Codon Usage Similarity Index (COUSIN)

Codon Usage Similarity Index (COUSIN) calculates normalized codon usage preferences by comparing synonymous codon usage of query sequences to reference datasets under a null hypothesis of random codon usage.

Key Features:

• COUSIN Index Calculation: Computes the Codon Usage Similarity Index to quantify similarity between query codon usage preferences and a reference codon usage profile.
• Normalized Codon Usage Analysis: Normalizes codon usage comparisons against a null hypothesis of random synonymous codon usage.
• Multi-Scale Codon Usage Evaluation: Analyzes codon usage preferences across genes, chromosomes, or complete genomes.
• Additional Codon Usage Metrics: Calculates seven supplementary indices for comprehensive codon usage preference analysis.
• Statistical and Clustering Analysis: Performs statistical analyses and clustering of codon usage patterns across datasets.
• Codon Usage Optimization: Supports optimization of codon usage preferences for improved gene expression.

Scientific Applications:

• Codon Usage Bias Analysis: Investigates unequal usage of synonymous codons across genes, chromosomes, and genomes.
• Comparative Genomics: Compares codon usage preferences among species or genomic datasets.
• Gene Expression Optimization: Assists in optimizing codon usage to enhance heterologous gene expression.
• Evolutionary Genomics: Studies evolutionary patterns and distributions of codon usage across genomes.

Methodology:

COUSIN computes codon usage preferences from coding sequences, compares query codon frequencies with reference datasets, normalizes similarity using a null hypothesis of random codon usage, and applies additional codon usage indices with statistical and clustering analyses.