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)

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