CytoGPS

CytoGPS transforms ISCN-formatted karyotypes into a machine-readable binary Loss-Gain-Fusion (LGF) model to enable computational cytogenetic analysis.

Key Features:

• Parsing and Conversion: Parses ISCN-formatted karyotypes into a structured machine-readable representation and translates them into a binary Loss-Gain-Fusion (LGF) model that encodes loss, gain, and fusion events.
• Analytical Capabilities: Represents cytogenetic abnormalities in an analyzable binary format to enable downstream large-scale computational analyses and cytogenetic pathology research.
• RCytoGPS Integration: Produces JSON output that the RCytoGPS R package converts into R objects for analysis and visualization within the R environment.

Scientific Applications:

• Clinical cytogenetics: Supports analysis of karyotypes routinely used in clinical contexts such as pediatric and cancer medicine.
• Discovery research: Facilitates large-scale computational studies to identify and characterize genetic abnormalities associated with disease.

Methodology:

CytoGPS parses ISCN text karyotypes into a structured machine-readable format, translates the parsed data into a binary LGF model encoding loss/gain/fusion events, and outputs JSON files convertible to R objects via RCytoGPS.