Single-Cell Support
The OncoMark tool is specifically designed for bulk transcriptomics data and is not directly applicable to raw single-cell RNA-seq (scRNA-seq) datasets, since Hallmarks represent coordinated biological programs best captured at the population level.
However, if you are working with single-cell transcriptomic data from patient samples, there are several strategies to adapt OncoMark or Hallmark analysis for meaningful interpretation:
1. Pseudo-Bulk Aggregation (Per Patient)
If your goal is to assess Hallmark activity per patient, you should:
- Aggregate gene expression by summing the expression values of each gene across all cells within each patient sample.
- This creates a pseudo-bulk profile that mimics a bulk transcriptome.
- You can then apply OncoMark to these pseudo-bulk profiles to estimate Hallmark pathway activity at the patient level.
2. Cluster-Level Analysis (Within Sample)
If your goal is to analyze specific groups or clusters of cells (e.g., T cells, macrophages, tumor subtypes) within a sample:
- Perform clustering or cell type or state annotation.
- Aggregate gene expression by summing the expression values of each gene across all cells within each cluster.
- Apply OncoMark to the aggregated profile of each cluster to estimate Hallmark pathway activity for that specific cell group or population.
3. Single-Cell Level Scoring (Digital Scores)
If you need to assign Hallmark activity scores to individual cells, use a method designed for single-cell data, such as:
- UCell: A rank-based scoring method robust to scRNA-seq sparsity and dropout.
- Use the curated Hallmark gene sets provided in the
data/directory of the GitHub repository. - Scripts for computing UCell scores using both Python and R are available in the
src/directory of the same repository.
This approach enables you to evaluate Hallmark signature activity at single-cell resolution, suitable for downstream tasks.
Summary
| Use Case | Method | Tool |
|---|---|---|
| Per-patient Hallmark activity | Aggregate all cells → Pseudo-bulk | OncoMark |
| Per-cluster Hallmark activity | Aggregate cells in a cluster | OncoMark |
| Per-cell Hallmark scoring | Use UCell with Hallmark gene sets | UCell |