The 'rbioacc' package.

Description

A DESCRIPTION OF THE PACKAGE

Author(s)

Maintainer: Virgile Baudrot virgile.baudrot@qonfluens.com

Authors:

• Sandrine Charles

• Miléna Kaag

• Aude Ratier

• Aurélie Siberchicot

Other contributors:

• Ophélia Gestin [contributor]

• Christelle Lopes [contributor]

• Gauthier Multari [contributor]

• Alain Pavé [contributor]

References

Stan Development Team (NA). RStan: the R interface to Stan. R package version NA. https://mc-stan.org

See Also

Useful links:

• https://gitlab.in2p3.fr/mosaic-software/rbioacc

• Report bugs at https://gitlab.in2p3.fr/mosaic-software/rbioacc/-/issues

A simple implementation of to pivot_longer of tidyr

Description

A simple implementation of to pivot_longer of tidyr

Usage

.fonte(df, names_to, values_to)

Arguments

Value

The data frame with a "lengthens" shape: more rows, less columns

Return column matching "expw", "exps", "expf", "exppw" of a data.frame

Description

Return column matching "expw", "exps", "expf", "exppw" of a data.frame

Usage

.index_col_exposure(data_frame)

Arguments

Value

A vector of numeric

Return column matching "concX" of a data.frame where X is metabolite

Description

Return column matching "concX" of a data.frame where X is metabolite

Usage

.index_col_metabolite(data_frame)

Arguments

Value

A vector of numeric

Check if two vectors x and y are equal after remove Inf

Description

Check if two vectors x and y are equal after remove Inf

Usage

.is_equal_rmInf(x, y)

Arguments

Value

A logical value

Data on Chironomus with several exposure routes.

Description

Data on Chironomus with several exposure routes.

Usage

data(Chiro_Creuzot)

Format

A dataframe with 24 observations on the following four variables:

time

A vector of class numeric with the time points in days.

expw

A vector of class numeric with the exposure in water.

expw

A vector of class numeric with the exposure in pore water.

replicate

A vector of class integer for replicate identification.

conc

A vector of class numeric with concentration in organism.

concm1

A vector of class numeric with metabolite concentration in organism.

concm2

A vector of class numeric with metabolite concentration in organism.

Data on Chironomus exposed to benzoapyrene

Description

Data on Chironomus exposed to benzoapyrene

Usage

data(Chironomus_benzoapyrene)

Data on Sialis lutaria exposure time series

Description

Data on Sialis lutaria exposure time series

Usage

data(Exposure_Sialis_lutaria)

Data on Gammarus exposed to azoxistrobine

Description

Data on Gammarus exposed to azoxistrobine

Usage

data(Gammarus_azoxistrobine_1d_Rosch2017)

Data on Sialis lutaria internal time series

Description

Data on Sialis lutaria internal time series

Usage

data(Internal_Sialis_lutaria)

Male Gammarus fossarum exposed to Hg spiked water. Three exposure concentrations were tested in triplicates. The duration of the accumulation phase is 4 days for 0.0000708021 and 0.000283208 \mu g.m L^{-1} exposure concentrations, and 7 days for 0.000141604 \mu g.m L^{-1} exposure concentration.

Description

Male Gammarus fossarum exposed to Hg spiked water. Three exposure concentrations were tested in triplicates. The duration of the accumulation phase is 4 days for 0.0000708021 and 0.000283208 \mu g.m L^{-1} exposure concentrations, and 7 days for 0.000141604 \mu g.m L^{-1} exposure concentration.

Usage

data(Male_Gammarus_Merged)

Format

A dataframe with 72 observations on the following four variables:

time

A vector of class numeric with the time points in days.

expw

A vector of class numeric with Hg exposure in water in \mu g.m L^{-1}.

replicate

A vector of class integer for replicate identification.

conc

A vector of class numeric with Hg concentration in organism in \mu g.m L^{-1}.

References

Ciccia, T. (2019). Accumulation et devenir du mercure chez l'espèce sentinelle Gammarus fossarum : de l'expérimentation au développement d'un modèle toxicocinétique multi-compartiments. Rapport de stage de Master 2, INRAE.

Bio-accumulation data set for Gammarus fossarum exposed to Hg spiked water.

Description

Male Gammarus fossarum exposed to Hg spiked water. A single exposure concentration was tested. The duration of the accumulation phase is 4 days.

