PAPi

PAPi computes pathway activity scores from metabolomics data to infer and compare metabolic pathway activities across experimental conditions.

Key Features:

• Metabolomics Data Utilization: Processes low molecular mass metabolite identifications and their abundance data from metabolomics experiments.
• Algorithmic Innovation: Implements a novel algorithm that compares metabolic pathway activities based on metabolite profiles.
• Activity Scores Calculation: Calculates "Pathways' Activity Scores" from identified metabolites and abundances to represent potential pathway activities.
• Statistical Analysis Tools: Provides principal components analysis and statistical tests including analysis of variance (ANOVA) and t-tests to compare pathway activity levels.
• Graphical Representation: Generates comparative graphs that highlight up- or down-regulated pathway activities across conditions.

Scientific Applications:

• Comparative Pathway Analysis: Enables comparison of metabolic pathway activities across different experimental conditions using metabolite abundance data.
• Hypothesis Generation: Facilitates generation of hypotheses linking changes in metabolite levels to changes in pathway activity.
• Interpretation and Validation: Supports biological interpretation of metabolomics results and has been validated using Saccharomyces cerevisiae data.

Methodology:

Accepts identified metabolites and their abundances as input, applies the PAPi algorithm to compute "Pathways' Activity Scores", performs principal components analysis and statistical tests (ANOVA, t-tests), and produces comparative graphs.