Nothing
## ---- include = FALSE---------------------------------------------------------
library(biodosetools)
knitr::opts_chunk$set(
fig.dpi = 96,
collapse = TRUE,
comment = "#>"
)
## ----sc-trans-estimate-01, echo=FALSE, out.width='100%', fig.align='center', fig.cap="'Curve fitting data options' box and 'Results' tabbed box in the dose estimation module when loading curve from an `.rds` file."----
knitr::include_graphics("figures/screenshot-translocations-estimate-01.png")
## ----sc-trans-estimate-01b, echo=FALSE, out.width='100%', fig.cap="'Curve fitting data options' box and 'Results' tabbed box in the dose estimation module when inputting curve coefficients manually. Note that if no variance-covariance matrix is provided, only the variances calculated from the coefficients' standard errors will be used in calculations."----
knitr::include_graphics("figures/screenshot-translocations-estimate-01b.png")
## ----load-fitting-results, tidy=TRUE, tidy.opts=list(width.cutoff=60)---------
fit_results <- system.file("extdata", "translocations-fitting-results.rds", package = "biodosetools") %>%
readRDS()
## ----fit-results--------------------------------------------------------------
fit_results$fit_coeffs
## ----sc-trans-estimate-02, echo=FALSE, out.width='100%', fig.align='center', fig.cap="'Stains color options', 'Chromosome data' and 'Genomic conversion factor' boxes in the dose estimation module."----
knitr::include_graphics("figures/screenshot-translocations-estimate-02.png")
## ----trans-genome-factor-est--------------------------------------------------
genome_factor <- calculate_genome_factor(
dna_table = dna_content_fractions_morton,
chromosome = c(1, 2, 3, 4, 5, 6),
color = c("Red", "Red", "Green", "Red", "Green", "Green"),
sex = "male"
)
## -----------------------------------------------------------------------------
genome_factor
## ----sc-trans-estimate-03, echo=FALSE, out.width='100%', fig.align='center', fig.cap="'Data input options' and 'Data input' boxes in the dose estimation module."----
knitr::include_graphics("figures/screenshot-translocations-estimate-03.png")
## ----trans-case-data----------------------------------------------------------
case_data <- data.frame(
C0 = 288, C1 = 52, C2 = 9, C3 = 1
) %>%
calculate_aberr_table(
type = "case",
assessment_u = 1,
aberr_module = "translocations"
) %>%
dplyr::mutate(
Xc = calculate_trans_rate_sigurdson(
cells = N,
genome_factor = genome_factor,
age_value = 30,
smoker_bool = TRUE
),
Fg = (X - Xc) / (N * genome_factor),
Fg_err = Fp_err / sqrt(genome_factor)
)
## -----------------------------------------------------------------------------
case_data
## ----sc-trans-estimate-04, echo=FALSE, out.width='60%', fig.align='center', fig.cap="'Dose estimation options' box in the dose estimation module."----
knitr::include_graphics("figures/screenshot-translocations-estimate-04.png")
## ----sc-trans-estimate-05, echo=FALSE, out.width='100%', fig.align='center', fig.cap="'Results' tabbed box, 'Curve plot' and 'Save results' boxes in the dose estimation module."----
knitr::include_graphics("figures/screenshot-translocations-estimate-05.png")
## ----trans-parse-fit-results--------------------------------------------------
fit_coeffs <- fit_results[["fit_coeffs"]]
fit_var_cov_mat <- fit_results[["fit_var_cov_mat"]]
## ----trans-protracted-g-value-------------------------------------------------
protracted_g_value <- protracted_g_function(
time = 0.5,
time_0 = 2
)
## -----------------------------------------------------------------------------
protracted_g_value
## ----trans-dose-estimation-whole-delta----------------------------------------
results_whole_delta <- estimate_whole_body_delta(
case_data,
fit_coeffs,
fit_var_cov_mat,
conf_int = 0.95,
protracted_g_value,
aberr_module = "translocations"
)
## ----trans-estimated-dose-curve, fig.width=6, fig.height=3.5, fig.align='center', fig.cap="Plot of estimated doses generated by \\{biodosetools\\}. The grey shading indicates the uncertainties associated with the calibration curve."----
plot_estimated_dose_curve(
est_doses = list(whole = results_whole_delta),
fit_coeffs,
fit_var_cov_mat,
protracted_g_value,
conf_int_curve = 0.95,
aberr_name = "Translocations"
)
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