The VectraPolarisData ExperimentHub package provides two large multiplex immunofluorescence datasets collected by Akoya Biosciences Vectra 3 and Vectra Polaris platforms. Image preprocessing (cell segmentation and phenotyping) was performed using Inform software. Data cover are formatted into objects of class SpatialExperiment.
VectraPolarisData 1.10.0
To retrieve a dataset, we can use a dataset’s corresponding named function <id>(), where <id> should correspond to one a valid dataset identifier (see ?VectraPolarisData). Below both the lung and ovarian cancer datasets are loaded this way.
library(VectraPolarisData)
spe_lung <- HumanLungCancerV3()
spe_ovarian <- HumanOvarianCancerVP()Alternatively, data can loaded directly from Bioconductor’s ExperimentHub as follows. First, we initialize a hub instance and store the complete list of records in a variable eh. Using query(), we then identify any records made available by the VectraPolarisData package, as well as their accession IDs (EH7311 for the lung cancer data). Finally, we can load the data into R via eh[[id]], where id corresponds to the data entry’s identifier we’d like to load. E.g.:
library(ExperimentHub)
eh <- ExperimentHub() # initialize hub instance
q <- query(eh, "VectraPolarisData") # retrieve 'VectraPolarisData' records
id <- q$ah_id[1] # specify dataset ID to load
spe <- eh[[id]] # load specified datasetBoth the HumanLungCancerV3() and HumanOvarianCancerVP() datasets are stored as SpatialExperiment objects. This allows users of our data to interact with methods built for SingleCellExperiment, SummarizedExperiment, and SpatialExperiment class methods in Bioconductor. See this ebook for more details on SpatialExperiment. To get cell level tabular data that can be stored in this format, raw multiplex.tiff images have been preprocessed, segmented and cell phenotyped using Inform software from Akoya Biosciences.
The SpatialExperiment class was originally built for spatial transcriptomics data and follows the structure depicted in the schematic below (Righelli et al. 2021):