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debCAM: a bioconductor R package for fully unsupervised deconvolution of complex tissues.
Chen, Lulu; Wu, Chiung-Ting; Wang, Niya; Herrington, David M; Clarke, Robert; Wang, Yue.
Afiliación
  • Chen L; Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.
  • Wu CT; Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.
  • Wang N; Search Ranking Unit, Google LLC, Mountain View, CA 94043, USA.
  • Herrington DM; Department of Internal Medicine, Wake Forest University, Winston-Salem, NC 27157, USA.
  • Clarke R; Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC 20057, USA.
  • Wang Y; Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.
Bioinformatics ; 36(12): 3927-3929, 2020 06 01.
Article en En | MEDLINE | ID: mdl-32219387
ABSTRACT

SUMMARY:

We develop a fully unsupervised deconvolution method to dissect complex tissues into molecularly distinctive tissue or cell subtypes based on bulk expression profiles. We implement an R package, deconvolution by Convex Analysis of Mixtures (debCAM) that can automatically detect tissue/cell-specific markers, determine the number of constituent subtypes, calculate subtype proportions in individual samples and estimate tissue/cell-specific expression profiles. We demonstrate the performance and biomedical utility of debCAM on gene expression, methylation, proteomics and imaging data. With enhanced data preprocessing and prior knowledge incorporation, debCAM software tool will allow biologists to perform a more comprehensive and unbiased characterization of tissue remodeling in many biomedical contexts. AVAILABILITY AND IMPLEMENTATION http//bioconductor.org/packages/debCAM. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Asunto(s)

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Proteómica Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Proteómica Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos