# sebkopf/isocyclr

an educational tool to facilitate the modeling of isotopic effects through biogeochemical pathways and cycles
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DESCRIPTION
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NAMESPACE

# isocyclr

This R package is intended as an educational tool to facilitate the modeling of isotopic effects through biogeochemical pathways and cycles including non-steady state and steady-state solutions. Core functionality for the construction of reaction networks and the corresponding system of differential equations is fully implemented and can be explored for multiple isotope systems in parallel. Automatically generated reaction diagrams and symbolic representation of the system of differential equations make it easy to check system structure. However, the package is still very much a work in progress and only generic custom and standard reaction types are implemented at this point as well as rudimentary computation of steady-state solutions. All implemented functionality is automatically tested with pretty good coverage to avoid updates accidentally breaking existing code.

## Installation

install.packages("devtools")
# with vignettes
devtools::install_github("sebkopf/isocyclr", build_vignettes = TRUE)

# OR ALTNERATIVELY:
# without vignettes (faster and recommended if build_vignettes = TRUE errors)
devtools::install_github("sebkopf/isocyclr", build_vignettes = FALSE)


Example code for use of isocyclr is always availabe in its latest interation in the vignettes of the package which can be explored from within R with the command browseVignettes("isocyclr") if the vignettes are installed.

# Example vignette

Load isocyclr and other packages used in these examples. Help on all functions is available within R (e.g. via ?add_standard_reaction).

library(isocyclr)
library(ggplot2)
library(magrittr)
library(dplyr)
library(tidyr)


## Set up reaction path

Set up a reaction network akin to Figure 2 in John Hayes' classic Fractionation of carbon and hydrogen isotopes in biosynthetic processes. Rev Mineral Geochem 43, 225–277. (2001).

path <- isopath() %>%
add_component("AA", carbon, variable = FALSE) %>%
add_component(c("DD", "GG", "II"), carbon, variable = FALSE) %>% # out flux
add_standard_reaction(AA == B, eps.carbon = e1, flux = dm) %>%
add_standard_reaction(B == C, eps.carbon = e2, flux = dm) %>%
add_standard_reaction(C == D, eps.carbon = e3, flux = f3 * dm) %>%
add_standard_reaction(D == DD, eps.carbon = 0, flux = f3 * dm, name = "D out") %>%
add_standard_reaction(C == E, eps.carbon = e4, flux = (1-f3) * dm) %>%
add_standard_reaction(E == F, eps.carbon.eq = e5, flux = (1-f3) *dm, eq_ratio = "P/S") %>%
add_standard_reaction(F == G, eps.carbon = e6, flux = (1-f3) *f6 * dm) %>%
add_standard_reaction(G == GG, eps.carbon = 0, flux = (1-f3) *f6 * dm, name = "G out") %>%
add_standard_reaction(F == H, eps.carbon = e7, flux = (1-f3) * (1-f6) * dm) %>%
add_standard_reaction(H == I, eps.carbon = e8, flux = (1-f3) * (1-f6) * dm) %>%
add_standard_reaction(I == II, eps.carbon = 0, flux = (1-f3) * (1-f6) * dm, name = "I out")


#### Schematic

path %>% generate_reaction_diagram() + coord_equal()


#### System of differential equations

The get_ode_matrix() makes it easy to look at the system of differential equations generated for the reaction network. To test what it evaluates to for the first step with the given parameters, take a look at the evaluate=TRUE parameter in ?get_ode_matrix (requires parameters to be set so the variables can all be evaluated).

path %>% get_ode_matrix() %>% knitr::kable()

