Single-Cell Omics
About the Community
The Single-Cell Omics (SCO) Community aims to advance the study of biological phenomena and cellular heterogeneity by leveraging single-cell omics technologies.
These technologies offer exciting possibilities:
- Identifying rare cell types previously hidden within complex tissues.
- Investigating diverse cell states to understand how cells function and interact.
- Gaining insights into fundamental processes like development, gene expression, and disease progression at an unprecedented, cellular level.
The ELIXIR Single-Cell Omics Community is actively addressing these challenges through several key initiatives:
- Promoting data standardisation to ensure data from different studies can be compared and integrated.
- Developing benchmarking tools to assess the performance of new analysis methods.
- Providing computational resources to facilitate researchers' access to the power they need for complex data analysis.
- Organizing training programs to equip researchers with the necessary skills and knowledge to utilize these technologies effectively.
By tackling these critical areas, the ELIXIR Single-Cell Omics Community fosters international collaboration and empowers researchers to unlock the full potential of single-cell omics for groundbreaking discoveries.
Contribution of ELIXIR Italy
At the national level, the ELIXIR-IT SCO community, established in 2022, is actively working on several fronts:
- Developing benchmarks for SCO;
- Designing tools for detecting epitranscriptomic changes at the single-cell level;
- Organising training courses, with the first online course held in February 2023, attended by more than 80 participants;
- Surveying available methods for their registration in the bio.tools catalogue;
- Creating a Slack channel to exchange information about SCO software and datasets for benchmarking;
- Exploring OpenEBench for benchmarking SCO data analysis methods;
- Evaluating the computing needs for SCO data analyses;
- Promoting and disseminating the use of FAIR data and metadata standards for single-cell omics.

