signifinder

signifinder streamlines the collection and use of curated public transcriptional cancer signatures across bulk, single-cell, and spatial transcriptomics data to assess tumor characteristics and therapy responses.

Key Features:

• Signature Collection: Provides a curated collection of publicly available cancer transcriptional signatures.
• Multi-platform Data Support: Analyzes signatures across bulk gene expression, single-cell RNA sequencing, and spatial transcriptomics data types.
• Tumor Characterization: Assesses hallmark processes, therapy responses, and tumor microenvironment peculiarities.
• Signature Exploration Framework: Offers a comprehensive framework for interpreting high-resolution transcriptomic data and addressing tumor complexity.

Scientific Applications:

• Cancer Mechanism Understanding: Enables investigation of cancer mechanisms through transcriptional signature analysis.
• Subtype Definition: Supports cancer subtype classification using gene expression signatures.
• Prognosis Prediction: Facilitates prediction of patient prognosis based on signature-derived tumor characteristics.
• Therapy Efficacy Assessment: Evaluates therapy responses and treatment efficacy across diverse transcriptomic data types.
• Tumor Heterogeneity Characterization: Characterizes complex cellular heterogeneity within tumors at single-cell and spatial resolution.

Methodology:

signifinder is implemented as an R package within the Bioconductor project.