aCGH

aCGH analyzes array comparative genomic hybridization (aCGH) data to detect and map DNA copy number variations across genomes.

Key Features:

• Data Handling: Reads aCGH data from image analysis output files and clone information files and constructs S3 objects for data storage.
• Data Manipulation: Provides methods for accessing, replacing, subsetting, printing, and plotting aCGH objects.
• Comparison of Statistical Methods: Implements comparisons of three publicly available methods for analyzing array CGH data.
• Segmentation Utilization: Uses segmentation results in downstream testing and classification to enhance statistical power and prediction accuracy.
• Chromosome-Level Analysis: Performs analysis on individual chromosomes.
• Novel Merging Procedure: Implements a novel procedure for merging segments across the genome to yield an interpretable set of copy number levels.

Scientific Applications:

• Detection and Mapping: Identifies regions with altered DNA copy numbers using aCGH data.
• Genomic Segmentation: Determines genomic segments with different copy number levels using statistical segmentation methods.
• Genomic Diagnostics: Supports identification of pathogenic copy number variations for diagnostic applications.
• Cancer Genomics: Investigates copy number variations associated with oncogenesis and tumor progression.
• Evolutionary Biology: Studies copy number variation across species or populations for evolutionary analyses.

Methodology:

Compares three publicly available array CGH analysis methods applied per chromosome, uses segmentation results in downstream testing and classification, and applies a novel genome-wide segment-merging procedure to define interpretable copy number levels.