Reproducible analysis of disease space via principal components using the novel R package syndRomics.

Torres-Espín, Abel; Chou, Austin; Huie, J Russell; Kyritsis, Nikos; Upadhyayula, Pavan S; Ferguson, Adam R

Torres-Espín, Abel; Chou, Austin; Huie, J Russell; Kyritsis, Nikos; Upadhyayula, Pavan S; Ferguson, Adam R.

Afiliación

Torres-Espín A; Weill Institute for Neurosciences, Brain and Spinal Injury Center (BASIC), University of California, San Francisco (UCSF), San Francisco, United States.
Chou A; Department of Neurological Surgery, University of California San Francisco (UCSF), San Francisco, United States.
Huie JR; Zuckerberg San Francisco General Hospital and Trauma Center, San Francisco, United States.
Kyritsis N; Weill Institute for Neurosciences, Brain and Spinal Injury Center (BASIC), University of California, San Francisco (UCSF), San Francisco, United States.
Upadhyayula PS; Department of Neurological Surgery, University of California San Francisco (UCSF), San Francisco, United States.
Ferguson AR; Zuckerberg San Francisco General Hospital and Trauma Center, San Francisco, United States.

Elife ; 102021 01 14.

Article en En | MEDLINE | ID: mdl-33443012

Asunto(s)

Biología Computacional; Salud Pública/métodos; Programas Informáticos; Humanos; Análisis de Componente Principal; Síndrome

Palabras clave

R package; computational biology; disease pattern discovery; medicine; multivariate analysis; none; nonlinear PCA; principal component analysis pca; syndromics; systems biology

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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Salud Pública / Biología Computacional Límite: Humans Idioma: En Revista: Elife Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos

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