Introduction
Recent advancements in single-cell sequencing have transformed our ability to characterize immune cells at unprecedented resolution. Pharmaceutical and Biotech scientists routinely collect data at a single-cell level on everything from protein expression, transcriptomics, epigenetics, immune receptor diversity, and metabolic states during R&D. However, integrating multiple single-cell omics datasets and making sense of their relationships remains a challenge- especially for those without bioinformatics expertise. Enter scImmOmics, a manually curated database designed to address this gap. Using a simple GUI, scImmOmics allows for the benchtop researcher to begin to perform these complex computational tasks without the need for bioinformatics hand-holding.
What is scImmOmics?
scImmOmics is a powerful resource that consolidates scRNA-seq, scTCR-seq, scBCR-seq, scATAC-seq, and CITE-seq from publicly available immune datasets. By harmonizing these datasets, scImmOmics provides researchers with a structured, hierarchical view of 131 immune cell types across 47 tissues and four species. This database can be harnessed to investigate questions around immune diversity, clonal expansion, regulatory mechanisms, and immune responses to cytokines.
Implementing scImmOmics in Research
The scImmOmics database is accessible online and supports flexible search functions based on tissue type, immune cell type, and disease status. Researchers can:
1. Browse datasets to identify relevant studies.
2. Download curated datasets to probe their research question of interest.
3. Compare immune cell populations across conditions to better understand their disease of interest.
4. Use differential gene enrichment analysis to determine which immune cells significantly express genes of interest.
Use Case 1: Searching for Datasets by Tissue Type, Disease, or Cell Type
scImmOmics provides a powerful browser-based search tool that allows users to quickly locate datasets based on:
· Tissue type (e.g., lung, bone marrow, skin, blood)
· Disease status (e.g., COVID-19, autoimmune disorders, cancer)
· Cell type (e.g., T cells, B cells, macrophages)
By refining their search criteria, users can identify specific datasets tailored to their research questions and explore detailed immune cell information, including functional annotations and regulatory states.
Use Case 2: Differential Gene Analysis
scImmOmics allows users to identify differentially expressed genes for each cell type to serve as a reference set for enrichment analysis. Alternatively, researchers can submit a gene list of interest, set thresholds for P-values or FDRs, and scImmOmics will display the immune cells where these genes are enriched. This feature is useful for identifying immune cell types relevant to specific gene signatures and providing insights into immune responses in various conditions.
Use Case 3: Integrating Two Different Datasets to Understand Regulatory Analysis
ScImmOmics provides integration of two different types of data. For example, by combining scRNA-seq and scATAC-seq data, to gain a deeper understanding of gene expression and regulatory elements. Integration provides a multi-dimensional view of immune regulation, helping researchers dissect immune cell states and their regulatory landscapes in disease progression and therapeutic interventions.
Conclusion
scImmOmics is a great resource for immunologists, bioinformaticians, and clinical researchers seeking to understand immune cell heterogeneity at the single-cell level. By integrating multi-omics data with a well-structured annotation framework, it enables new discoveries in immune regulation, disease pathogenesis, and potential therapeutic strategies.
Outsourcing Bioinformatics Analysis: How Bridge Informatics (BI) Can Help
We are passionate about empowering life science companies with cutting-edge technologies. BI’s data scientists prioritize studying, understanding, and reporting on the latest developments, like ScImmOmics, so we can advise our clients confidently. Our bioinformaticians are trained bench biologists, so they understand the biological questions driving your computational analysis.
From pipeline development and software engineering to deploying your existing bioinformatic tools, BI can help you on every step of your research journey. As experts across data types from leading sequencing platforms, we can help you tackle the challenging computational tasks of storing, analyzing and interpreting genomic and transcriptomic data. Click here to schedule a free introductory call with a member of our team.
