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SLDAssay: A software package and web tool for analyzing limiting dilution assays.
Trumble, Ilana M; Allmon, Andrew G; Archin, Nancie M; Rigdon, Joseph; Francis, Owen; Baldoni, Pedro L; Hudgens, Michael G.
Afiliación
  • Trumble IM; Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27599, USA. Electronic address: itrumble@unc.edu.
  • Allmon AG; Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27599, USA.
  • Archin NM; Division of Infectious Diseases, Center for AIDS Research, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC 27599, USA.
  • Rigdon J; Quantitative Sciences Unit, Stanford University School of Medicine, Palo Alto, CA 94304, USA.
  • Francis O; Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27599, USA.
  • Baldoni PL; Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27599, USA.
  • Hudgens MG; Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27599, USA.
J Immunol Methods ; 450: 10-16, 2017 11.
Article en En | MEDLINE | ID: mdl-28733216
ABSTRACT
Serial limiting dilution (SLD) assays are used in many areas of infectious disease related research. This paper presents SLDAssay, a free and publicly available R software package and web tool for analyzing data from SLD assays. SLDAssay computes the maximum likelihood estimate (MLE) for the concentration of target cells, with corresponding exact and asymptotic confidence intervals. Exact and asymptotic goodness of fit p-values, and a bias-corrected (BC) MLE are also provided. No other publicly available software currently implements the BC MLE or the exact methods. For validation of SLDAssay, results from Myers et al. (1994) are replicated. Simulations demonstrate the BC MLE is less biased than the MLE. Additionally, simulations demonstrate that exact methods tend to give better confidence interval coverage and goodness-of-fit tests with lower type I error than the asymptotic methods. Additional advantages of using exact methods are also discussed.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Programas Informáticos / Linfocitos T CD4-Positivos / Infecciones por VIH / Recuento de Linfocito CD4 / Internet Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: J Immunol Methods Año: 2017 Tipo del documento: Article

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Programas Informáticos / Linfocitos T CD4-Positivos / Infecciones por VIH / Recuento de Linfocito CD4 / Internet Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: J Immunol Methods Año: 2017 Tipo del documento: Article