miTEA

miTEA identifies and visualizes enriched microRNA (miRNA) targets within ranked gene or protein lists to infer miRNA activity from high-throughput data.

Key Features:

• Minimum-mHG (mmHG) scoring: Uses the minimum-mHG (mmHG) statistical test to assess mutual enrichment between two ranked lists.
• Mutual enrichment analysis: Evaluates overlaps between gene/protein rankings and miRNA target predictions to infer regulatory activity.
• Top-segment enrichment: Detects enriched miRNA targets specifically in top segments of ranked gene or protein lists.
• Target prediction evaluation: Enables evaluation of miRNA target prediction tools using public miRNA constitutive expression data.
• Integrative dataset support: Applies to integrative datasets including matched miRNA/mRNA data across multiple human tissue types.
• Visualization: Produces visual representations of enriched miRNA targets and their overlaps with ranked lists.

Scientific Applications:

• miRNA activity inference: Infers miRNA regulatory activity from expression-derived ranked lists and high-throughput datasets.
• miR-519 in placenta: Identified activity of miR-519 in placental tissues.
• miR-15 in healthy tissues: Identified involvement of miR-15 in healthy tissue types.
• miR-768 in health and cancer: Identified involvement of miR-768 in healthy tissues and cancer cell lines.

Methodology:

Computational assessment uses the minimum-mHG (mmHG) statistic to measure mutual enrichment between two ranked lists by evaluating overlaps between gene/protein rankings and miRNA target predictions to infer miRNA activity from high-throughput data.