Genome scale network model
From CSBLwiki
(Difference between revisions)
| Line 16: | Line 16: | ||
library("BiGGR") # <- related packages automatically ON (graph, igraph,...) | library("BiGGR") # <- related packages automatically ON (graph, igraph,...) | ||
load("shewanella.rdata") | load("shewanella.rdata") | ||
| + | #sm # stoichiometric matrix | ||
| + | metabo = rownames(sm) # metabolites | ||
| + | fluxname = colnames(sm) # reactions | ||
| + | dim(sm) | ||
| + | am = matrix(0,729,729) # null adj. matrix | ||
| + | dimnames(am) = list(metabo,metabo); am[1:5,1:5] | ||
| + | ## converting sm to am | ||
| + | for(i in 1:ncol(sm)) { | ||
| + | # i = 1 | ||
| + | ind = names(sm[which(sm[,i]!=0),i]) | ||
| + | am[ind,ind] = 1 | ||
| + | # print(i) | ||
| + | } | ||
| + | diag(am) = 0 # set digonal '0' | ||
| + | ## Too many edges such as ATP, H2O, PPi.... | ||
| + | cofact = sort(rowSums(am),decreasing=T)[1:100] | ||
| + | cofact # top 100; mostly cofactors, tRNA... | ||
| + | cof.ind = which(metabo %in% names(cof)) | ||
| + | am.m = am[-cof.ind,-cof.ind] | ||
| + | dim(am.m) # 629 629 | ||
| + | |||
| + | ## adjacency matrix to graph obj. | ||
| + | gl = new("graphAM",adjMat=am.m) | ||
| + | |||
</pre> | </pre> | ||
Revision as of 16:21, 21 July 2011
- Graph Visualization
- Bioconductor Install
- Rgraphviz
- rsbml
- BiGGR
source("http://bioconductor.org/biocLite.R")
## requirement: libsbml, graphviz library
biocLite("rsbml","Rgraphviz","BiGGR",type="source") # compiling from source code
###
### visualization of stoichiometric matrix
###
library("BiGGR") # <- related packages automatically ON (graph, igraph,...)
load("shewanella.rdata")
#sm # stoichiometric matrix
metabo = rownames(sm) # metabolites
fluxname = colnames(sm) # reactions
dim(sm)
am = matrix(0,729,729) # null adj. matrix
dimnames(am) = list(metabo,metabo); am[1:5,1:5]
## converting sm to am
for(i in 1:ncol(sm)) {
# i = 1
ind = names(sm[which(sm[,i]!=0),i])
am[ind,ind] = 1
# print(i)
}
diag(am) = 0 # set digonal '0'
## Too many edges such as ATP, H2O, PPi....
cofact = sort(rowSums(am),decreasing=T)[1:100]
cofact # top 100; mostly cofactors, tRNA...
cof.ind = which(metabo %in% names(cof))
am.m = am[-cof.ind,-cof.ind]
dim(am.m) # 629 629
## adjacency matrix to graph obj.
gl = new("graphAM",adjMat=am.m)
