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A machine learning approach to optimizing cell-free DNA sequencing panels: with an application to prostate cancer

BACKGROUND: Cell-free DNA’s (cfDNA) use as a biomarker in cancer is challenging due to genetic heterogeneity of malignancies and rarity of tumor-derived molecules. Here we describe and demonstrate a novel machine-learning guided panel design strategy for improving the detection of tumor variants in...

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Detalles Bibliográficos
Autores principales: Cario, Clinton L., Chen, Emmalyn, Leong, Lancelote, Emami, Nima C., Lopez, Karen, Tenggara, Imelda, Simko, Jeffry P., Friedlander, Terence W., Li, Patricia S., Paris, Pamela L., Carroll, Peter R., Witte, John S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7456018/
https://www.ncbi.nlm.nih.gov/pubmed/32859160
http://dx.doi.org/10.1186/s12885-020-07318-x