CNVxplorer

CNVxplorer integrates clinical, genomic, and epigenomic annotations to assess the functional impact of copy number variants (CNVs) for clinical diagnostics.

Key Features:

• Phenotype Correlation: Assesses agreement between CNVs and patient phenotypes to support clinical interpretation.
• Sequence Constraint Metrics: Provides sequence constraint metrics for genes impacted by CNVs.
• Regulatory Element and TAD Impact: Evaluates impact on regulatory elements and topologically associating domains (TADs), including non-coding regions.
• Gene Expression Patterns: Integrates gene expression patterns to assess potential dosage and expression-level effects of CNVs.
• Gene–Regulatory–Transcription Factor Associations: Visualizes associations among genes, regulatory elements, and transcription factors to elucidate potential regulatory mechanisms.
• Functional and Pathway Enrichment Analysis: Performs enrichment analyses on functional annotations and biological pathways for genes affected by CNVs.
• Literature Co-occurrence Analysis: Examines term co-occurrence across PubMed publications related to query CNVs.
• Support for array-based Comparative Genomic Hybridization: Processes CNVs identified through array-based Comparative Genomic Hybridization (array-CGH) data.
• Coding and Non-coding Impact Assessment: Considers both coding and non-coding impacts of CNVs in the evaluation.
• Flexible Evaluation Workflow: Supports iterative re-interrogation of CNV annotations during clinical evaluation.

Scientific Applications:

• Clinical CNV Interpretation: Interpretation of CNVs in rare genetic disease diagnostics to aid in pathogenicity assessment.
• Candidate Prioritization: Prioritization of candidate genes and regulatory elements affected by CNVs for further investigation.
• Pathway and Literature Contextualization: Contextualization of CNVs within biological pathways and PubMed literature to inform clinical hypotheses.

Methodology:

Integration of clinical, genomic, and epigenomic annotations; calculation of sequence constraint metrics; evaluation of impacts on regulatory elements and TADs; integration of gene expression patterns; functional and pathway enrichment analyses; PubMed term co-occurrence analysis; and visualization of gene–regulatory–transcription factor associations.