patterns.priorA: Approaches to use a priori known gene association information...

In NTW: Predict gene network using an Ordinary Differential Equation (ODE) based method

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.

Author(s)

Wei Xiao, Yin Jin, Darong Lai, Xinyi Yang,Yuanhua Liu, Christine Nardini

NTW documentation built on Nov. 8, 2020, 6:51 p.m.