SPATAData - A database for spatial transcriptomic datasets • SPATA2

The package SPATAData simplifies access to our data base of spatial transcriptomic samples.

# install the package with...
devtools::install_github("theMILOlab/SPATAData")

# load package
library(SPATAData)

1. Interactive downloads

The simplest way to access spatial transcriptomic data sets is by using the function launchSpataData(). It opens an interactive application in which all samples that we currently provide are displayed. You can conveniently look up and filter for characteristics such as species, organ, pathology, WHO grades in case of malignancies, organization etc.

# load package
library(SPATAData)

# open the application
launchSpataData()

Be patient. It might take a few moments for the app to load. Once the app has loaded you can use the tab ‘Tissue-Organs’ to skim the organs for which spatial transcriptomic datasets are available.

Fig.1 Displaying healthy brain samples that are available.

Using the filter options in the header above you subset all available samples for those that fit the characteristics you are interested in.

Fig.2 Displaying pathological brain samples that fit the filter characteristics.

Clicking on the button ‘SPATA2’ below every sample downloads the respective sample in form of a spata2 object. ‘Visualize’ downloads it right in the app where you can visualize its surface in combination with gene or gene set expression.

2. Manual downloads and other functions

To manually download spata2 objects use the following functions:

# downloads object and assign it to the gloabl environment
# file = NULL skips saving it 
object <- downloadSpataObject(sample_name = "275_T", file = NULL)

# download several samples at the same time
downloadSpataObjects(sample_names = c("275_T", "313_T"), folder = "my_spata_folder")

Additional functions:

# obtain all sample names 
validSampleNames()

# check how to cite if you have used a sample for your publication
getCitation(object)