Pomelo II

Pomelo II performs statistical analysis of gene and protein expression and tissue array data to identify differential expression, associations, and survival-related markers.

Key Features:

• Statistical analysis: Implements permutation-based tests for class comparisons including t-tests and ANOVA, regression analysis, survival analysis using the Cox proportional hazards model, and contingency table analysis with Fisher's exact test.
• Linear modeling and empirical Bayes: Supports linear models that incorporate additional covariates and applies empirical Bayes moderated statistics.
• Parallel computing: Utilizes parallel computing on multicore CPUs and computing clusters to accelerate computationally intensive analyses.
• Database integration: Provides annotations and references from PubMed, Gene Ontology, KEGG, and Reactome for genes and gene sets.

Scientific Applications:

• Genomics and proteomics: Analysis of gene and protein expression datasets to detect differential expression and associations.
• Multifactorial and longitudinal studies: Analysis of complex experimental designs including additional covariates and survival outcomes.
• Pathway and functional analysis: Interpretation of results in the context of Gene Ontology, KEGG, and Reactome pathways.

Methodology:

Permutation-based class comparisons (t-tests, ANOVA), regression analysis, Cox proportional hazards survival analysis, Fisher's exact test for contingency tables, linear models with covariates, empirical Bayes moderated statistics, and parallel computation on multicore CPUs and clusters; integration of PubMed, Gene Ontology, KEGG and Reactome annotations.