Scholarlink

Somatic variant detection is an important step in the analysis of cancer genomes for basic research as well as precision oncology. Here, we review existing computational methods for identifying somatic mutations from tissue as well as liquid biopsy samples. We then describe steps to run VarNet (Krishnamachari et al., Nat Commun 13:4248, 2022), a variant caller using deep learning, to accurately identify single nucleotide variants (SNVs) and short insertion-deletion (indels) mutations from next-generation sequencing (NGS) of tumor tissue samples.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Identification of Somatic Variants in Cancer Genomes from Tissue and Liquid Biopsy Samples

  • 实验方案

  • 发表日期：

    2025年

查看全文
  • Kiran Krishnamachari,
  • Hanaé Carrié,
  • Anders Jacobsen Skanderup

摘要

Somatic variant detection is an important step in the analysis of cancer genomes for basic research as well as precision oncology. Here, we review existing computational methods for identifying somatic mutations from tissue as well as liquid biopsy samples. We then describe steps to run VarNet (Krishnamachari et al., Nat Commun 13:4248, 2022), a variant caller using deep learning, to accurately identify single nucleotide variants (SNVs) and short insertion-deletion (indels) mutations from next-generation sequencing (NGS) of tumor tissue samples.