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ZygosityPredictor. | LitMetric

AI Article Synopsis

  • ZygosityPredictor evaluates the number of affected copies of genes due to mutations in next-generation sequencing data, focusing on somatic and germline mutations in cancer samples.
  • The tool analyzes single nucleotide variants and small insertions/deletions, providing insights into gene-level effects by phasing variants and assessing their impact.
  • ZygosityPredictor is available as an R package on Bioconductor, complete with detailed documentation and example applications for users.

Article Abstract

Summary: 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.

Availability And Implementation: 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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10980564PMC
http://dx.doi.org/10.1093/bioadv/vbae017DOI Listing

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