CAPweb

CAPweb performs analysis and interpretation of array Comparative Genomic Hybridization (array CGH) data to detect and characterize genomic DNA copy number variations relevant to constitutional and somatic diseases, including cancers.

Key Features:

• Automatic Normalization: Corrects experimental biases in array CGH data prior to downstream analysis.
• Breakpoint Detection (Adaptive Weights Smoothing, AWS): Detects breakpoints using the Adaptive Weights Smoothing (AWS) procedure, achieving reported breakpoint detection rates of 97–100% across datasets.
• Status Assignment: Assigns chromosomal region statuses (normal, gained, or lost) based on detected breakpoints with reported precision of 98.9–100%.
• Array Annotations Support: Processes array annotations including genomic probe positions for accurate mapping of copy number events.
• Validation and Quality Control: Incorporates validation and quality criteria with summary outputs validated against simulated data, karyotyping results, and manually analyzed profiles.
• Visualization and Biological Analysis: Provides visualization of genomic profiles and identification of systematically deleted or amplified regions associated with tumor progression.

Scientific Applications:

• Cancer gene identification: Pinpoints tumor suppressor genes in deleted regions and oncogenes in amplified regions to support discovery of cancer-associated genes.
• Tumor classification and genomic characterization: Supports classification of tumors and characterization of genomic alterations during tumorigenesis.

Methodology:

Automatic normalization to correct experimental biases; breakpoint detection and status assignment using the Adaptive Weights Smoothing (AWS) procedure; validation against simulated data, karyotyping results, and manually analyzed profiles.