This function replicates counts from a real-world dataset.
sccomp_replicate(
fit,
formula_composition = NULL,
formula_variability = NULL,
number_of_draws = 1,
mcmc_seed = sample(1e+05, 1)
)The result of sccomp_estimate.
A formula. The formula describing the model for differential abundance, for example ~treatment. This formula can be a sub-formula of your estimated model; in this case all other factor will be factored out.
A formula. The formula describing the model for differential variability, for example ~treatment. In most cases, if differentially variability is of interest, the formula should only include the factor of interest as a large anount of data is needed to define variability depending to each factors. This formula can be a sub-formula of your estimated model; in this case all other factor will be factored out.
An integer. How may copies of the data you want to draw from the model joint posterior distribution.
An integer. Used for Markov-chain Monte Carlo reproducibility. By default a random number is sampled from 1 to 999999. This itself can be controlled by set.seed()
A tibble tbl with cell_group-wise statistics
A tibble (tbl), with the following columns:
cell_group - A character column representing the cell group being tested.
sample - A factor column representing the sample name from which data was generated.
generated_proportions - A numeric column representing the proportions generated from the model.
generated_counts - An integer column representing the counts generated from the model.
replicate - An integer column representing the replicate number, where each row corresponds to a different replicate of the data.
message("Use the following example after having installed install.packages(\"cmdstanr\", repos = c(\"https://stan-dev.r-universe.dev/\", getOption(\"repos\")))")
#> Use the following example after having installed install.packages("cmdstanr", repos = c("https://stan-dev.r-universe.dev/", getOption("repos")))
# \donttest{
if (instantiate::stan_cmdstan_exists() && .Platform$OS.type == "unix") {
data("counts_obj")
sccomp_estimate(
counts_obj,
~ type, ~1, sample, cell_group, count,
cores = 1
) |>
sccomp_replicate()
}
# }