scSELpy

scSELpy enables manual selection of cells from single-cell RNA sequencing (scRNA-seq) datasets to isolate and analyze immune cell subsets, including T cell subphenotypes, within Scanpy-based workflows.

Key Features:

• Integration with Scanpy: Integrates into Scanpy-based workflows to operate on AnnData objects and maintain compatibility with existing single-cell analysis pipelines.
• Manual Cell Selection: Allows manual selection of cells by drawing polygons on various data representations to isolate populations not captured by automated clustering.
• Downstream Analysis Support: Supports downstream analysis of selected cell subsets, including plotting and visualization of transcriptomic results.
• Application to Immunological Datasets: Applied to single-cell RNA sequencing datasets from inflammatory bowel disease (IBD) for positive and negative selection of T cell subsets and subphenotyping.
• Validation and T cell receptor sequencing: Corroborates findings from published datasets and extends applicability to analyses involving T cell receptor sequencing.

Scientific Applications:

• Inflammatory Bowel Diseases (IBD): Used to identify and analyze immune cell dynamics and T cell subset composition in IBD scRNA-seq datasets.
• Subphenotyping of Immune Cells: Enables subphenotyping of T cell subsets to investigate functional heterogeneity within immune populations.
• T cell receptor sequencing analyses: Applied in conjunction with T cell receptor sequencing to support analyses that combine TCR data with selected transcriptomic subsets.

Methodology:

User-driven cell selection via drawing polygons on data representations to delineate cell populations based on transcriptomic data; integration with Scanpy for compatibility with Scanpy-based analysis pipelines.