Performance determinants of unsupervised clustering methods for microbiome data.

Shi, Yushu; Zhang, Liangliang; Peterson, Christine B; Do, Kim-Anh; Jenq, Robert R

Shi, Yushu; Zhang, Liangliang; Peterson, Christine B; Do, Kim-Anh; Jenq, Robert R.

Afiliación

Shi Y; Department of Statistics, The University of Missouri, Columbia, 209D Middlebush Hall, Columbia, 65201, MO, USA.
Zhang L; Department of Population and Quantitative Health Sciences, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, 44106, OH, USA.
Peterson CB; Department of Biostatistics, The University of Texas MD Anderson Cancer Center, 1400 Pressler St, 4th Floor, Houston, 77030, TX, USA.
Do KA; Department of Biostatistics, The University of Texas MD Anderson Cancer Center, 1400 Pressler St, 4th Floor, Houston, 77030, TX, USA.
Jenq RR; Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, 1881 East Road, 3SCR5.4102, Unit 1954, Houston, 77054, TX, USA. rrjenq@mdanderson.org.

Microbiome ; 10(1): 25, 2022 02 05.

Article en En | MEDLINE | ID: mdl-35120564

Asunto(s)

Microbiota; Análisis por Conglomerados; Microbiota/genética

Palabras clave

Beta diversity; Bray Curtis distance; Unsupervised clustering; Unweighted UniFrac distance

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Microbiota Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Microbiome Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos

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