MINI-EX

MINI-EX infers cell-type-specific gene regulatory networks in multicellular organisms, focusing on plants, by integrating single-cell RNA sequencing data with transcription factor motif information.

Key Features:

• Single-Cell Transcriptomic Data Utilization: Leverages single-cell RNA sequencing data to define expression-based networks at single-cell resolution.
• Integration of TF Motif Information: Incorporates transcription factor (TF) motif information to refine and filter inferred regulons.
• Regulon Assignment to Cell Types: Assigns inferred regulons to specific cell types based on cell-specific expression patterns.
• Prioritization of Candidate Regulators: Prioritizes candidate regulators using network centrality measures, functional annotations, and expression specificity.
• Robustness and Stability: Maintains reliable network inference performance with datasets containing low cell numbers or missing data.

Scientific Applications:

• Root Development: Identified regulators controlling root development in Arabidopsis and rice.
• Leaf Development: Elucidated regulatory networks governing leaf development in Arabidopsis.
• Ear Development: Revealed regulators involved in ear development in maize.

Methodology:

Uses single-cell RNA sequencing data, integrates transcription factor (TF) motif information, assigns regulons to cell types based on cell-specific expression patterns, and prioritizes regulators using network centrality measures, functional annotations, and expression specificity.