Description Usage Arguments Details Value Examples
View source: R/gemini_inference.R
Estimate the posterior using a variational inference technique. Inference is performed through an iterative process until convergence.
1 2 3 4 | gemini_inference(Model, n_iterations = 20, mean_x = 1, sd_x = 1,
mean_xx = 1, sd_xx = 1, mean_y = 0, sd_y = 10, mean_s = 0,
sd_s = 10, threshold = 0.001, cores = 1, force_results = FALSE,
verbose = FALSE, save_iterations = FALSE)
|
Model |
an object of class gemini.model |
n_iterations |
a numeric indicating the maximum number of iterations (default=20). |
mean_x |
a numeric indicating prior mean of x (default=1). |
sd_x |
a numeric indicating prior sd of x (default=1). |
mean_xx |
a numeric indicating prior mean of xx (default=1). |
sd_xx |
a numeric indicating prior sd of xx (default=1) |
mean_y |
a numeric indicating prior mean of y (default=0) |
sd_y |
a numeric indicating prior sd of y (default=10). |
mean_s |
a numeric indicating prior mean of s(default=0) |
sd_s |
a numeric indicating prior sd of s (default=10) |
threshold |
a numeric indicating the threshold of change in MAE at which to stop the iterative process (default=0.001). |
cores |
a numeric indicating the number of cores to use. See details in gemini_parallel. (default=1) |
force_results |
a logical indicating if the CAVI algorithm should be halted if non-convergence is detected. (default=FALSE) |
verbose |
default FALSE |
save_iterations |
for especially large libraries that require long computations, saves the latest iteration of each update. default FALSE |
GEMINI uses the following parameters, which are described in Zamanighomi et al. and translated here for clarity:
y: individual gene effect
s: combination effect
x: screen variation corresponding to individual guides
xx: screen variation corresponding to paired guides
Default parameters may need to be changed if convergence is not achieved. See README for more details.
a gemini.model object with estimated posteriors
1 2 | data("Model", package = "gemini")
Model %<>% gemini_inference(verbose = FALSE, n_iterations = 1) # iterations set to 1 for testing
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