FindClassBasedOnMC {IRISFGM} | R Documentation

## FindClassBasedOnMC

### Description

This function is for performing Markov chain clustering regarding generated co-expression gene modules. This clustering method is working for relative small dataset. If you have a large dataset, We recommend you should use Seurat clustering wrapped in this IRISFGM package. See details `RunLTMG`, `RunDimensionReduction`, and `RunClassification`.

### Usage

    FindClassBasedOnMC(object, ...)

    .final(object = NULL, method = "MCL", K = 5)

    ## S4 method for signature 'IRISFGM'
    FindClassBasedOnMC(object = NULL, method = "MCL", K = 5)

### Arguments

`object` | input IRIS-FGM object
`...` | other arguments passed to methods
`method` | using MCL(Markov Cluster) algorithm to predict clusters. There is alternative option which is 'SC.' ( Unnormalized spectral clustering function. Uses Partitioning Around Medoids clustering instead of K-means.)
`K` | expected number of predicted clusters when you are using 'SC' method for cell clustering and this parameter does not work for 'MCL'

### Value

It will reture cell clustering results based on MCL method.

### Examples

    data(example_object)
    example_object<- RunLTMG(example_object,Gene_use = "200")
    example_object <- CalBinaryMultiSignal(example_object)
    # Due to generate intermedie files, please make sure to set working directory

    example_object <- RunBicluster(example_object,
                                  DiscretizationModel = 'LTMG',
                                  OpenDual = FALSE,
                                  NumBlockOutput = 1000,
                                  BlockOverlap = 0.7,
                                  BlockCellMin = 15)
    example_object <- FindClassBasedOnMC(example_object)

[Package IRISFGM version 1.2.0 Index]