autoencode | R Documentation |
R interface for the autoencode python function
autoencode(x, python.module, main, test.x = NULL, pretrain_file = "", nonmissing_indicator = 1, n_human = 21183L, n_mouse = 21122L, shared_size = 15494L, model.species = NULL, out_dir = ".", batch_size = 32L, write_output_to_tsv = F, ...)
x |
Target sparse data matrix of gene by cell. When pretraining is used, the genes should be the same as the nodes used in the pretrained model. If a node gene is missing is the target dataset, set all values of that gene as 0 in |
python.module |
The python module for the Python package |
main |
A Python main module |
test.x |
Data matrix to evaluate the test error |
pretrain_file |
The pretrained weights file ended with '.hdf5' |
nonmissing_indicator |
A single value 1 or a vector of 0 and 1s to indicate which nodes are missing in the target dataset. Set to 1 for no pretraining. |
model.species |
Should be either 'Human' or 'Mouse' when pretraining is used |
write_output_to_tsv |
If True, then the result of Python is written as .tsv files instead of passing back to R. Default is False. |
... |
Extra parameters passed to Python module |
A data matrix for the Python autoencoder result
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.