Visium Spatial Gene Expression is a popular spatial transcriptomics tool developed by 10x Genomics. Visium maps the whole transcriptome with morphological context in FFPE and fresh-frozen tissues, then generates two types of data: an H&E or immunofluorescence tissue image and sequencing data. While the technology has been widely used, down-stream exploratory platforms for Visium data are still limited.
In this blog, we would like to introduce a new option for exploring Visium spatial transcriptome data using C-DIAM Multi-Omics Studio by Pythia Biosciences.
What is C-DIAM Multi-Omics Studio?
C-DIAM Multi-Omics Studio is an SAAS analytics platform for multi-omics data analysis and integration. C-DIAM supports various data types including bulk and single-cell RNA-seq, spatial transcriptomics, proteomics, and metabolomics. Users can analyze individual datasets or combine insights across multiple datasets for a more comprehensive view.
Using C-DIAM for Visium spatial transcriptome data analysis
C-DIAM has recently incorporated a single-cell and spatial data explorer where users can interactively analyze their scRNA-seq, Visium, and Xenium data with a wide range of down-stream analytics.
Bridging external pipelines with interactive visualizations
Beside supporting standard Cell Ranger and Space Ranger outputs, C-DIAM is also compatible with Scanpy objects (.H5AD format). Scanpy is a popular open-source tool for analyzing single-cell and spatial transcriptomics data. The adaptation to Scanpy objects allows C-DIAM to read and visualize your Scanpy outputs, such as dimensionality reduction coordinates, clustering results, metadata, and normalized values.
Therefore, you have two possible ways to work with C-DIAM: (1) easily visualizing data and analysis results processed through other pipelines and tools by submitting Scanpy objects, or (2) running the entire QC and preprocessing pipeline with customizable parameters in C-DIAM. Both options are very lightweight and come in a user-friendly interface. The first option is very helpful if bioinformatics teams want to share their results with wet-lab scientists.
Data access from any place, flexible deployment, and easy collaboration
C-DIAM Multi-Omics Studio is web-based, meaning that you can work with the data anywhere without the need for installation. This flexibility also makes collaboration easier, as team members can access and work on the same shared data from different locations.
C-DIAM can easily be deployed behind a firewall, on a physical server, or on a private cloud.
Diving deeper into the data with gene colocalization, intercellular signaling, and other analytics
Current tools are limited in the capabilities to deeply analyze Visium spatial transcriptome data. C-DIAM supports comprehensive analysis of the data with different sets of downstream analytics and workflows. While it accommodates common analyses such as comparing gene expression and differential expression, you can also dig deeper into gene colocalization, enriched pathways, lists of targets for prioritization, lists of biomarkers for validation, bioactivity networks, intercellular signaling, ligand-receptor pair activities, and many more.
Visualizing and comparing expression levels across tissue slides with multi-slide view
A common question that we want to answer is whether there are any differences in the morphology and gene expression among patients, samples, conditions, etc. C-DIAM supports multi-slide experiments, allowing visualizations of multiple tissue slides in one place. This can be used to easily view and compare the morphology as well as gene expression between them using different analytics options such as gene queries, colocalization queries, and differential expression analysis.
Reducing the false positives by insight validation across different omics
Multiple omics layers, when combined, can complement each other and tell us so much more about the big picture of biology. For example, it has been known that changes in transcript levels may not necessarily correspond to similar changes in protein levels. So, for those who work on drug target discovery, it is critical to know if your candidate genes really trigger any protein activities. One way to do that is to combine transcriptomics and proteomics insights.
Since C-DIAM is a platform that tackles various types of omics data, one of the most powerful aspects of it is performing cross-omics analysis. C-DIAM supports summarizing insights across omics datasets to find the common patterns that happen among them, e.g. common enriched pathways, differentially expressed genes, targets, biomarkers, intercellular signals, and active ligand-receptor pairs.
In C-DIAM, you can simply pair a Visium spatial transcriptome dataset with a scRNA-seq dataset, a mass-spec proteomics dataset and a metabolomics dataset to explore the aggregate insights. This holistic approach provides a more comprehensive understanding of your biological systems, enabling deeper insights and more informed conclusions.
Cross-analysis with public data
C-DIAM is also incorporating several public omics databases for users to interactively access and pair with their in-house data. The databases cover more than 1,000 datasets from Visium spatial transcriptome, CosMx, scRNA-seq, bulk RNA-seq and mass spec proteomics from various repositories like Recount3, 10x Genomics, Cellxgene, GTEx, and NCI Proteomic Data Commons. The number of datasets is constantly growing.
Where can I find C-DIAM?
C-DIAM is a web-based platform and available via www.c-diam.com. Contact us to request a trial!
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