StemChecker

StemChecker evaluates gene sets for association with stemness by comparing them to curated stemness signatures and transcription factor target sets to identify statistically significant overlaps and regulatory associations.

Key Features:

• Curated stemness signatures: Contains nearly fifty published stemness signatures curated from gene expression analyses, RNA interference (RNAi) screens, transcription factor (TF) binding sites, literature reviews, and computational approaches.
• Gene-list comparison: Compares user-provided gene lists against the curated collection to determine shared membership with stemness signatures.
• Statistical significance evaluation: Computes statistical significance of overlaps between input genes and stemness signatures and highlights individual genes present in known signatures.
• Transcriptional regulatory sets: Includes over 80 target gene sets associated with transcription factors linked to pluripotency or multipotency to support analysis of regulatory programs.
• Disease-relevance inference: Maps input genes to stemness signatures and TF targets to indicate potential implications in diseases such as cancer.

Scientific Applications:

• Stem Cell Biology: Identification and characterization of genes associated with maintenance of stem cell properties.
• Developmental Biology: Analysis of gene sets to elucidate genetic contributions to developmental processes involving stem cells.
• Regenerative Medicine: Prioritization of gene targets relevant for regenerative therapies based on stemness associations.
• Human Disease Research: Investigation of the role of stemness-associated genes in diseases such as cancer, diabetes, neurodegenerative disorders, and heart disease.

Methodology:

Compare user-provided gene lists against a curated collection of nearly fifty published stemness signatures (from gene expression, RNAi screens, TF binding sites, literature reviews, and computational approaches) and over 80 TF target gene sets linked to pluripotency or multipotency, and compute statistical significance of overlaps.