WPZgithub/CEFCON
Deciphering driver regulators of cell fate decisions from single-cell RNA-seq data
CEFCON helps molecular biologists and geneticists understand how cells make decisions about their identity and function. It takes single-cell RNA sequencing data (scRNA-seq) and a known gene interaction network as input. It then outputs the key 'driver' genes and gene regulatory modules that control cell fate transitions, along with their influence scores, helping researchers pinpoint the most critical regulatory mechanisms. This tool is for scientists studying cell development, differentiation, or disease processes.
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Use this if you need to identify the master regulator genes that drive cell fate changes in your single-cell RNA-seq experiments and understand the underlying gene regulatory networks.
Not ideal if you are looking for a simple tool for basic scRNA-seq data visualization or differential expression analysis without needing deep insights into regulatory mechanisms.
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Language
Jupyter Notebook
License
MIT
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Last pushed
Oct 24, 2024
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