waviCGH

waviCGH analyzes genomic copy number alterations from high-density SNP-arrays, array-CGH, or other copy-number call sources to preprocess, segment, call gains and losses, and determine minimal common regions across samples.

Key Features:

• Input data types: Accepts high-density SNP-arrays, array-CGH, and other techniques that generate copy-number calls.
• Pre-processing: Provides pre-processing routines for copy-number data.
• Segmentation: Performs segmentation of copy-number signals.
• Calling: Calls gains and losses from segmented data.
• Minimal common regions: Determines minimal common regions across sets of experiments.
• Species support: Accommodates any species and includes specific mapping support for human, mouse, and rat genomes.
• Cytogenetic mapping: Maps altered regions onto chromosomes using an integrated cytogenetic browser.
• Output formats: Produces images and tables representing results in a genomic context.

Scientific Applications:

• Comparative CNV analysis: Comparison of genomic copy number alterations across multiple samples.
• Recurrent event discovery: Identification of recurrent gains and losses and minimal common regions across experiments.
• Cytogenetic interpretation: Localization of copy-number alterations within chromosomal/cytogenetic context for human, mouse, and rat.
• Cross-platform analysis: Analysis of copy-number data derived from both high-density SNP-arrays and array-CGH.

Methodology:

Pre-processing of copy-number data, segmentation, calling of gains and losses, determination of minimal common regions, and mapping of altered regions onto chromosomes via an integrated cytogenetic browser.