SNPchip

SNPchip provides storage, visualization, and analysis of high-density single nucleotide polymorphism (SNP) array data to detect chromosomal abnormalities (aneuploidies, microdeletions, microduplications), assess loss of heterozygosity (LOH), and support genomic mapping and association studies within the R/Bioconductor environment.

Key Features:

• Data handling and visualization: Implements S4 classes in R/Bioconductor to store and plot high-density SNP array data, enabling visualization of heterozygosity and homozygosity patterns.
• Genomic analysis: Generates high-resolution maps of the human genome from SNP chip data to detect aneuploidies, microdeletions, microduplications, and LOH.
• Statistical modeling: Constructs SNP-level statistical models operating on S4 class instances to analyze associations between SNPs and phenotypes or traits.
• Integration with R/Bioconductor: Operates within the R programming environment and leverages Bioconductor classes and packages for genomic data analysis.

Scientific Applications:

• Chromosomal abnormality detection: Identification of aneuploidies, microdeletions, and microduplications from SNP array data.
• Disease-associated locus mapping: High-resolution mapping of genomic regions associated with disease phenotypes using SNP chip data.
• Cancer genomics and LOH analysis: Detection and analysis of loss of heterozygosity events relevant to tumorigenesis and oncogenomic studies.

Methodology:

Uses S4 object-oriented classes in R for data representation, plotting routines for SNP array visualization, and SNP-level statistical modeling implemented on S4 class instances.