generateGDM {phemd} | R Documentation

## Computes ground distance matrix based on cell embedding

### Description

Takes as input a Phemd object containing cell-state embedding object. Returns updated object with ground distance matrix representing pairwise distances between distinct cell subtypes based on cell state embedding.

### Usage

    generateGDM(
      obj,
      cell_model = c("monocle2", "seurat", "phate"),
      expn_type = "reduced",
      ndim = 8
    )

### Arguments

`obj` | 'Phemd' object containing cell-state embedding object
`cell_model` | Method by which cell state was modeled (either "monocle2", "seurat", or "phate")
`expn_type` | Data type to use to determine cell-type dissimilarities
`ndim` | Number of embedding dimensions to be used for computing cell-type dissimilarity (optional)

### Details

`embedCells` and `orderCellsMonocle` need to be called before calling this function. Requires 'igraph' package

### Value

Phemd object with ground distance matrix (to be used in EMD computation) in @data_cluster_weights slot

### Examples

    my_phemdObj <- createDataObj(all_expn_data, all_genes, as.character(snames_data))
    my_phemdObj_lg <- removeTinySamples(my_phemdObj, 10)
    my_phemdObj_lg <- aggregateSamples(my_phemdObj_lg, max_cells=1000)
    my_phemdObj_monocle <- embedCells(my_phemdObj_lg, data_model = 'gaussianff', sigma=0.02, maxIter=2)
    my_phemdObj_monocle <- orderCellsMonocle(my_phemdObj_monocle)
    my_phemdObj_final <- clusterIndividualSamples(my_phemdObj_monocle)
    my_phemdObj_final <- generateGDM(my_phemdObj_final)

[Package phemd version 1.10.0 Index]