csdR

csdR implements differential gene coexpression analysis using the Conserved, Specific, and Differentiated (CSD) method to compare gene co-expressions across two conditions and assign each gene pair a conserved (C), specific (S), or differentiated (D) score.

Key Features:

• CSD method: Implements the Conserved, Specific, and Differentiated (CSD) approach for comparing gene co-expression between two distinct conditions.
• Pairwise scoring: Assigns each gene pair one of three scores—conserved (C), specific (S), or differentiated (D)—reflecting changes in coexpression between conditions.
• Network output: Produces a gene network where nodes are genes and edges represent the highest C, S, or D score for each gene pair.
• R package: Provided as an R package implementation.
• Benchmarking: Benchmarked on a dataset containing 20,645 genes.
• Parallelization and performance: Supports multi-core processing with reported parallel speedup up to 2.7 and saturation near 10 cores.
• Comparative performance: Demonstrated higher computational efficiency than previous CSD implementations in comparative tests.

Scientific Applications:

• Differential coexpression analysis: Comparing gene coexpression patterns across two biological conditions.
• Phenotype and disease studies: Interpreting changes in gene coexpression related to biological phenotypes and disease states.
• Interaction discovery: Identifying gene pairs and interactions that are conserved, condition-specific, or differentially regulated between conditions.

Methodology:

Computes pairwise coexpression comparisons between two conditions using the CSD method, assigns C/S/D scores to gene pairs, constructs a network retaining the highest C/S/D score per edge, and performs analyses with multi-core parallelization; benchmarking was performed on a 20,645-gene dataset with reported speedup metrics.