Build Status codecov bioc bioc

A thin wrapper around Rlabkey to access the ImmuneSpace database from R.

This package simplifies access to the HIPC ImmuneSpace database for R programmers. It takes advantage of the standardization of the database to hide all the Rlabkey specific code away from the user. The study-specific datasets can be accessed via an object-oriented paradigm.


Install from Bioconductor:


Or install the latest development version via remotes:



The ImmuneSpace Portal can be accessed via ImmuneSpaceR with the user's credentials. A .netrc file storing login and password information is required.

  1. Register
  2. Create a netrc file with your ImmuneSpace credetntials using interactive_netrc() function in R:

If you're familiar with the command-line interface, see the introductory vignette.


Create a connection

The general idea is that the user creates an instance of an ImmuneSpaceConnection class. The instance configures itself to connect to a specific study, and datasets and gene expression matrices can be retrieved by name.

For example:

con <- CreateConnection("SDY269")

will create an instance of SDY269.

List datasets

Datasets can be listed by:

#> datasets
#>  gene_expression_files
#>  fcs_sample_files
#>  demographics
#>  elispot
#>  hai
#>  elisa
#>  pcr
#>  cohort_membership
#>  fcs_analyzed_result
#> Expression Matrices
#>  SDY269_PBMC_TIV_Geo
#>  SDY269_PBMC_LAIV_Geo

which will print names of available datasets and gene expression matrices.

Retrieve datasets

Gene expression matrices or datasets can be retreived by:

LAIV2008 <- con$getGEMatrix("SDY269_PBMC_LAIV_Geo")
#> Downloading matrix..
#> Constructing ExpressionSet
elisa <- con$getDataset("elisa")

The connection object caches data, so once it is retrieved, the next time you access it, it will use the local cached copy. The package uses a R6 class system to represent the connection to a study and get around some of R's copy-on-change behaviour.


The plot method uses ggplot2 functions to generate visualizations of datasets, leveraging the standardized dataset tables.


Examples & Documentation

For more advanced examples and detailed documentation, see the package vignettes and the reports available on ImmuneSpace.


If you'd like to report bugs/issues/feature requests or contribute to the package, please see the contributing guidelines and join our Slack workspace.

Try the ImmuneSpaceR package in your browser

Any scripts or data that you put into this service are public.

ImmuneSpaceR documentation built on Dec. 21, 2020, 2:01 a.m.