oposSOM-Browser

oposSOM-Browser provides exploration and analysis of high-throughput omics and transcriptome datasets to map single-gene and gene-set expression profiles, molecular "portrait landscapes", phenotype diversity, signaling pathway activation patterns, diagnostic signature quality, and survival-associated molecular profiles.

Key Features:

• Single-gene and gene-set profiling: Maps and visualizes single-gene and gene set expression profiles across samples.
• Molecular "portrait landscape" mapping: Projects genes and functions onto a molecular "portrait landscape" to reveal structural organization and relationships within datasets.
• Phenotype diversity analysis: Quantifies and compares phenotype diversity across datasets to identify phenotypic variation associated with biological conditions.
• Survival differences analysis: Associates molecular profiles with survival differences to evaluate prognostic factors.
• Signaling pathway activation patterns: Analyzes cellular signaling pathway activation patterns across samples.
• Diagnostic quality evaluation: Maps and evaluates individual signature gene lists for diagnostic quality and biomarker selection.
• Cross-dataset transcriptome analysis: Supports comparative analyses of multiple transcriptome datasets including melanomas, B-cell lymphomas, gliomas, sepsis, and healthy individuals.

Scientific Applications:

• Cancer research: Analyzes tumor transcriptomes (melanomas, B-cell lymphomas, gliomas) to identify molecular mechanisms, biomarkers, and prognostic signatures.
• Infectious disease and systemic response studies: Compares sepsis and healthy individual transcriptomes to reveal systemic response patterns and phenotype diversity.
• Biomarker discovery and prognostic assessment: Evaluates signature gene lists and pathway activation patterns to support biomarker selection and prognostic analyses.

Methodology:

Built on oposSOM, the framework integrates machine learning-based methodologies, diversity analyses, biomarker selection, functional information mining, and advanced visualization techniques.