pathprint

pathprint converts gene expression profiles into pathway fingerprints—ternary vectors with scores high (1), low (-1), or insignificant (0)—to summarize pathway, network, and transcriptionally regulated target activity for functional comparison across experiments and species.

Key Features:

• Pathway fingerprints: Converts gene expression profiles into vectors that represent pathway, network, and transcriptional-target activity.
• Ternary scoring: Encodes expression in each pathway as high (1), low (-1), or insignificant (0).
• Data integration: Integrates experimental data from cell lines, primary tissues, and model organisms to address diverse sources.
• Standardization: Standardizes variables to overcome platform variability, species differences, and batch effects.
• Functional distance: Provides a consistent measure of functional distance between different experiments.
• Cross-species comparison: Leverages large-scale profiling methods and curated public repositories to compare gene expression profiles across species.
• Disease-relevant analysis: Supports identification of prognostic indicators, exemplified by applications in acute myeloid leukemia (AML).

Scientific Applications:

• Cross-species analysis: Comparative analysis of gene expression across species, including combined mouse and human datasets.
• Prognostic marker discovery: Identification of pathway-level prognostic indicators in diseases such as acute myeloid leukemia (AML).
• Functional comparison of experiments: Quantitative comparison and clustering of experiments based on pathway activity fingerprints.
• Integrative analysis of diverse datasets: Synthesis of data from cell lines, primary tissues, and model organisms for unified functional interpretation.

Methodology:

Converts gene expression profiles into pathway fingerprints with ternary scores (high 1, low -1, insignificant 0); integrates data from cell lines, primary tissues, and model organisms; standardizes to mitigate platform variability, species differences, and batch effects; and compares profiles across species using large-scale profiling methods and curated public repositories to compute functional distance between experiments.