Arboreto Gene Regulatory Network Inference

关于

Arboreto is a high-performance computational library designed to reconstruct gene regulatory networks (GRNs) from large-scale gene expression data, such as bulk or single-cell RNA-seq. By leveraging parallelized algorithms like GRNBoost2 and GENIE3, it identifies regulatory relationships between transcription factors and target genes with exceptional speed. This skill is particularly valuable for bioinformaticians needing to scale analyses from local machines to distributed clusters using Dask, providing a robust foundation for downstream systems biology workflows like the pySCENIC pipeline.

主要功能

• 81 GitHub stars
• Distributed computing support via Dask for large-scale datasets
• Identification of transcription factor-target gene interactions
• Scalable GRN inference using GRNBoost2 and GENIE3 algorithms
• Optimized performance for datasets with 10k+ observations
• Seamless integration with single-cell and bulk RNA-seq workflows

使用场景

• Identifying cell-type-specific regulatory networks in single-cell RNA-seq data
• Performing comparative regulatory analysis across multiple experimental conditions
• Mapping transcription factor targets in bulk transcriptomics studies