x value dx/dt
B B 1 * dm + -1 * dm
B.carbon B.carbon 1 * dm/B * (fractionate(AA.carbon, eps = e1) - B.carbon) + -1 * dm/B * (fractionate(B.carbon, eps = e2) - B.carbon)
C C 1 * dm + -1 * (f3 * dm) + -1 * ((1 - f3) * dm)
C.carbon C.carbon 1 * dm/C * (fractionate(B.carbon, eps = e2) - C.carbon) + -1 * (f3 * dm)/C * (fractionate(C.carbon, eps = e3) - C.carbon) + -1 * ((1 - f3) * dm)/C * (fractionate(C.carbon, eps = e4) - C.carbon)
D D -1 * (f3 * dm) + 1 * (f3 * dm)
D.carbon D.carbon 1 * (f3 * dm)/D * (fractionate(C.carbon, eps = e3) - D.carbon) + -1 * (f3 * dm)/D * (fractionate(D.carbon, eps = 0) - D.carbon)
E E 1 * ((1 - f3) * dm) + -1 * dir_flux((1 - f3) * dm, rev = 1, dir = "+") + -1 * dir_flux((1 - f3) * dm, rev = 1, dir = "-")
E.carbon E.carbon 1 * ((1 - f3) * dm)/E * (fractionate(C.carbon, eps = e4) - E.carbon) + -1 * dir_flux((1 - f3) * dm, rev = 1, dir = "+")/E * (fractionate(E.carbon, eps = e5, m = TRUE) - E.carbon) + -1 * dir_flux((1 - f3) * dm, rev = 1, dir = "-")/E * (F.carbon - E.carbon)
F F -1 * ((1 - f3) * (1 - f6) * dm) + 1 * dir_flux((1 - f3) * dm, rev = 1, dir = "+") + 1 * dir_flux((1 - f3) * dm, rev = 1, dir = "-") + -1 * ((1 - f3) * f6 * dm)
F.carbon F.carbon 1 * dir_flux((1 - f3) * dm, rev = 1, dir = "+")/F * (fractionate(E.carbon, eps = e5, m = TRUE) - F.carbon) + 1 * dir_flux((1 - f3) * dm, rev = 1, dir = "-")/F * (F.carbon - F.carbon) + -1 * ((1 - f3) * f6 * dm)/F * (fractionate(F.carbon, eps = e6) - F.carbon) + -1 * ((1 - f3) * (1 - f6) * dm)/F * (fractionate(F.carbon, eps = e7) - F.carbon)
G G -1 * ((1 - f3) * f6 * dm) + 1 * ((1 - f3) * f6 * dm)
G.carbon G.carbon 1 * ((1 - f3) * f6 * dm)/G * (fractionate(F.carbon, eps = e6) - G.carbon) + -1 * ((1 - f3) * f6 * dm)/G * (fractionate(G.carbon, eps = 0) - G.carbon)
H H 1 * ((1 - f3) * (1 - f6) * dm) + -1 * ((1 - f3) * (1 - f6) * dm)
H.carbon H.carbon 1 * ((1 - f3) * (1 - f6) * dm)/H * (fractionate(F.carbon, eps = e7) - H.carbon) + -1 * ((1 - f3) * (1 - f6) * dm)/H * (fractionate(H.carbon, eps = e8) - H.carbon)
I I -1 * ((1 - f3) * (1 - f6) * dm) + 1 * ((1 - f3) * (1 - f6) * dm)
I.carbon I.carbon 1 * ((1 - f3) * (1 - f6) * dm)/I * (fractionate(H.carbon, eps = e8) - I.carbon) + -1 * ((1 - f3) * (1 - f6) * dm)/I * (fractionate(I.carbon, eps = 0) - I.carbon)

## Assign parameters

The symbols used in reaction network setup can be assigned numeric values (multiple scenarios if needed) that get evaluated upon running the model.

path <- path %>%
set_parameters(
data_frame(
scenario = c("low flux", "high flux"),
# fluxes and flux fractions
dm = c(0.1, 1), f3 = 0.2, f6 = 0.2,
# isotopic effects
e1 = 0, e2 = 25, e3 = 15, e4 = 35, e5 = 8, e6 = 20, e7 = 0, e8 = 14,
# starting isotopic composition
AA.carbon = 0, B.carbon = 0, C.carbon = 0, D.carbon = 0, E.carbon = 0,
F.carbon = 0, G.carbon = 0, H.carbon = 0, I.carbon = 0,
# pool sizes for variable components
B = 10, C = 1, D = 20, E = 10, F = 50, G = 20, H = 10, I = 1
)
)


## Run model

Running the system of differential equations is easily done and uses the ode solvers of the deSolve package.

model <- path %>% run_model(time_steps = 500)


## Plot time course

model %>%
gather(reservoir, delta, ends_with("carbon")) %>%
ggplot() + aes(time, delta, color = reservoir) +
geom_line() + theme_bw() +
labs(y = expression(delta*13*'C')) +
facet_grid(~scenario)


## Run model with event

Additional parameters can be passed and will be forwarded to the ode solver, e.g. introducing different starting isotopic composition part way through via a timed event.

model2 <- path %>% run_model(
time_steps = 500, make_state_var = c("AA.carbon"),
events = list(data = data.frame(
var = "AA.carbon", time = 250, value = 10, method = "rep")))
last_plot() %+%
gather(model2, reservoir, delta, ends_with("carbon"))


The model can also be run to steady-state using runsteady functionality from the rootSolve package. All parameters are forwarded to the ode/root solver.

steady <- path %>% run_steady_state(stol = 1e-5, rtol = 1e-3)


Looking at the steady state results, there is no difference between low and high flux once steady-state is reached (the correct behavior). Since fractionation is calculated precisely when using add_standard_reaction() (without any $\alpha \approx 1$ approximations), the isotopic offsets are not exactly the $\epsilon$ values provided.

path %>% generate_reaction_diagram(
steady %>% gather(component, y, ends_with("carbon")) %>%
mutate(component = sub(".carbon", "", component, fixed = T)) %>%
select(scenario, component, y)
) + facet_grid(~scenario)


Changing the the branching flux at nodes however, does change the outcome as expected. As an example:

steady2 <- path %>%
set_parameters(scenario = c("low D/E branching ratio", "high D/E branching ratio"),
dm = c(1, 1), f3 = c(0.2, 0.9)) %>%
run_steady_state(stol = 1e-5, rtol = 1e-3)

path %>% generate_reaction_diagram(
steady2 %>% gather(component, y, ends_with("carbon")) %>%
mutate(component = sub(".carbon", "", component, fixed = T)) %>%
select(scenario, component, y)
) + facet_grid(~scenario)


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