# ZygosityPredictor

## TL;DR

ZygosityPredictor is a tool that determines how many gene copies are affected by mutations in cancer sequencing data, helping in precision oncology.

## Contribution

The novel contribution is a new R-package that integrates variant phasing and logic to assess gene-level mutation impact with confidence measures.

## Key findings

- ZygosityPredictor evaluates affected gene copies for SNVs and Indels in cancer samples.
- The tool integrates phasing and logic to derive gene-level mutation impact.
- It is implemented as an R-package available via Bioconductor with detailed documentation.

## Abstract

ZygosityPredictor provides functionality to evaluate how many copies of a gene are affected by mutations in next generation sequencing data. In cancer samples, the tool processes both somatic and germline mutations. In particular, ZygosityPredictor computes the number of affected copies for single nucleotide variants and small insertions and deletions (Indels). In addition, the tool integrates information at gene level via phasing of several variants and subsequent logic to derive how strongly a gene is affected by mutations and provides a measure of confidence. This information is of particular interest in precision oncology, e.g. when assessing whether unmutated copies of tumor-suppressor genes remain.

ZygosityPredictor was implemented as an R-package and is available via Bioconductor at https://bioconductor.org/packages/ZygosityPredictor. Detailed documentation is provided in the vignette including application to an example genome.