Bayesian identification of bacterial strains from sequencing data
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Abstract
Rapidly assaying the diversity of a bacterial species present in a sample obtained from a hospital patient or an environmental source has become possible after recent technological advances in DNA sequencing. For several applications it is important to accurately identify the presence and estimate relative abundances of the target organisms...
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staphylococcus aureus , DNA, Bacterial , FOS: Computer and information sciences , strain identification , Quantitative Biology - Quantitative Methods , Statistics - Applications , Humans , Quantitative Biology - Genomics , Applications (stat.AP) , Plant biology, microbiology, virology , Quantitative Methods (q-bio.QM) , Genomics (q-bio.GN) , Computer and information sciences , Bacteria , pathogenic bacteria , Bayes Theorem , Sequence Analysis, DNA , Bacterial Typing Techniques , FOS: Biological sciences , probabilistic modelling , /dk/atira/pure/subjectarea/asjc/2700/2700; name=General Medicine , Genome, Bacterial , Software , Research Paper
