Bayesian sample size determination for the accurate identification of the bacterial subtypes. 2009

Mohamad Amin Pourhoseingholi, and Anahita Dezfoulian, and Malihe Nasiri, and Hosein Dabiri, and Mohammad Reza Zali
Research Center of Gastroenterology and Liver diseases, Shahid Beheshti University, (M.C), Tehran, Iran. Aminphg@gmail.com

OBJECTIVE Sample size estimation is a major component of the design of virtually every experiment in biosciences. Microbiologists face a challenge when allocating resources to surveys designed to determine the sampling unit of bacterial strains of interest. In this study we derived a Bayesian approach with a dirichlet prior based on a pilot study in to find an adequate sample size for E. coli subtypes' determination. METHODS Five strains of E. coli (st genes, eae gene, stx1 and stx2 genes, ial gene) were used in this study. The strains were grown overnight at 37 degrees C to obtain strains in a linear growth phase, according to McFarland's score. The resulting supernatants were used as templates in the PCR reactions. Then the results used with Dirichlet Distribution as a prior to find the Bayesian optimum sample size. RESULTS 100 colonies were harvested from plate and examined in the PCR reaction, 50 colonies showed no specific genes, 40 detected as eae gene (78.8%), 6 colonies stx2 gene (11.7%), 2 colonies st gene (3.9%), 2 colonies stxl2 gene (3.9%) and only 1 colony detected as lall gene (1.9%). First according to the frequentist view sample size calculated indicating a different range of sample size from 25 colonies to unusual number, 4475 colonies. Then using Bayesian approach by posterior expectations instead of pilot results sample size were fund from the range of 291 colonies to 443 colonies. CONCLUSIONS The results indicated that Bayesian approach technique leads to optimal sample size with similar power in compare to traditional technique where sample size calculated without any prior information.

UI MeSH Term Description Entries
D010641 Phenotype The outward appearance of the individual. It is the product of interactions between genes, and between the GENOTYPE and the environment. Phenotypes
D010865 Pilot Projects Small-scale tests of methods and procedures to be used on a larger scale if the pilot study demonstrates that these methods and procedures can work. Pilot Studies,Pilot Study,Pilot Project,Project, Pilot,Projects, Pilot,Studies, Pilot,Study, Pilot
D012107 Research Design A plan for collecting and utilizing data so that desired information can be obtained with sufficient precision or so that an hypothesis can be tested properly. Experimental Design,Data Adjustment,Data Reporting,Design, Experimental,Designs, Experimental,Error Sources,Experimental Designs,Matched Groups,Methodology, Research,Problem Formulation,Research Methodology,Research Proposal,Research Strategy,Research Technics,Research Techniques,Scoring Methods,Adjustment, Data,Adjustments, Data,Data Adjustments,Design, Research,Designs, Research,Error Source,Formulation, Problem,Formulations, Problem,Group, Matched,Groups, Matched,Matched Group,Method, Scoring,Methods, Scoring,Problem Formulations,Proposal, Research,Proposals, Research,Reporting, Data,Research Designs,Research Proposals,Research Strategies,Research Technic,Research Technique,Scoring Method,Source, Error,Sources, Error,Strategies, Research,Strategy, Research,Technic, Research,Technics, Research,Technique, Research,Techniques, Research
D004926 Escherichia coli A species of gram-negative, facultatively anaerobic, rod-shaped bacteria (GRAM-NEGATIVE FACULTATIVELY ANAEROBIC RODS) commonly found in the lower part of the intestine of warm-blooded animals. It is usually nonpathogenic, but some strains are known to produce DIARRHEA and pyogenic infections. Pathogenic strains (virotypes) are classified by their specific pathogenic mechanisms such as toxins (ENTEROTOXIGENIC ESCHERICHIA COLI), etc. Alkalescens-Dispar Group,Bacillus coli,Bacterium coli,Bacterium coli commune,Diffusely Adherent Escherichia coli,E coli,EAggEC,Enteroaggregative Escherichia coli,Enterococcus coli,Diffusely Adherent E. coli,Enteroaggregative E. coli,Enteroinvasive E. coli,Enteroinvasive Escherichia coli
D000818 Animals Unicellular or multicellular, heterotrophic organisms, that have sensation and the power of voluntary movement. Under the older five kingdom paradigm, Animalia was one of the kingdoms. Under the modern three domain model, Animalia represents one of the many groups in the domain EUKARYOTA. Animal,Metazoa,Animalia
D001499 Bayes Theorem A theorem in probability theory named for Thomas Bayes (1702-1761). In epidemiology, it is used to obtain the probability of disease in a group of people with some characteristic on the basis of the overall rate of that disease and of the likelihood of that characteristic in healthy and diseased individuals. The most familiar application is in clinical decision analysis where it is used for estimating the probability of a particular diagnosis given the appearance of some symptoms or test result. Bayesian Analysis,Bayesian Estimation,Bayesian Forecast,Bayesian Method,Bayesian Prediction,Analysis, Bayesian,Bayesian Approach,Approach, Bayesian,Approachs, Bayesian,Bayesian Approachs,Estimation, Bayesian,Forecast, Bayesian,Method, Bayesian,Prediction, Bayesian,Theorem, Bayes
D015233 Models, Statistical Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc. Probabilistic Models,Statistical Models,Two-Parameter Models,Model, Statistical,Models, Binomial,Models, Polynomial,Statistical Model,Binomial Model,Binomial Models,Model, Binomial,Model, Polynomial,Model, Probabilistic,Model, Two-Parameter,Models, Probabilistic,Models, Two-Parameter,Polynomial Model,Polynomial Models,Probabilistic Model,Two Parameter Models,Two-Parameter Model
D015983 Selection Bias The introduction of error due to systematic differences in the characteristics between those selected and those not selected for a given study. In sampling bias, error is the result of failure to ensure that all members of the reference population have a known chance of selection in the sample. Bias, Selection,Sampling Bias,Sampling Biases,Sampling Error,Selection Biases,Bias, Sampling,Biases, Sampling,Biases, Selection,Error, Sampling,Errors, Sampling,Sampling Errors
D016133 Polymerase Chain Reaction In vitro method for producing large amounts of specific DNA or RNA fragments of defined length and sequence from small amounts of short oligonucleotide flanking sequences (primers). The essential steps include thermal denaturation of the double-stranded target molecules, annealing of the primers to their complementary sequences, and extension of the annealed primers by enzymatic synthesis with DNA polymerase. The reaction is efficient, specific, and extremely sensitive. Uses for the reaction include disease diagnosis, detection of difficult-to-isolate pathogens, mutation analysis, genetic testing, DNA sequencing, and analyzing evolutionary relationships. Anchored PCR,Inverse PCR,Nested PCR,PCR,Anchored Polymerase Chain Reaction,Inverse Polymerase Chain Reaction,Nested Polymerase Chain Reaction,PCR, Anchored,PCR, Inverse,PCR, Nested,Polymerase Chain Reactions,Reaction, Polymerase Chain,Reactions, Polymerase Chain
D018401 Sample Size The number of units (persons, animals, patients, specified circumstances, etc.) in a population to be studied. The sample size should be big enough to have a high likelihood of detecting a true difference between two groups. (From Wassertheil-Smoller, Biostatistics and Epidemiology, 1990, p95) Sample Sizes,Size, Sample,Sizes, Sample

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