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Bioinformatics ; 28(7): 1045-7, 2012 Apr 01.
Artigo em Inglês | MEDLINE | ID: mdl-22333246

RESUMO

MOTIVATION: The massive data produced by next-generation sequencing require advanced statistical tools. We address estimating the total diversity or species richness in a population. To date, only relatively simple methods have been implemented in available software. There is a need for software employing modern, computationally intensive statistical analyses including error, goodness-of-fit and robustness assessments. RESULTS: We present CatchAll, a fast, easy-to-use, platform-independent program that computes maximum likelihood estimates for finite-mixture models, weighted linear regression-based analyses and coverage-based non-parametric methods, along with outlier diagnostics. Given sample 'frequency count' data, CatchAll computes 12 different diversity estimates and applies a model-selection algorithm. CatchAll also derives discounted diversity estimates to adjust for possibly uncertain low-frequency counts. It is accompanied by an Excel-based graphics program. AVAILABILITY: Free executable downloads for Linux, Windows and Mac OS, with manual and source code, at www.northeastern.edu/catchall. CONTACT: jab18@cornell.edu.


Assuntos
Genética Populacional/métodos , Genética Populacional/estatística & dados numéricos , Modelos Estatísticos , Software , Algoritmos , Bacteriófagos/genética , Biologia Computacional/métodos , Funções Verossimilhança , Modelos Lineares
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