nmf.LassoCV {SparseSignatures} | R Documentation

## nmf.LassoCV

### Description

Perform the discovery by cross validation of K (unknown) somatic mutational signatures given a set of observations x. The estimation can slow down because of memory usage, when I high number of cross validation repetitions is asked and when the grid search is performed for a lot of configurations. In this case, we advice to split the computation into multiple smaller sets.

### Usage

    nmf.LassoCV(x, K = 3:10, starting_beta = NULL,
      background_signature = NULL, nmf_runs = 10, lambda_values = c(0.1,
      0.2, 0.3), cross_validation_entries = 0.05,
      cross_validation_iterations = 5, cross_validation_repetitions = 10,
      iterations = 20, max_iterations_lasso = 10000, num_processes = Inf,
      seed = NULL, verbose = TRUE)

### Arguments

`x` | count matrix.
`K` | a range of numeric value (each of them greater than 1) indicating the number of signatures to be discovered.
`starting_beta` | a list of starting beta value for each configuration of K. If it is NULL, starting betas are estimated by NMF.
`background_signature` | background signature to be used. If not provided, a warning is thrown.
`nmf_runs` | number of iteration of NMF to be performed for a robust estimation of starting beta. If beta is not NULL, this parameter is ignored.
`lambda_values` | range of values of LASSO to be used between 0 and 1. This value should be greater than 0. 1 is the value of LASSO that would shrink all the signatures to 0 within one step. The higher lambda_rate is, the sparser are the resulting signatures, but too large values result in a poor fit of the counts.
`cross_validation_entries` | Percentage of cells in the count matrix to be replaced by 0s.
`cross_validation_iterations` | For each configuration, the first time the signatures are discovered form a matrix with a ercentage of values replaced by 0s. This may result in a poor. This parameter is the number of restarts to be performed to improve this estimate.
`cross_validation_repetitions` | Number of time cross-validation should be repeated. Higher values result in better estimate, but are computationally expensive.
`iterations` | Number of iterations to be performed. Each iteration correspond to a first step where the counts are fitted and a second step where sparsity is enhanced.
`max_iterations_lasso` | Number of maximum iterations to be performed during the sparsification.
`num_processes` | Number of processes to be used during parallel execution. If executing in single process mode, this is ignored.
`seed` | Seed for reproducibility.
`verbose` | boolean; Shall I print all messages?

### Value

A list corresponding with 3 elements: grid_search, starting_beta and mean_squared_error. Here, grid_search provides all the results of the executions within the grid search; starting_beta is the set of initial values of beta used for each configuration and mean_squared_error is the mean squared error between the observed counts and the predicted ones for each configuration.

[Package SparseSignatures version 1.6.0 Index]