VIC

VIC (Variant Interpretation for Cancer) is a semi-automated software tool to streamline the interpretation of somatic sequence variants in cancer based on the guidelines published by the Association for Molecular Pathology (AMP), American Society of Clinical Oncology (ASCO), and College of American Pathologists (CAP) in 2017. The tool aims to accelerate the interpretation process and minimize individual biases that may arise from the manual implementation of the guidelines.

Key features of VIC include:

1. Automatic classification of sequence variants using pre-annotated files based on several criteria outlined in the guidelines.

2. users can integrate additional evidence to optimize the interpretation of clinical impacts.

3. Time-efficient and conservative classification of somatic variants under default settings, particularly for variants with strong and potential clinical significance.

4. Customizable settings that fit into clinical laboratories' analytical pipelines facilitate the laborious process of somatic variant interpretation.

Topic

Oncology;Pathology;Allergy, clinical immunology and immunotherapeutics

Detail

  • Operation: Variant calling;Parsing;Variant classification

  • Software interface: Command-line user interface

  • Language: Java

  • License: Not stated

  • Cost: Free of charge

  • Version name: -

  • Credit: Simcere Diagnostics Co., Ltd. and CHOP Research Institute.

  • Input: -

  • Output: -

  • Contact: Max M. He maxm.he@outlook.com ,Kai Wang wangk@email.chop.edu

  • Collection: -

  • Maturity: -

Publications

  • Variant Interpretation for Cancer (VIC): a computational tool for assessing clinical impacts of somatic variants.
  • He MM, et al. Variant Interpretation for Cancer (VIC): a computational tool for assessing clinical impacts of somatic variants. Variant Interpretation for Cancer (VIC): a computational tool for assessing clinical impacts of somatic variants. 2019; 11:53. doi: 10.1186/s13073-019-0664-4
  • https://doi.org/10.1186/S13073-019-0664-4
  • PMID: 31443733
  • PMC: PMC6708137

Download and documentation


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