trainModel {MetaNeighbor} | R Documentation

## Pretrains model for the unsupervised version of MetaNeighbor

### Description

When comparing clusters to a large reference dataset, this function summarizes the gene-by-cell matrix into a much smaller highly variable gene-by-cluster matrix which can be fed as training data into MetaNeighborUS, resulting in substantial time and memory savings.

### Usage

    trainModel(var_genes, dat, i = 1, study_id, cell_type)

### Arguments

`var_genes` | vector of high variance genes.
`dat` | SummarizedExperiment object containing gene-by-sample expression matrix.
`i` | default value 1; non-zero index value of assay containing the matrix data
`study_id` | a vector that lists the Study (dataset) ID for each sample
`cell_type` | a vector that lists the cell type of each sample

### Value

The output is a gene-by-cluster matrix that contains all the information necessary to run MetaNeighborUS from a pre-trained model.

### Examples

    data(mn_data)
    var_genes = variableGenes(dat = mn_data, exp_labels = mn_data$study_id)
    trained_model = trainModel(var_genes = var_genes,
                               dat = mn_data,
                               study_id = mn_data$study_id,
                               cell_type = mn_data$cell_type)
    celltype_NV = MetaNeighborUS(trained_model = trained_model,
                                 dat = mn_data,
                                 study_id = mn_data$study_id,
                                 cell_type = mn_data$cell_type)
    celltype_NV

[Package MetaNeighbor version 1.14.0 Index]