CNVMetrics

CNVMetrics calculates similarity metrics to facilitate copy number variant comparison among samples and/or methods.

Key Features:

• Multiple similarity metrics: Metrics based on shared amplified/deleted regions and metrics relying on the level of amplification/deletion.
• Flexible profile comparison: Compares CNV profiles of genetically unrelated samples as well as those with a common genetic background.
• Input data support: Accepts plain text files containing genomic position of copy number variations, status calls, and/or log2 ratio values.
• Statistical significance assessment: Significance of observed metrics is assessed against null distributions computed using simulated profiles, with simulation functions included in the package.
• Visualization: Generates sample-to-sample heatmaps to explore resulting metrics.

Scientific Applications:

• Tumor evolution studies: Comparison between primary and metastatic tumor CNV profiles may reveal genomic determinants of metastasis.
• Model validation: Quantifies recapitulation of CNV patterns in patient-derived xenograft or organoid models relative to tumor tissue of origin.
• Cancer genomics: Predictive analysis of patient outcomes based on copy number profile patterns in cancer.
• Cross-platform analysis: Supports CNV profiles derived from microarrays and next-generation DNA sequencing platforms.

Methodology:

CNVMetrics is implemented in R using data structures supplied by the Bioconductor GenomicRanges package to store and manipulate CNVs. Similarity metrics are calculated based on either CNV categorical status calls or copy number ratios. Significance assessment uses null distributions computed from simulated profiles.