InfernoRDN

InfernoRDN performs downstream analysis of quantitative bottom-up shotgun proteomics and microarray data by providing normalization, missing-value imputation, peptide-to-protein rollup, visualization, and hypothesis-testing capabilities for protein expression and differential analysis.

Key Features:

• Normalization: Implements selected normalization methods tailored for diverse high-throughput datasets to enable accurate comparative analyses.
• Missing Value Imputation: Includes algorithms for imputing missing values common in large-scale proteomics and microarray datasets.
• Peptide-to-Protein Rollup Methods: Aggregates peptide-level measurements into protein-level summaries for proteomic analysis.
• Extensive Plotting Functions: Provides a wide array of plotting functions for detailed visualization of complex datasets.
• Comprehensive Hypothesis Testing: Supports hypothesis-testing procedures that handle unbalanced data and incorporate random effects.

Scientific Applications:

• Proteomics data analysis: Processes large-scale proteomics data for protein expression profiling and differential analysis.
• Microarray and other omics analyses: Adapts to microarray datasets and broader omics contexts, including genomics and transcriptomics.

Methodology:

Applies normalization methods, missing-value imputation algorithms, peptide-to-protein rollup methods, plotting functions, and hypothesis-testing schemes that accommodate unbalanced data and random effects.