SNPLims: a data management system for genome wide association studies.

Area of Science:

• Genomics
• Bioinformatics
• Genetic Epidemiology

Background:

• High-density genetic maps require robust data management systems.
• Whole genome genotyping generates vast amounts of genetic data.
• Efficient management is crucial for analyzing disease-related genetic variations.

Purpose of the Study:

• To develop an information system for managing SNP genotype data.
• To facilitate the analysis of large-scale genetic datasets.
• To support the identification of genetic markers associated with diseases.

Main Methods:

• Developed a relational database system for SNP genotype data storage and management.
• Enabled data import and export in formats compatible with genetic analysis programs.
• Integrated functionality for importing association study results and visualizing findings.

Main Results:

• The system efficiently stores and manages large volumes of SNP genotype data.
• Allows rapid identification and annotation of statistically relevant polymorphisms.
• Supports data visualization and export for further analysis.

Conclusions:

• The infrastructure effectively manages extensive genotype and phenotype data.
• Enables data quality control and common screening analyses.
• Facilitates the identification of candidate genes for diseases.