qudiscretize {QUBIC} | R Documentation

## Create a qualitative discrete matrix for a given gene expression matrix

### Description

`qudiscretize` delivers a discrete matrix. It is useful if we just want to get a discretized matrix.

### Usage

    qudiscretize(x, r = 1L, q = 0.06)

### Arguments

`x` | the input data matrix, which could be the normalized gene expression matrix or its qualitative representation from Qdiscretization or other discretization ways. (for example: a qualitative representation of gene expression data) For `BCQU()`, the data matrix should be real For `BCQUD()`, the data matrix should be discretized as integer. Zeros in the matrix will be treated as non-relevant value.
`r` | Affect the granularity of the biclusters. The range of possible ranks. A user can start with a small value of `r` (the default value is `1` so the corresponding data matrix consists of values '`1`', '`-1`' and '`0`'), evaluate the results, and then use larger values (should not be larger than half of the number of the columns) to look for fine structures within the identified biclusters.
`q` | Affect the granularity of the biclusters. The percentage of the regulating conditions for each gene. The choice of `q`'s value depends on the specific application goals; that is if the goal is to find genes that are responsive to local regulators, we should use a relatively small q-value; otherwise we may want to consider larger q-values. The default value of `q` is `0.06` in QUBIC (this value is selected based on the optimal biclustering results on simulated data).

### Details

`qudiscretize` convert a given gene expression matrix to a discrete matrix. It's implimented in C++, providing a increase in speed over the C equivalent.

### Value

A qualitative discrete matrix

### See Also

`QUBIC` `discretize`

### Examples

    # Qualitative discretize yeast microarray data
    data(BicatYeast)
    qudiscretize(BicatYeast[1:7, 1:5])

[Package QUBIC version 1.14.0 Index]