TROM

TROM measures overlap between transcriptome-associated gene sets to compare transcriptomic similarity and identify conserved and divergent biological processes across samples and species.

Key Features:

• Testing-Based Methodology: Employs a testing-based approach that identifies genes associated with specific molecular characteristics and compares transcriptomes by evaluating overlaps of these gene sets.
• Contrast to Correlation Methods: Focuses on gene-set overlap rather than sample-level Pearson or Spearman correlation, providing an alternative framework for comparative transcriptomics.
• Robustness and Power: Demonstrated increased sensitivity in detecting transcriptomic similarities and robustness to stochastic gene expression noise compared with traditional correlation methods.
• Implementation: Implemented as an R package for computational analysis of transcriptomic overlap.

Scientific Applications:

• Comparative transcriptomics across species and stages: Enables exploration and comparison of transcriptomic landscapes across species and developmental stages, applied to datasets including six Drosophila species, C. elegans, S. purpuratus, Danio rerio, and mouse liver.
• Detection of conserved developmental programs: Used to reveal conserved patterns of gene expression across developmental stages, indicating conserved genetic programs underlying development.

Methodology:

Identify genes associated with specific molecular characteristics in biological samples, then statistically test for overlaps between these associated gene sets to compare transcriptomes.