ZygosityPredictor

ZygosityPredictor predicts how many copies of a gene are affected by small variants in next generation sequencing data.

Key Features:

• Affected Copy Number Calculation: Computes the number of affected copies for single nucleotide variants and small insertions and deletions.
• Gene-Level Integration: Integrates the influence of several variants on a gene via phasing and subsequent logic to derive how strongly a gene is affected by mutations.
• Wild-Type Copy Assessment: Determines if and how many wild-type copies of a gene remain after variant effects.
• Large-Scale Deletion Assessment: Evaluates large scale deletions that cause losses of whole genes or parts of them.
• Confidence Measure: Provides a measure of confidence for the gene-level predictions.
• Dual Origin Support: Processes both somatic and germline mutations.

Scientific Applications:

• Tumor-Suppressor Gene Analysis: Assesses whether unmutated copies of tumor-suppressor genes remain in cancer genomes.
• Genome-Wide Gene Assessment: Enables wild-type copy evaluation for all genes of an organism.
• Precision Oncology: Supports translational medicine applications where gene copy status informs therapeutic decisions.

Methodology:

ZygosityPredictor performs phasing of several variants at the gene level and applies subsequent logic to derive how strongly a gene is affected by mutations, with integration of large scale deletion assessments for losses of whole genes or gene parts.