capacity_logreg_algorithm function

Main algorithm to calculate channel capacity by SLEMI approach

Additional parameters: lr_maxit and maxNWts are the same as in definition of multinom function from nnet package. An alternative model formula (using formula_string arguments) should be provided if data are not suitable for description by logistic regression (recommended only for advanced users). It is recommended to conduct estimation by calling capacity_logreg_main.R.

capacity_logreg_algorithm(
  data,
  signal = "signal",
  response = "response",
  side_variables = NULL,
  formula_string = NULL,
  model_out = TRUE,
  cc_maxit = 100,
  lr_maxit = 1000,
  MaxNWts = 5000
)

Arguments

• data: must be a data.frame object. Cannot contain NA values.
• signal: is a character object with names of columns of dataRaw to be treated as channel's input.
• response: is a character vector with names of columns of dataRaw to be treated as channel's output
• side_variables: (optional) is a character vector that indicates side variables' columns of data, if NULL no side variables are included
• formula_string: (optional) is a character object that includes a formula syntax to use in logistic regression model. If NULL, a standard additive model of response variables is assumed. Only for advanced users.
• model_out: is the logical indicating if the calculated logistic regression model should be included in output list
• cc_maxit: is the number of iteration of iterative optimisation of the algorithm to estimate channel capacity. Default is 100.
• lr_maxit: is a maximum number of iteration of fitting algorithm of logistic regression. Default is 1000.
• MaxNWts: is a maximum acceptable number of weights in logistic regression algorithm. Default is 5000.

Returns

a list with three elements:

• output$cc - channel capacity in bits
• output$p_opt - optimal probability distribution
• output$regression - confusion matrix of logistic regression predictions
• output$model - nnet object describing logistic regression model (if model_out=TRUE)

References

[1] Jetka T, Nienaltowski K, Winarski T, Blonski S, Komorowski M, Information-theoretic analysis of multivariate single-cell signaling responses using SLEMI, PLoS Comput Biol, 15(7): e1007132, 2019, https://doi.org/10.1371/journal.pcbi.1007132.

Examples

tempdata=data_example1 
outputCLR1=capacity_logreg_algorithm(data=tempdata, signal="signal",
response="response",cc_maxit=3,model_out=FALSE,
formula_string = "signal~response")