TransSynW

TransSynW predicts transcription factors and marker genes from single-cell RNA-sequencing (scRNA-seq) data to guide design of cell conversion experiments.

Key Features:

• scRNA-seq data input: Leverages single-cell RNA-sequencing (scRNA-seq) gene expression data for analysis.
• Transcription Factor Prediction: Predicts cell conversion transcription factors tailored to user-specified cell populations.
• Pioneer Factor Prioritization: Prioritizes pioneer transcription factors that facilitate chromatin opening during cell conversion.
• Marker Gene Prediction: Identifies marker genes to assess performance of cell conversion experiments.
• Customizable Input Format: Accepts single-cell gene expression input as a tab-separated file format with genes labeled according to Gene Symbols nomenclature.
• Conversion Specificity Analysis: Applies across multiple levels of cell conversion specificity and has recapitulated known conversion transcription factors.

Scientific Applications:

• Protocol Design: Guides design of novel cell conversion protocols in stem cell research.
• Regenerative Medicine Development: Supports selection of subtype-specific core transcription factor sets for regenerative medicine applications.
• Experimental Assessment: Enables evaluation of conversion outcomes through predicted marker genes.

Methodology:

Analyzes single-cell RNA-seq gene expression (tab-separated, Gene Symbols) to predict conversion transcription factors, prioritize pioneer factors, and identify marker genes.