PCGIMA

PCGIMA analyzes position-defined CpG island (CGI) methylation in the human genome, predicting short CpG islets and linking CGI methylation patterns to gene expression specificity and gene function at a genome-wide scale.

Key Features:

• MR-CpGCluster-based position-defined CGI prediction: Implements the MR-CpGCluster algorithm using high-performance computing to predict position-defined CGIs and locate short CpG islets characterized by multiple consecutive (d) values.
• Genome-wide annotation and functional analysis: Performs genome-wide annotation linking CGI methylation to gene expression specificity, gene functions, and chromosomal integrity to investigate regulatory mechanisms.
• Integrated prediction and analysis workflow: Combines position-defined CGI prediction with genome-scale analyses to explore relationships among CGIs, methylation patterns, and gene expression.

Scientific Applications:

• Epigenetic research: Characterizing CGI methylation patterns and their influence on gene expression and chromosomal stability.
• Gene regulation studies: Investigating position-dependent methylation effects on gene expression specificity and gene function.
• Genome annotation and functional mapping: Providing genome-wide maps of position-defined CGIs, including CpG islets, for functional annotation of the human genome.

Methodology:

Uses the MR-CpGCluster algorithm with high-performance computing to predict position-defined CGIs and locate CpG islets by detecting regions with multiple consecutive (d) values.