CoNVaQ

CoNVaQ performs CNV-based association analyses to identify genomic regions where copy number variations associate with phenotypes and to characterize their functional enrichment.

Key Features:

• Two analytical models: A statistical model that uses Fisher's exact test to identify genomic regions where CNVs are significantly associated with phenotypes, and a query-based model that matches regions against user-defined queries.
• Global q-value statistic: Computes a global q-value for each region through repeated permutation of samples among populations to assess association significance.
• Comparative CNV input: Accepts two sets of CNV segments for association analyses between sample groups.
• Functional analysis: Identifies overrepresented Gene Ontology (GO) terms and pathways from associated regions.
• R integration: Provided as an R package for scripted analyses.

Scientific Applications:

• CNV association studies: Identification of CNVs associated with disease phenotypes in complex disease genetics.
• Extension of GWAS: Extends genome-wide association studies (GWAS) to include structural variants by testing CNV-phenotype associations.
• Pennile cancer case study: Demonstrated on a dataset comparing HPV-positive and HPV-negative penile cancer patients to identify phenotype-associated CNVs.

Methodology:

Accepts two CNV segment sets; applies Fisher's exact test in a statistical model and a query-based region-matching model; computes global q-values by repeated permutation of samples among populations; performs Gene Ontology and pathway overrepresentation analysis.