Graphical Representation of a Generalized Linear Model-Based Statistical Test Estimating the Fit of the Single-Hit Poisson Model to Limiting Dilution Assays

Bonnefoix, Thierry; Bonnefoix, Philippe; Callanan, Mary; Verdiel, Paul; Sotto, Jean‐Jacques

doi:10.4049/jimmunol.167.10.5725

Cited by 33 publications

(32 citation statements)

References 9 publications

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“…The K3 genomic region was chosen because its primer set had rapid amplification kinetics. Our data were compatible with the single-hit Poisson model (SHPM) as tested by modeling the limiting dilution data according to a generalized linear log-log model fitting the SHPM and checking this model by an appropriate slope test as described by Bonnefoix et al (5). A regression plot of input cell number against log fraction-negative samples was used to estimate the frequency of cells with viral genomes.…”

Section: Cd11bmentioning

confidence: 82%

Selective Gene Expression of Latent Murine Gammaherpesvirus 68 in B Lymphocytes

Marques

Efstathiou

Smith

et al. 2003

J Virol

114

182

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Section: Cd11bmentioning

confidence: 82%

Selective Gene Expression of Latent Murine Gammaherpesvirus 68 in B Lymphocytes

Marques

Efstathiou

Smith

et al. 2003

J Virol

114

182

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“…3A). Based on these three points, it is possible to estimate f p , the frequency of HA-specific responsive T cells, by the method of likelihood maximization (13,21), and the result is presented in Fig. 4 ( f p ϭ 1/1946).…”

Section: The Stepwise Regression Proceduresmentioning

confidence: 99%

“…Modeling limiting dilution data according to a linear log-log regression procedure results in a statistical slope test z that can be graphed to visualize whether the SHPM is compatible or not with the data (13). Based on the current simulated data, the graphical 1.…”

Section: Fitting the Shpm To Limiting Dilution Data By Generalized LImentioning

confidence: 99%

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Detection of Suppressor T Lymphocytes and Estimation of Their Frequency in Limiting Dilution Assays by Generalized Linear Regression Modeling

Bonnefoix

Bonnefoix²,

et al. 2003

The Journal of Immunology

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The estimate of the frequency of suppressor T lymphocytes in unfractionated cell populations remains challenging, mainly because these regulatory cells do not display specific immunophenotypic markers. In this paper, we describe a novel theoretical approach for quantifying the frequency of suppressor cells. This method is based on limiting dilution data modeling, and allows the simultaneous estimation of the frequencies of both proliferating and suppressor cells. We used previously published biological data, characterizing the inhibiting activity of suppressor T cell clones. Starting from these data, we propose a mathematical model describing the interaction between suppressor and proliferating T cells, and applied to a Poisson process. Limiting dilution data corresponding to this non-single-hit, suppressor two-target Poisson model were artificially generated, then modeled according to a generalized linear regression procedure. Deviation from the single-hit Poisson model was revealed by a statistical slope test, and a stepwise analysis of the regression appeared to be an efficient method that strongly argued in favor of the presence of suppressor cells. By using the frequency of proliferating T cells calculated in the first step of the regression, we demonstrated the possibility to provide a reasonable estimate of the frequency of suppressor T cells. Based on these findings, a practical decision-making procedure is given to perform standard analyses of limiting dilution data.

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“…This general shape favored the singlehit kinetics hypothesis. This was checked by a generalized linear model-based statistical slope test that we have tailored to the statistical analysis of LDA (35). Briefly, the equation of the generalized linear log-log regression line, in the form of Y i ϭ ␣ ϩ ␤X i was Y i ϭ Ϫ5.874 ϩ 0.909X i .…”

Section: The Ld Data Setmentioning

confidence: 99%

Quantitating Effector and Regulatory T Lymphocytes in Immune Responses by Limiting Dilution Analysis Modeling

Bonnefoix

Perron

et al. 2005

The Journal of Immunology

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Although there is currently no doubt that regulatory lymphocytes represent a master player in the immune system, a major unresolved problem is the accurate quantitation of these cells among unfractionated cell populations. This difficulty mainly arises because there are no specific immunophenotypic markers that can reliably discriminate between effector and regulatory lymphocytes. To face this problem, we have developed computational models of limiting dilution analyses addressing the question of the accurate estimation of the frequencies of effector and regulatory cells functionally engaged in an immune response. A set of generic equations were provided to form a framework for modeling limiting dilution data, enabling discrimination between qualitatively different models of suppression. These models include either one or two subpopulations of regulatory cells, featured by either low or potent regulatory activity. The potential of this modeling approach was illustrated by the accurate determination of the frequencies of effector and regulatory T lymphocytes in one real limiting dilution experiment of CD4+CD25+ T lymphocytes performed in the context of an allogeneic response in the human system. The crucial advantage of the limiting dilution method over the “static, phenotype-based” method is the dynamic evaluation of effector and regulatory T cell biology through their actual functional activity.

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Graphical Representation of a Generalized Linear Model-Based Statistical Test Estimating the Fit of the Single-Hit Poisson Model to Limiting Dilution Assays

Cited by 33 publications

References 9 publications

Selective Gene Expression of Latent Murine Gammaherpesvirus 68 in B Lymphocytes

Selective Gene Expression of Latent Murine Gammaherpesvirus 68 in B Lymphocytes

Detection of Suppressor T Lymphocytes and Estimation of Their Frequency in Limiting Dilution Assays by Generalized Linear Regression Modeling

Quantitating Effector and Regulatory T Lymphocytes in Immune Responses by Limiting Dilution Analysis Modeling

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