PREDA: an R-package to identify regional variations in genomic data

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• Genomic signals form molecular fingerprints reflecting genome structure and function.
• Integrating diverse genomic data enhances interpretation of high-throughput results.

Purpose of the Study:

• To introduce PREDA, an R package for detecting regional variations in genomics data.
• To provide a flexible and robust tool for analyzing chromosomal patterns in high-throughput data.

Main Methods:

• PREDA utilizes a smoothing approach considering distance and density of genomic features.
• Custom data structures efficiently manage diverse signals across different genomes.
• The package offers various smoothing functions and statistics for flexible workflows.

Main Results:

• PREDA identifies relevant chromosomal patterns in high-throughput genomics data.
• The package facilitates efficient management of diverse genomic signals.
• Modular design allows for custom analytical pipeline deployment.

Conclusions:

• PREDA deepens the resolution and enhances the interpretation of genomic data.
• The R package aids in understanding how genome organization impacts functional control mechanisms.
• Tabular and graphical outputs support downstream biological interpretation.