NTW (version 1.22.0)

patterns.priorA: Approaches to use a priori known gene association information for a single row estimation in matrix A

Description

Given some information of the gene interaction network, for example the estimated gene association matrix pred.net by other algorithms or from literature, NTW can use this prior information to enhance acurracy. NTW offers two approaches to infer the gene network, i.e. forward and backward, on the base of pred.net. The former computes further edges than the ones in pred.net, while the latter prunes edges.

Usage

backward(r, X, pert, topD, restk, cFlag, TA, noiseLevel)
forward(r, X, pert, topD, restk, cFlag, TA, noiseLevel)

Arguments

r

A number to indicate the row of A to be estimated when row r of P is fixed.

X

Gene expression data, a matrix with genes as rows and perturbations as columns.

pert

Row r in P.

topD

A parameter in NTW algorithm for keeping the top topD combinations of non-zero regressors of row r in A, see vignette for details.

restk

The number of non-zero regressors for the estimation of row r in A.

cFlag

A flag to identify the regression methods, "geo" for geometric mean method, "sse" for sum of square method and "ml" for maximum likelihood method.

TA

A vector including the indexes of non-zero elements in row r of the network containing a priori information, pred.net.

noiseLevel

Only used in "ml" method, to indicate the noise level in each perturbed experiment.

Value

A.row

A vector of estimated row r in A.

CrtValue

The minimum value from the objective function.