scPlant

scPlant provides a framework for analysis of plant single-cell transcriptomic data, enabling processing, cell-type annotation and deconvolution, trajectory inference, cross-species integration, and gene regulatory network construction to study plant growth, development, and responses to environmental stimuli.

Key Features:

• End-to-End Pipeline: Implements a comprehensive pipeline for exploration of plant single-cell atlases from minimal input data.
• Basic Data Processing: Handles and preprocesses raw single-cell transcriptomic data.
• Cell-Type Annotation and Deconvolution: Identifies and classifies cell types within plant tissue samples.
• Trajectory Inference: Reconstructs developmental trajectories to characterize cellular differentiation processes.
• Cross-Species Data Integration: Integrates data across different plant species to facilitate comparative studies.
• Gene Regulatory Network Construction: Builds cell-type-specific gene regulatory networks to elucidate genetic control mechanisms.

Scientific Applications:

• Cellular Heterogeneity Analysis: Investigates cellular heterogeneity within plant tissues at single-cell resolution.
• Developmental Process Analysis: Studies developmental processes and cellular differentiation at the single-cell level.
• Stress Response Analysis: Examines plant responses to biotic and abiotic stresses through cell-type-specific analyses.
• Comparative and Evolutionary Studies: Enables cross-species comparisons to identify conserved genetic pathways.

Methodology:

Performs basic data processing and preprocessing of raw single-cell transcriptomic data, cell-type annotation and deconvolution, trajectory inference, cross-species data integration, and gene regulatory network construction.