Single Cell Analysis Tools

Comprehensive workflows for single-cell RNA-seq analysis, including cell clustering, trajectory inference, and differential expression analysis. Features interactive visualization modules and integrative analysis pipelines.

Scalable Python toolkit for single-cell transcriptomics with integrated workflows for pseudotime analysis and cell-cell communication inference. Optimized for large-scale datasets with GPU acceleration support.

Integrated pipelines for joint analysis of scRNA-seq and scATAC-seq data, enabling cross-modal cell state characterization and regulatory element mapping. Features joint embedding visualization and differential accessibility analysis.

Python package specializing in single-cell DNA methylation analysis with comprehensive visualization tools. Includes unique features for allele-specific methylation analysis and 3D genome interaction mapping.

CRISPR-Cas9 based perturbation analysis toolkit enabling large-scale functional genomics studies. Features pseudo-bulk aggregation methods and trajectory inference for perturbation response analysis.