netresponse-package: NetResponse: Global modeling of transcriptional responses in...

Description Author(s) References Examples

Description

Global modeling of transcriptional responses in interaction networks.

Package: netresponse
Type: Package
Version: See sessionInfo() or DESCRIPTION file
Date: 2011-02-03
License: GNU GPL >=2
LazyLoad: yes

Author(s)

Leo Lahti, Olli-Pekka Huovilainen, Antonio Gusmao and Juuso Parkkinen. Maintainer: Leo Lahti [email protected]

References

Leo Lahti et al.: Global modeling of transcriptional responses in interaction networks. Bioinformatics (2010). See citation("netresponse") for details.

Examples

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# Define parameters for toy data
Ns <- 200  # number of samples (conditions)
Nf <- 10   # number of features (nodes)
feature.names <- paste("feat", seq(Nf), sep="")
sample.names  <- paste("sample", seq(Ns), sep="") 
# random seed
set.seed( 123 )
# Random network
netw <- pmax(array(sign(rnorm(Nf^2)), dim = c(Nf, Nf)), 0)
# in pathway analysis nodes correspond to genes
rownames(netw) <- colnames(netw) <- feature.names
# Random responses of the nodes across conditions 
D <- array(rnorm(Ns*Nf), dim = c(Ns,Nf), dimnames = list(sample.names, feature.names))
D[1:100, 4:6]  <- t(sapply(1:(Ns/2),function(x){rnorm(3, mean = 1:3)}))
D[101:Ns, 4:6] <- t(sapply(1:(Ns/2),function(x){rnorm(3, mean = 7:9)}))
# Calculate the model
model <- detect.responses(D, netw)
# Subnets (each is a list of nodes)
get.subnets( model )

# Retrieve model for one subnetwork
# means, standard devations and weights for the components
inds <- which(sapply(model@last.grouping, length) > 2)
subnet.id <- names(model@subnets)[[1]]
m <- get.model.parameters(model, subnet.id) 
print(m)

Example output

Loading required package: Rgraphviz
Loading required package: graph
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, sd, var, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colMeans, colSums, colnames, do.call,
    duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
    lapply, lengths, mapply, match, mget, order, paste, pmax, pmax.int,
    pmin, pmin.int, rank, rbind, rowMeans, rowSums, rownames, sapply,
    setdiff, sort, table, tapply, union, unique, unsplit, which,
    which.max, which.min

Loading required package: grid
Loading required package: minet
Loading required package: mclust
Package 'mclust' version 5.3
Type 'citation("mclust")' for citing this R package in publications.
Loading required package: reshape2

netresponse (C) 2008-2016 Leo Lahti et al.

https://github.com/antagomir/netresponse
convert the network into edge matrix
removing self-links
matching the features between network and datamatrix
Filter the network to only keep the edges with highest mutual information
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Compute cost for each variable
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independent models done
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Combining groups,  10  group(s) left...

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Combining groups,  3  group(s) left...

Warning message:
In check.network(network, datamatrix, verbose = verbose) :
  Network is not symmetric. Removing link directions to force symmetric network.
$`Subnet-2`
[1] "feat4" "feat5" "feat6"

$mu
            [,1]       [,2]        [,3]       [,4]      [,5]       [,6]
[1,] 0.006459156 0.03481401 -0.09597205 0.01638899 0.0622605 0.04811945
            [,7]
[1,] -0.02276986

$sd
          [,1]     [,2]      [,3]      [,4]      [,5]     [,6]     [,7]
[1,] 0.9582671 1.009199 0.9786874 0.9955374 0.9911944 1.026288 0.989218

$w
[1] 1

$free.energy
         [,1]
[1,] 2045.463

$Nparams
[1] 15

$qofz
       [,1]
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$nodes
[1] "feat1"  "feat2"  "feat3"  "feat7"  "feat8"  "feat9"  "feat10"

netresponse documentation built on Nov. 1, 2018, 2:59 a.m.