gemini_inference: gemini_inference

In sellerslab/gemini: GEMINI: Variational inference approach to infer genetic interactions from pairwise CRISPR screens

gemini_inference

Description

Estimate the posterior using a variational inference technique. Inference is performed through an iterative process until convergence.

Usage

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
)

Arguments

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

Details

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.

Value

a gemini.model object with estimated posteriors

Examples

data("Model", package = "gemini")
Model %<>% gemini_inference(verbose = FALSE, n_iterations = 1) # iterations set to 1 for testing

sellerslab/gemini documentation built on Dec. 5, 2022, 8:56 a.m.