Description Usage Arguments Value Examples
View source: R/poisson_lognormal.R
poisson_lognormal
uses Hamiltonion Monte Carlo to sample form an extend
Poisson log-normal mixed model. Each cell and protein marker has its own rate
parameter following a linear model.
1 2 3 4 5 6 7 8 9 10 11 12 13 | poisson_lognormal(
df_samples_subset,
protein_names,
condition,
group,
r_donor,
eta = 1,
iter = 325,
warmup = 200,
num_chains = 1,
adapt_delta = 0.8,
seed = 1
)
|
df_samples_subset |
Data frame or tibble with proteins counts, cell condition, and group information |
protein_names |
A vector of column names of protein to use in the analysis |
condition |
The column name of the condition variable |
group |
The column name of the group variable |
r_donor |
Rank of the donor random effect covariance matrix |
eta |
Hyperparameter for LKJ prior |
iter |
Number of iteration per chain for the HMC sampler |
warmup |
Number of warm up steps per chain for the HMC sampler |
num_chains |
Number of HMC chains to run in parallel |
adapt_delta |
Parameter to control step size of numerical solver |
seed |
Set seed for HMC sampler (higher value means smaller step size, max is 1) |
A list of class cytoeffect_poisson
containing
fit_mcmc |
|
protein_names |
input protein names |
condition |
input condition variable |
group |
input group names |
df_samples_subset |
input df_samples_subset table |
1 2 3 4 5 6 7 8 9 10 |
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