sc3: Run all steps of 'SC3' in one go
In SC3: Single-Cell Consensus Clustering

This function is a wrapper that executes all steps of SC3 analysis in one go.

sc3.SingleCellExperiment(object, ks, gene_filter, pct_dropout_min,
  pct_dropout_max, d_region_min, d_region_max, svm_num_cells, svm_train_inds,
  svm_max, n_cores, kmeans_nstart, kmeans_iter_max, k_estimator, biology,
  rand_seed)

## S4 method for signature 'SingleCellExperiment'
sc3(object, ks = NULL, gene_filter = TRUE,
  pct_dropout_min = 10, pct_dropout_max = 90, d_region_min = 0.04,
  d_region_max = 0.07, svm_num_cells = NULL, svm_train_inds = NULL,
  svm_max = 5000, n_cores = NULL, kmeans_nstart = NULL,
  kmeans_iter_max = 1e+09, k_estimator = FALSE, biology = FALSE,
  rand_seed = 1)

`object`	an object of `SingleCellExperiment` class.
`ks`	a range of the number of clusters `k` used for `SC3` clustering. Can also be a single integer.
`gene_filter`	a boolen variable which defines whether to perform gene filtering before SC3 clustering.
`pct_dropout_min`	if `gene_filter = TRUE`, then genes with percent of dropouts smaller than `pct_dropout_min` are filtered out before clustering.
`pct_dropout_max`	if `gene_filter = TRUE`, then genes with percent of dropouts larger than `pct_dropout_max` are filtered out before clustering.
`d_region_min`	defines the minimum number of eigenvectors used for kmeans clustering as a fraction of the total number of cells. Default is `0.04`. See `SC3` paper for more details.
`d_region_max`	defines the maximum number of eigenvectors used for kmeans clustering as a fraction of the total number of cells. Default is `0.07`. See `SC3` paper for more details.
`svm_num_cells`	number of randomly selected training cells to be used for SVM prediction. The default is `NULL`.
`svm_train_inds`	a numeric vector defining indeces of training cells that should be used for SVM training. The default is `NULL`.
`svm_max`	define the maximum number of cells below which SVM is not run.
`n_cores`	defines the number of cores to be used on the user's machine. If not set, 'SC3' will use all but one cores of your machine.
`kmeans_nstart`	nstart parameter passed to `kmeans` function. Can be set manually. By default it is `1000` for up to `2000` cells and `50` for more than `2000` cells.
`kmeans_iter_max`	iter.max parameter passed to `kmeans` function.
`k_estimator`	boolean parameter, defines whether to estimate an optimal number of clusters `k`. If user has already defined the ks parameter the estimation does not affect the user's paramater.
`biology`	boolean parameter, defines whether to compute differentially expressed genes, marker genes and cell outliers.
`rand_seed`	sets the seed of the random number generator. `SC3` is a stochastic method, so setting the `rand_seed` to a fixed values can be used for reproducibility purposes.