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 ImmuneSpace database to hide all the Rlabkey specific code away from the user.
Study-specific datasets can be accessed via an object-oriented paradigm.
The package can be downloaded here and installed like any other R packages or installed directly from github using devtools.
library(devtools)
install_github("RGLab/ImmuneSpaceR")The database is accessed with the user's credentials. A .netrc file storing login and password information is required.
Create netrc file in the computer running R.
- On a UNIX system this file should be named
.netrc(dotnetrc) - On windows it sould be named
_netrc(underscorenetrc). - The file should be located in the users home directory and the permissions
on the file should be unreadable for everybody except the owner. To determine
home directory, run
Sys.getenv("HOME")in R.
The following three lines must be included in the .netrc or _netrc file either separated by white space (spaces, tabs, or newlines) or commas.
machine www.immunespace.org
login [email protected]
password supersecretpassword
Multiple such blocks can exist in one file.
Please ensure that the machine name in the netrc file contains the "www" prefix as that is how the package connects to immunespace by default. A mismatch will lead to connection failures.
See man netrc for the official documentation and the User guide vignette for an
ImmuneSpace specific setup.
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:
study <- CreateConnection("SDY269")will create an instance of study 269. The user needs credentials stored in a .netrc file to access the database.
Datasets can be listed by:
study$listDatasets()which will print names of available datasets and gene expression matrices.
Gene expression matrices or data sets can be retreived by:
study$getGEMatrix("name")
# or
study$getDataset("name")The study object caches data, so once it is retrieved, the next time you access it, it will use the local cached copy.
The package uses a simple S5 reference class to represent the connection to a study and get around some of R's copy-on-change behaviour.
The quick_plot function uses ggplot2's qplot function to generate quick plots of data sets, leveraging the standardized data set tables.
study$quick_plot("hai")
For more advanced examples and detailed documentation, see the package vignettes and the reports available on ImmuneSpace.