Viola

Viola extracts and analyzes genomic structural variant (SV) signatures to characterize large-scale DNA alterations relevant to disease such as cancer.

Key Features:

• Custom SV Classification: Provides tools for customizing the classification of structural variants to suit specific research needs or datasets.
• Feature Matrix Generation: Generates matrices that encapsulate relevant features of structural variants for downstream analysis.
• SV Signature Extraction with NMF: Employs Non-negative Matrix Factorization to extract SV signatures from genomic datasets.
• Stability Evaluation System: Assesses the reliability and stability of extracted SV signatures.
• Merging SV Caller Outputs: Merges outputs from various structural variant callers to enhance data comprehensiveness and accuracy.
• SV Annotation: Annotates structural variant data to support interpretation of variants.
• Computational Time Assessment: Evaluates computational runtime requirements across different datasets.

Scientific Applications:

• Cancer genomics: Extracts and analyzes SV signatures to identify patterns associated with tumorigenesis and progression.
• Large-scale SV dataset analysis: Processes publicly available and large-scale genomic SV data to derive insights into genetic variation.

Methodology:

Performs merging of outputs from multiple structural variant callers, annotation of SV data, generation of feature matrices, extraction of SV signatures using Non-negative Matrix Factorization (NMF), and evaluation of signature stability and computational runtime.