Description Details Author(s) References
This package includes the functions for estimating the gene-gene interaction network (a matrix, named A, with genes as rows and columns) and the associated transcriptional targets of the perturbations (a matrix, named P, with genes as rows and perturbations as columns). These estimations are computed with the NTW algorithm, a gene network inference algorithm based on ODE (ordinary differential equation) method, see reference. In this package, the whole A matrix and P matrix are estimated row by row with the function AP.estimation.Srow, and built together with the function NTW. AP.estimation.Srow can be used independently so that estimation of each row can be performed in parallel, improving computation time. For solving the steady state ODE equations, 3 regression methods are supplied: geo, sse and ml, see details in the the corresponding function help pages. In addition, in order to accelerate the estimation of matrix A, an option is available to make use of some prior information such as gene association (output from other gene netwrok inference algorithms, or from literature) in NTW. The regression methods used in forward or backward mode makes 6 possibilities available for estimating a single row of A matrix. The main functions in this package are listed below,
NTW, to estimate the whole matrix A and P (if P is unknown).
AP.estimation.Srow, to estimate one single row in A and P .
A.estimation.Srow, to estimate one single row in A with P known.
backward and forward, to estimate one single row of matrix A with different patterns of using prior gene association information.
method.geo, method.sse and method.ml, to estimate one single row of matrix A with different regression methods.
comb.matrix, sub-function to create all the combinations for regressor locations.
P.preestimation, pre-estimate P matrix according to the gene expression data.
Package: | NTW |
Type: | Package |
Version: | 0.99.0 |
Date: | 2010-5-11 |
License: | GPL-2 |
LazyLoad: | yes |
Wei Xiao, Yin Jin, Darong Lai, Xinyi Yang, Yuanhua Liu, Christine Nardini
Maintainer: Yuanhua Liu <[email protected]>
Applied method for the inference of gene networks: the bifidobacterium case. to be submitted
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