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Assessing the merits: an opinion on the effectiveness of simulation techniques in tumor subclonal reconstruction.
Lai, Jiaying; Yang, Yi; Liu, Yunzhou; Scharpf, Robert B; Karchin, Rachel.
Afiliação
  • Lai J; Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, United States.
  • Yang Y; Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, United States.
  • Liu Y; Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, United States.
  • Scharpf RB; Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21231, United States.
  • Karchin R; Department of Oncology, Johns Hopkins Medical Institutions, Baltimore, MD 21231, United States.
Bioinform Adv ; 4(1): vbae094, 2024.
Article em En | MEDLINE | ID: mdl-38948008
ABSTRACT

Summary:

Neoplastic tumors originate from a single cell, and their evolution can be traced through lineages characterized by mutations, copy number alterations, and structural variants. These lineages are reconstructed and mapped onto evolutionary trees with algorithmic approaches. However, without ground truth benchmark sets, the validity of an algorithm remains uncertain, limiting potential clinical applicability. With a growing number of algorithms available, there is urgent need for standardized benchmark sets to evaluate their merits. Benchmark sets rely on in silico simulations of tumor sequence, but there are no accepted standards for simulation tools, presenting a major obstacle to progress in this field. Availability and implementation All analysis done in the paper was based on publicly available data from the publication of each accessed tool.

Texto completo: 1 Coleções: 01-internacional Temas: Geral Base de dados: MEDLINE Idioma: En Revista: Bioinform Adv Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Temas: Geral Base de dados: MEDLINE Idioma: En Revista: Bioinform Adv Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos