SC2Spa.tl.Train_transfer

SC2Spa.tl.Train_transfer(adata, root, model_root, sparse=True, polar=True, CT='A', lrr_patience=20, ES_patience=50, min_lr=1e-05, epoch=500, batch_size=4096, NLFT=6, subLayer=False)

Finetune location prediction model (FCNN) on a specific cell type A model will be trained and saved to root + ‘SI_’ + CT + ‘.h5’ The predicted coordinates of single cells will be saved in adata_query.obsm[‘spatial_mapping’] The predicted coordinates of beads will be saved in adata_ref.obs[‘spatial_mapping’] Fine mapping information will be saved in adata_ref.obs[‘FM’] and adata_query.obs[‘FM’]. True if a cell/bead was mapped, otherwise False.

Parameters

adata

An anndata object that contains the gene expression matrix of the target type of cells. The gene expression matrix should be the shape of (cell, gene). Spatial information should be stored in adata_ref.obsm[‘spatial’] in np.array format

sparse

True if gene expression is saved in sparse format, otherwise False

model_root

The path of a trained model.

root

the root path to save the model

name

the name used to save the model

lrr_patience

The patience for learning rate reduction

min_lr

minimum learning rate

ES_patience

The patience for early stopping

sublayer

whether to finetune part of the neural network

NLFT

the number of layers that are finetuned. Layers are counted from the last layer to the first layer

Returns

model

The finetuned FCNN