Usage

data(Male_Gammarus_Single)

Format

A dataframe with 23 observations on the following four variables:

time

A vector of class numeric with the time points in days.

expw

A vector of class numeric with Hg exposure in water in \mu g.m L^{-1}.

replicate

A vector of class integer for replicate identification.

conc

A vector of class numeric with Hg concentration in organism in \mu g.m L^{-1}.

References

Ciccia, T. (2019). Accumulation et devenir du mercure chez l'espèce sentinelle Gammarus fossarum : de l'expérimentation au développement d'un modèle toxicocinétique multi-compartiments. Rapport de stage de Master 2, INRAE.

Male Gammarus pulex exposed to seanine spiked water. A single exposure concentration was tested. The duration of the accumulation phase is 1.417 days. Three metabolites were quantified. The growth of organism was included.

Description

Male Gammarus pulex exposed to seanine spiked water. A single exposure concentration was tested. The duration of the accumulation phase is 1.417 days. Three metabolites were quantified. The growth of organism was included.

Usage

data(Male_Gammarus_seanine_growth)

Format

A dataframe with 22 observations on the following four variables:

time

A vector of class numeric with the time points in days.

expw

A vector of class numeric with seanine exposure in water in \mu g.m L^{-1}.

replicate

A vector of class integer for replicate identification.

conc

A vector of class numeric with concentration in organism.

concm1

A vector of class numeric with metabolite concentration in organism.

concm2

A vector of class numeric with metabolite concentration in organism.

concm3

A vector of class numeric with metabolite concentration in organism.

growth

A vector of class numeric with growth of the organism.

References

Ashauer, R. et al. (2012). Significance of xenobiotic metabolism for bioaccumulation kinetics of organic chemicals in Gammarus pulex. Environmental Science Technology, 46: 3498-3508.

Data on Oncorhynchus exposition

Description

Data on Oncorhynchus exposition

Usage

data(Oncorhynchus_two)

Biaccumulation metrics

Description

Biaccumulation metrics

Usage

bioacc_metric(fit, ...)

## S3 method for class 'fitTK'
bioacc_metric(fit, type = "k", route = "all", ...)

Arguments

Value

a data frame

Correlations between parameters: colored matrix

Description

Correlations between parameters: colored matrix

Usage

corrMatrix(fit)

Arguments

Value

A heatmap of class ggplot.

Correlations between parameters: pairs plot

Description

Correlations between parameters: pairs plot

Usage

corrPlot(fit, plots = c("all", "deterministic", "stochastic"))

Arguments

Value

A pairsplot of class ggmatrix containing planes of parameter pairs (lower triangle), marginal posterior distribution of each parameter (diagonal) and Pearson correlation coefficients (upper triangle)

Data frame of Posterior over Prior

Description

Data frame of Posterior over Prior

Data frame of Posterior over Prior

Usage

df_PriorPost(fit, ...)

## S3 method for class 'fitTK'
df_PriorPost(fit, select = "all", ...)

Arguments

Value

An object of class data.frame

PPC data.frame

Description

This is the generic ppc S3 method for plots of the predicted values along with 95\ versus the observed values for fitTK objects.

Usage

df_ppc(fit, ...)

## S3 method for class 'fitTK'
df_ppc(fit, ...)

ppc(fit, ...)

## S3 method for class 'fitTK'
ppc(fit, ...)

Arguments

Details

The black points show the observed number of survivors (pooled replicates, on X-axis) against the corresponding predicted number (Y-axis). Predictions come along with 95\ intervals, which are depicted in green when they contain the observed value and in red otherwise. Samples with equal observed value are shifted on the X-axis. For that reason, the bisecting line (y = x), is represented by steps when observed values are low. That way we ensure green intervals do intersect the bisecting line.

Value

A data frame with median and 95\

a plot of class ggplot

Equations of the mathematical model used for the fit

Description

Equations of the mathematical model used for the fit

Usage

equations(fit, object)

Arguments

Value

A vector of strings each containing an equation

Retrieve exposure routes names from object

Description

Retrieve exposure routes names from object

Usage

exposure_names(object)

Arguments

Value

A vector of string

Posterior predictive check

Description

Posterior predictive check

Bayesian inference of TK model with Stan

Bayesian inference of TK model with variable exposure profile (BETA version)

Usage

fitTK(stanTKdata, ...)

