qudiscretize: Create a qualitative discrete matrix for a given gene...

In QUBIC: An R package for qualitative biclustering in support of gene co-expression analyses

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])

QUBIC documentation built on Nov. 8, 2020, 8:17 p.m.