padma

padma uses multiple factor analysis to calculate individualized pathway-centric scores of deviation with respect to the sampled population based on multi-omic assays.

Key Features:

• Multi-omic integration: Analyzes data from RNA-seq, copy number alterations, methylation, and other multi-omic assays simultaneously.
• Pathway-centric deviation scoring: Computes individualized scores measuring deviation from the sampled population for specific pathways of interest.
• Aberrant individual identification: Provides graphical and numerical outputs to identify highly aberrant individuals for a particular pathway.
• Driver identification: Identifies the gene and omics drivers responsible for aberrant multi-omic profiles.

Scientific Applications:

• Individualized pathway analysis: Characterizes patient-specific pathway aberrations across multiple molecular data types in a population context.
• Multi-omic biomarker discovery: Identifies genes and omics drivers underlying aberrant multi-omic profiles for specific biological pathways.
• Precision medicine: Supports stratification of individuals based on pathway-level multi-omic deviation patterns.

Methodology:

Multiple factor analysis is applied to multi-omic assays to calculate individualized pathway-centric deviation scores with respect to the sampled population.