A visualization interface for BRAIN single cell data, integrating transcriptomics, epigenomics and spatial assays - PROJECT SUMMARY / ABSTRACT
The BRAIN Initiative’s -omics data archive NeMO contains all the BICCN single cell single cell data, more
than one million files at the time of writing. However, no interactive visualization interface to inspect these
results is available and many researchers are not proficient enough with computational tools (download data,
convert, load, plot) to take advantage of the data in NeMO. This makes testing hypotheses by
non-computational researchers a lot harder than necessary but the input from these domain experts and their
knowledge about molecular processes and cell specification is crucial for the interpretation of the data.
Here, I propose to repeat for the single cell field what has made genome browsers a pillar of data sharing: a
standard file format and a visualization tool for it. A new format is a requirement, because in the era of cloud
technology and distributed archives, data is usually not stored locally anymore. Sub-second reaction times
from remote storage are necessary for visualization and possible but existing single cell file formats were not
designed for this access pattern. In addition, for NeMO, being able to keep all results of a single cell assay in
one defined structure makes data management and access easier. We will define such a format, it will
integrate all the main analysis results and will convert all existing processed data in NeMO (not the raw read
data) to the new format.
We will then make the data available for interactive exploration directly on the NeMO website via our UCSC
Cell Browser, which is already running on different University websites. It is actively used already by thousands
of researchers every month to visualize hundreds of single datasets that we collected at UCSC and has been
used for hundreds of scientific publications. We will extend our tool to provide direct support for the most recent
assay and analysis types, mainly ATAC, methylation and spatial transcriptomics imaging data and integrate the
UCSC Genome Browser for chromosome-level views and summaries. An improved split-screen mode will
allow visualizing both spatial and transcriptomic data at the same time. In addition, the Cell Browser will allow
users to run the most fundamental and well-known analysis algorithms on any subset of cells, with a focus on
fast response time so that researchers do not have to download the whole dataset to get differential genes,
dimensionality reduction or specific sub-clustering results of a few selected cell clusters of interest.
Integrating these software features and the NeMO data into a single user-friendly environment will make
sure that the BICCN -omics data can be accessed as easily as possible, which will help accelerate the path to
discovery from the wealth of BRAIN single cell datasets being produced right now and in the future.
