Select_Model_short_TSCAN {FEAST} | R Documentation

## Using clustering results (from TSCAN) based on feature selection to perform model selection.

### Description

Using clustering results (from TSCAN) based on feature selection to perform model selection.

### Usage

    Select_Model_short_TSCAN(
      Y,
      cluster,
      minexpr_percent = 0.5,
      cvcutoff = 1,
      tops = c(500, 1000, 2000)
    )

### Arguments

`Y` | A gene expression matrix
`cluster` | The initial cluster labels NA values are allowed. This can directly from the `Consensus` function.
`minexpr_percent` | The threshold used for processing data in TSCAN. Using it by default.
`cvcutoff` | The threshold used for processing data in TSCAN. Using it by default.
`tops` | A numeric vector containing a list of numbers corresponding to top genes; e.g., tops = c(500, 1000, 2000).

### Value

mse and the TSCAN clustering result.

### Examples

    data(Yan)
    k = length(unique(trueclass))
    Y = process_Y(Y, thre = 2) # preprocess the data
    set.seed(123)
    rixs = sample(nrow(Y), 500)
    cixs = sample(ncol(Y), 40)
    Y = Y[rixs, cixs]
    con_res = Consensus(Y, k=k)
    # not run
    # mod_res = Select_Model_short_TSCAN(Y, cluster = con_res$cluster, top = c(100, 200))

[Package FEAST version 1.0.0 Index]