Modeling of inter-sample variation in flow cytometric data with the joint clustering and matching procedure.

Lee, Sharon X; McLachlan, Geoffrey J; Pyne, Saumyadipta

Lee, Sharon X; McLachlan, Geoffrey J; Pyne, Saumyadipta.

Affiliation

Lee SX; Department of Mathematics, University of Queensland, St. Lucia, Queensland, 4072, Australia.
McLachlan GJ; Department of Mathematics, University of Queensland, St. Lucia, Queensland, 4072, Australia.
Pyne S; Indian Institute of Public Health Hyderabad (IIPHH), Plot No. 1, A.N.V. Arcade, Amar Co-op Society, Kavuri Hills, Madhapur, Hyderabad, AP, 500033, India.

Cytometry A ; 89(1): 30-43, 2016 Jan.

Article in En | MEDLINE | ID: mdl-26492316

Subject(s)

Biomarkers/blood; Computational Biology/methods; Electronic Data Processing/methods; Flow Cytometry/methods; Membrane Proteins/analysis; Pattern Recognition, Automated/methods; Algorithms; Cluster Analysis; Data Interpretation, Statistical; Humans; Leukemia, Myeloid, Acute/diagnosis; Lymphoma, Follicular/diagnosis; Models, Theoretical; West Nile Fever/diagnosis

Key words

EM algorithm; JCM; class template; classification; clustering; flow cytometry; inter-sample variation; matching; skew mixture models

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Electronic Data Processing / Pattern Recognition, Automated / Biomarkers / Computational Biology / Flow Cytometry / Membrane Proteins Type of study: Diagnostic_studies / Prognostic_studies Limits: Humans Language: En Journal: Cytometry A Year: 2016 Type: Article Affiliation country: Australia

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