copynumber

copynumber performs segmentation and analysis of genomic copy number data by fitting piecewise constant curves and identifying breakpoints for single-sample, multi-sample and multi-track analyses of array-CGH, SNP arrays, and high-throughput sequencing to study genomic instability.

Key Features:

• Penalized Least Squares Regression: Employs penalized least squares regression to fit piecewise constant curves to copy number data, providing least-squares-optimal fits conditional on the number of breakpoints.
• Unified Framework: Supports array-CGH, SNP arrays, and high-throughput sequencing data and enables single-sample, multi-sample, and multi-track segmentation.
• Computational Efficiency: Implements a novel algorithm that leverages vector-based operations in R to improve performance on high-density copy number scans.
• Visualization Tools: Includes plotting functions for visualizing raw copy number data and segmentation results.

Scientific Applications:

• Cancer Research: Identifies genomic regions with constant or altered copy numbers to support studies of cancer progression and genomic instability.
• Genomic Studies: Supports large-scale analyses of DNA gains and losses in high-density genomic scans.

Methodology:

Uses penalized least squares regression to fit piecewise constant curves, conditions estimates on the number of breakpoints, and employs vectorized operations in R for computational efficiency.