## S3 method for class 'stanTKdataCST'
fitTK(stanTKdata, ...)

## S3 method for class 'stanTKdataVAR'
fitTK(stanTKdata, ...)

Arguments

Value

An object of class fitTK containing two object: stanTKdata the data set used for inference and stanfit returned by rstan::sampling

Traces of MCMC iterations

Description

Traces of MCMC iterations

Usage

mcmcTraces(fit, plots = "all")

Arguments

Value

A traceplot of class ggplot.

Create a list giving data and parameters to use in the model inference.

Description

Create a list giving data and parameters to use in the model inference.

Usage

modelData(object, ...)

## S3 method for class 'data.frame'
modelData(object, time_accumulation, elimination_rate = NA, ...)

Arguments

Value

A list with data and parameters require for model inference.

Create a list giving data and parameters to use in the model inference.

Description

Create a list giving data and parameters to use in the model inference.

Usage

modelData_ode(
  df_exposure,
  df_internal,
  y0 = 1,
  t0 = -0.001,
  unifMax = 10,
  time_accumulation = NULL,
  minK = -5,
  maxK = 5,
  ...
)

modelData_ode(
  df_exposure,
  df_internal,
  y0 = 1,
  t0 = -0.001,
  unifMax = 10,
  time_accumulation = NULL,
  minK = -5,
  maxK = 5,
  ...
)

Arguments

Value

A list with data and parameters require for model inference.

Plot function for object of class bioaccMetric

Description

Plot function for object of class bioaccMetric

Usage

## S3 method for class 'bioaccMetric'
plot(x, ...)

Arguments

Value

A plot of class ggplot

Plotting method for fitTK objects

Description

This is the generic plot S3 method for the fitTK. It plots the fit obtained for each variable in the original dataset.

Usage

## S3 method for class 'fitTK'
plot(x, time_interp = NULL, ...)

Arguments

Value

a plot of class ggplot

Plotting method for predictTK objects

Description

This is the generic plot S3 method for the predictTK.

Usage

## S3 method for class 'predictTK'
plot(x, ...)

## S3 method for class 'predictTKstan'
plot(x, add_data = FALSE, ...)

Arguments

Value

A plot of class ggplot

Plot Posterior over Prior

Description

Plot Posterior over Prior

Plot Posterior over Prior

Usage

plot_PriorPost(x, ...)

## S3 method for class 'fitTK'
plot_PriorPost(x, select = "all", ...)

## S3 method for class 'df_PP'
plot_PriorPost(x, select = "all", ...)

Arguments

Value

A plot of class ggplot.

A plot of class ggplot.

Plot exposure profile

Description

Plot exposure profile

Usage

plot_exposure(object)

Arguments

Value

a plot of class ggplot

Prediction function using fitTK object

Description

Use when parameter are manually given by the user.

Usage

## S3 method for class 'fitTK'
predict(object, data, mcmc_size = NULL, fixed_init = TRUE, ...)

predict_stan(
  object,
  data,
  mcmc_size = NULL,
  fixed_init = TRUE,
  time_interp = NULL,
  iter = 1000,
  ...
)

predict_manual(
  param,
  data,
  time_accumulation = NULL,
  C0 = 0,
  G0 = NA,
  gmax = NA
)

Arguments

Value

An object of class predictTK

An object of class predictTK

Potential Scale Reduction Factors (PSRF) of the parameters

Description

Potential Scale Reduction Factors (PSRF) of the parameters

Usage

psrf(fit)

Arguments

Value

An object of class data.frame with two columns: PSRF and parameter

a data frame with Potential Scale Reduction Factors

Quantiles of parameters

Description

Quantiles of parameters

Usage

quantile_table(fit, probs = c(0.025, 0.5, 0.975))

Arguments

Value

A data frame with quantiles

Replace element of a vector

Description

Replace element of a vector

Usage

replace_(x, from, to)

Arguments

Value

a vector

Examples

 
replace_(1:10,c(2,4,5,8), c(0,0,0,0))
replace_(c(1,2,2,3,2),c(3,2), c(4,5))

remove message and warning

Description

Remove message and warning which is usefull when running a model and removing all outputs messages and warnings#'

Usage

rmMessWarn(...)

Arguments

Return the time at 95% depuration of the parent component

Description

Return the time at 95% depuration of the parent component

Usage

t95(fit)

Arguments

Value

a numeric object

Widely Applicable Information Criterion (WAIC)

Description

Compute WAIC using the waic() method of the loo package.

Usage

waic(fit)

Arguments

Value

A numeric containing the WAIC