StemChecker: a web-based tool to discover and explore stemness signatures in gene sets

Area of Science:

• Stem cell biology
• Regenerative medicine
• Bioinformatics

Background:

• Stem cells possess regenerative potential for treating diseases like diabetes and neurodegenerative disorders.
• Identifying stemness signatures is crucial for stem cell research but lacks comprehensive resources.
• Existing methods for stemness analysis are often time-consuming and require extensive data processing.

Purpose of the Study:

• To develop a novel, user-friendly tool for analyzing stemness signatures.
• To provide a comprehensive resource for exploring gene expression, TF binding sites, and literature-curated stemness signatures.
• To facilitate the investigation of regulatory mechanisms underlying stem cell pluripotency and multipotency.

Main Methods:

• Curated nearly fifty published stemness signatures from various sources including gene expression, RNAi screens, and TF binding sites.
• Integrated over 80 target gene sets of transcription factors associated with pluripotency or multipotency.
• Developed an intuitive graphical interface and detailed statistical output for data exploration.

Main Results:

• StemChecker enables researchers to analyze stemness signatures in user-defined gene sets efficiently.
• The tool facilitates the discovery of transcriptional regulatory programs associated with stemness.
• Identified potential links between stemness processes and diseases such as cancer.

Conclusions:

• StemChecker significantly enhances the available tools for stem cell biology, developmental biology, and regenerative medicine research.
• The platform provides valuable insights into stemness regulatory networks and their disease implications.
• StemChecker is freely accessible online, supporting a broad research community.