Probabilistic Mixture Models Improve Calibration of Panel-derived Tumor Mutational Burden in the Context of both Tumor-normal and Tumor-only Sequencing.

Anaya, Jordan; Sidhom, John-William; Cummings, Craig A; Baras, Alexander S

Anaya, Jordan; Sidhom, John-William; Cummings, Craig A; Baras, Alexander S.

Afiliación

Anaya J; Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Sidhom JW; The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Cummings CA; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Baras AS; Bloombergâ¼Kimmel Institute for Cancer Immunotherapy, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland.

Cancer Res Commun ; 3(3): 501-509, 2023 03.

Article en En | MEDLINE | ID: mdl-36999044

Asunto(s)

Neoplasias; Humanos; Calibración; Neoplasias/genética; Biomarcadores de Tumor/genética; Mutación; Genómica

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Cancer Res Commun Año: 2023 Tipo del documento: Article Pais de publicación: Estados Unidos

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