rROMA

rROMA computes the activity of gene sets with coordinated expression from high-throughput transcriptomic and proteomic data.

Key Features:

• Fast and accurate algorithm: The calculation algorithm incorporates significant improvements for computing gene set activity.
• Statistical analysis functions: The package implements functions for statistical analysis of gene set activity results.
• Visualization functions: The package provides functions for visualizing gene set activity results.

Scientific Applications:

• Disease mechanism identification: rROMA detects disease-related active signaling pathways using transcriptomic and proteomic data, as demonstrated in cystic fibrosis.
• Cell culture bias detection: Analysis with rROMA can raise awareness of possible biases related to cell culture conditions.
• Candidate gene discovery: The tool uncovers genes warranting further investigation in the context of disease progression.

Methodology:

The sources do not provide detailed methodological description beyond fast and accurate computation of coordinated gene set expression activity with improved calculation algorithms.