always
default if none is specified. If your profile doesn’t have
the resourcer package installed, install it:
library(resourcer)
#> Loading required package: R6
#> Loading required package: httr
#> Registering LocalFileResourceGetter...
#> Registering HttpFileResourceGetter...
#> Registering ScpFileResourceGetter...
#> Registering GridFsFileResourceGetter...
#> Registering OpalFileResourceGetter...
#> Registering MariaDBResourceConnector...
#> Registering PostgresResourceConnector...
#> Registering SparkResourceConnector...
#> Registering PrestoResourceConnector...
#> Registering TidyFileResourceResolver...
#> Registering ShellResourceResolver...
#> Registering SshResourceResolver...
#> Registering RDataFileResourceResolver...
#> Registering RDSFileResourceResolver...
#> Registering SQLResourceResolver...
#> Registering NoSQLResourceResolver...Create resources
In order to be able to assign the data uploaded in the armadillo you
need to create the resources as well. The data files you uploaded to
armadillo, can be retrieved via the following URL:
yoururl + /storage/projects/{project name}/objects/{folder name}%2F{filename}
an example is:
https://armadillo-demo.molgenis.net/storage/projects/omics/objects/ewas%2Fgse66351_1.rda.
Here the URL is https://armadillo-demo.molgenis.net/, the
project name is omics, the folder is ewas and
the name of the data file is gse66351_1.rda.
resGSE1 <- resourcer::newResource(
name = "GSE66351_1",
url = "https://armadillo-demo.molgenis.net/storage/projects/omics/objects/ewas%2Fgse66351_1.rda",
format = "ExpressionSet"
)
resGSE2 <- resourcer::newResource(
name = "GSE66351_1",
url = "https://armadillo-demo.molgenis.net/storage/projects/omics/objects/ewas%2Fgse66351_1.rda",
format = "ExpressionSet"
)
armadillo.upload_resource(project="omics", folder="ewas", resource = resGSE1, name = "GSE66351_1")
#> Compressing...
#> Uploaded ewas/GSE66351_1
armadillo.upload_resource(project="omics", folder="ewas", resource = resGSE2, name = "GSE66351_2")
#> Compressing...
#> Uploaded ewas/GSE66351_2The data is now available for researcher to assign.