PADOG

PADOG implements gene set analysis that down-weights genes overlapping multiple gene sets and computes gene set scores as the mean of absolute values of weighted moderated gene t-scores to improve ranking and sensitivity in pathway and microarray expression analyses.

Key Features:

• Weighting scheme: Genes appearing in fewer gene sets are emphasized while genes present in many gene sets are down-weighted.
• Gene set scoring: Gene set scores are calculated as the mean of absolute values of weighted moderated gene t-scores.
• Data type: Applicable to microarray gene expression data.
• Implementation: Provided as an R package.
• Validation: Objectively assessed across 24 public datasets from the KEGGdzPathwaysGEO package.
• Pathway demonstration: Performance demonstrated using KEGG pathways.
• Robustness: Improvements in ranking and sensitivity remain stable when varying the database of gene sets.

Scientific Applications:

• Pathway analysis (KEGG): Interpreting KEGG pathway activity from gene expression profiles.
• Gene-set ranking: Prioritizing gene sets by incorporating gene specificity across sets.
• Microarray studies: Detecting biologically relevant gene set signals in microarray datasets.
• Method benchmarking: Objective comparison of gene set analysis methods across multiple GEO datasets via KEGGdzPathwaysGEO.

Methodology:

Compute weighted moderated gene t-scores, apply a weighting scheme that down-weights genes appearing in many gene sets, and calculate gene set scores as the mean of the absolute values of these weighted moderated t-scores; validate results across 24 public datasets from the KEGGdzPathwaysGEO package.