Bayclone: Bayesian nonparametric inference of tumor subclones using NGS data

Pacific Symposium on Biocomputing

Volumn , Issue , 2015, Pages 467-478

  Sengupta, Subhajit ^a   Wang, Jin ^b   Lee, Juhee ^c   Müller, Peter ^d   Gulukota, Kamalakar ^a   Banerjee, Arunava ^e   Ji, Yuan ^a,f  

^a NORTHSHORE UNIVERSITY HEALTHSYSTEM   (United States)

^b UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

^c University of California Santa Cruz   (United States)

^d UNIVERSITY OF TEXAS AT AUSTIN   (United States)

^e J Crayton Pruitt Family Department of Biomedical Engineering   (United States)

^f UNIVERSITY OF CHICAGO   (United States)

Author keywords

Categorical Indian buffet process; Heterozygosity; Latent feature model; NGS data; Random categorical matrices; Subclones; Tumor heterogeneity

Indexed keywords

BAYESIAN NETWORKS; INFERENCE ENGINES; TUMORS;

FEATURE MODELING; HETEROZYGOSITY; NGS DATA; SUBCLONES; TUMOR HETEROGENEITY;

BARIUM COMPOUNDS;

BAYES THEOREM; BIOLOGY; COMPUTER PROGRAM; COMPUTER SIMULATION; GENETICS; HIGH THROUGHPUT SEQUENCING; HUMAN; LUNG TUMOR; MARKOV CHAIN; MONTE CARLO METHOD; MUTATION; NEOPLASM; NONPARAMETRIC TEST; SINGLE NUCLEOTIDE POLYMORPHISM; STATISTICAL MODEL; STATISTICS AND NUMERICAL DATA;

BAYES THEOREM; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS; LIKELIHOOD FUNCTIONS; LUNG NEOPLASMS; MARKOV CHAINS; MODELS, STATISTICAL; MONTE CARLO METHOD; MUTATION; NEOPLASMS; POLYMORPHISM, SINGLE NUCLEOTIDE; SOFTWARE; STATISTICS, NONPARAMETRIC;

EID: 84971311457     PISSN: 23356928     EISSN: 23356936     Source Type: Journal    
DOI: None     Document Type: Conference Paper

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