Argument_list.R

In himelmallick/MimESys: Simulate Realistic Multi-Omics Datasets with Specified Structural and Sparsity Patterns

### Input for Functions
mainDir = '~/Users/siddheshkulkarni/Desktop'
subDir = 'plots_simulated_data'
seed.number = 1234
M = 3  # Number of views (NB: the inputs are currently set up only for this specific case!!!)
p_m = c(500, 700, 1000)  # Number of features per view
n = 100  # Train set size
nTest = 100  # Test set size
fixed_act_patter = TRUE  # Set a custom activity pattern in the joint component

#### Make changes in the code from here ##

J0_m = c(5, 6, 7)  # Number of groups in joint component
K0_m = c(5, 7, 10)  # Number of factors in view-specific components
S0_m = c(6, 7, 8)  # Number of groups in view-specific components

nu2_0 = 0.1  # Input the joint loadings variability
pi2_0 = 0.1  # Input the view-specific loadings variability

snr_m = rep(1, M)  # Input the view-specific signal-to-noise ratio (mean)
snr_y = 1  # Input signal-to-noise ratio

decaying_loadings = FALSE  # Enforce loadings decay (re-weighting importance of latent axis of variation)
decaying_type = 'sqrt'  # One of 'sqrt' and 'log'

pJ_zero = 0.6  # Probability of group-wise zero in joint component
pJ_sign = 0.4  # Probability of group-wise sign-switch in joint component
pJ_zeroEntr = 0.5  # Probability of entry-wise zero in joint component

pS_zero = 0.6  # Probability of group-wise zero in specific components
pS_sign = 0.4  # Probability of group-wise sign-switch in specific components
pS_zeroEntr = 0.5  # Probability of entry-wise zero in specific components

Activity_pattern_plot = TRUE  #Save the Activity Pattern Plot

Emprical_correlation_plot = TRUE #Save the Emprical correlation plot

Data_save=TRUE  ## save the data in directory