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#install.packages("R.matlab")
library(R.matlab)## R.matlab v3.6.2 (2018-09-26) successfully loaded. See ?R.matlab for help.##
## Attaching package: 'R.matlab'## The following objects are masked from 'package:base':
##
## getOption, isOpene_coli_core <- readMat(url("http://bigg.ucsd.edu/static/models/e_coli_core.mat"))
e_coli_core## $e.coli.core
## , , 1
##
## [,1]
## mets List,72
## metNames List,72
## metFormulas List,72
## metCharge Numeric,72
## genes List,137
## rxnGeneMat ?
## grRules List,95
## rxns List,95
## rxnNames List,95
## subSystems List,95
## S Numeric,6840
## lb Numeric,95
## ub Numeric,95
## b Numeric,72
## c Numeric,95
## rev Integer,95
## description "e_coli_core"
##
##
## attr(,"header")
## attr(,"header")$description
## [1] "MATLAB 5.0 MAT-file Platform: posix, Created on: Fri Nov 1 08:18:51 2019"
##
## attr(,"header")$version
## [1] "5"
##
## attr(,"header")$endian
## [1] "little"The e_coli_core contains many element; since I am not farmiliar with this type of data, I am not sure which one to transfer to a matrix. Something seems workable is:
ecolicore_mat<-unlist(e_coli_core[1])$e.coli.core426
dim(ecolicore_mat)## [1] 95 137head(ecolicore_mat)## 6 x 137 sparse Matrix of class "dgCMatrix"
##
## [1,] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
## [2,] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
## [3,] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
## [4,] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
## [5,] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
## [6,] 1 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
##
## [1,] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
## [2,] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
## [3,] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
## [4,] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
## [5,] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
## [6,] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
##
## [1,] . . . . . . . . . . . . . . . . . . . . . . . . . 1 1 . . . . . . . . . .
## [2,] . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1 1 1 1 1 . . . .
## [3,] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 . . .
## [4,] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 . .
## [5,] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 .
## [6,] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
##
## [1,] . . . . . . . . . . . . . . . . . . . . . . . . . .
## [2,] . . . . . . . . . . . . . . . . . . . . . . . . . .
## [3,] . . . . . . . . . . . . . . . . . . . . . . . . . .
## [4,] . . . . . . . . . . . . . . . . . . . . . . . . . .
## [5,] . . . . . . . . . . . . . . . . . . . . . . . . . .
## [6,] . . . . . . . . . . . . . . . . . . . . . . . . . .which is 6 x 137 sparse Matrix of class “dgCMatrix”, Yet the matrix has 95 rows in fact. If we change “NA” into “0” we will have
head(as.matrix(ecolicore_mat))## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14]
## [1,] 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [2,] 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [3,] 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [4,] 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [5,] 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [6,] 1 1 0 0 0 0 0 0 0 0 0 0 0 0
## [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25] [,26]
## [1,] 0 0 0 0 0 0 0 0 0 0 0 0
## [2,] 0 0 0 0 0 0 0 0 0 0 0 0
## [3,] 0 0 0 0 0 0 0 0 0 0 0 0
## [4,] 0 0 0 0 0 0 0 0 0 0 0 0
## [5,] 0 0 0 0 0 0 0 0 0 0 0 0
## [6,] 0 0 0 0 0 0 0 0 0 0 0 0
## [,27] [,28] [,29] [,30] [,31] [,32] [,33] [,34] [,35] [,36] [,37] [,38]
## [1,] 0 0 0 0 0 0 0 0 0 0 0 0
## [2,] 0 0 0 0 0 0 0 0 0 0 0 0
## [3,] 0 0 0 0 0 0 0 0 0 0 0 0
## [4,] 0 0 0 0 0 0 0 0 0 0 0 0
## [5,] 0 0 0 0 0 0 0 0 0 0 0 0
## [6,] 0 0 0 0 0 0 0 0 0 0 0 0
## [,39] [,40] [,41] [,42] [,43] [,44] [,45] [,46] [,47] [,48] [,49] [,50]
## [1,] 0 0 0 0 0 0 0 0 0 0 0 0
## [2,] 0 0 0 0 0 0 0 0 0 0 0 0
## [3,] 0 0 0 0 0 0 0 0 0 0 0 0
## [4,] 0 0 0 0 0 0 0 0 0 0 0 0
## [5,] 0 0 0 0 0 0 0 0 0 0 0 0
## [6,] 0 0 0 0 0 0 0 0 0 0 0 0
## [,51] [,52] [,53] [,54] [,55] [,56] [,57] [,58] [,59] [,60] [,61] [,62]
## [1,] 0 0 0 0 0 0 0 0 0 0 0 0
## [2,] 0 0 0 0 0 0 0 0 0 0 0 0
## [3,] 0 0 0 0 0 0 0 0 0 0 0 0
## [4,] 0 0 0 0 0 0 0 0 0 0 0 0
## [5,] 0 0 0 0 0 0 0 0 0 0 0 0
## [6,] 0 0 0 0 0 0 0 0 0 0 0 0
## [,63] [,64] [,65] [,66] [,67] [,68] [,69] [,70] [,71] [,72] [,73] [,74]
## [1,] 0 0 0 0 0 0 0 0 0 0 0 0
## [2,] 0 0 0 0 0 0 0 0 0 0 0 0
## [3,] 0 0 0 0 0 0 0 0 0 0 0 0
## [4,] 0 0 0 0 0 0 0 0 0 0 0 0
## [5,] 0 0 0 0 0 0 0 0 0 0 0 0
## [6,] 0 0 0 0 0 0 0 0 0 0 0 0
## [,75] [,76] [,77] [,78] [,79] [,80] [,81] [,82] [,83] [,84] [,85] [,86]
## [1,] 0 0 0 0 0 0 0 0 0 0 0 0
## [2,] 0 0 0 0 0 0 0 0 0 0 0 0
## [3,] 0 0 0 0 0 0 0 0 0 0 0 0
## [4,] 0 0 0 0 0 0 0 0 0 0 0 0
## [5,] 0 0 0 0 0 0 0 0 0 0 0 0
## [6,] 0 0 0 0 0 0 0 0 0 0 0 0
## [,87] [,88] [,89] [,90] [,91] [,92] [,93] [,94] [,95] [,96] [,97] [,98]
## [1,] 0 0 0 0 0 0 0 0 0 0 0 0
## [2,] 0 0 0 0 0 0 0 0 0 0 0 0
## [3,] 0 0 0 0 0 0 0 0 0 0 0 0
## [4,] 0 0 0 0 0 0 0 0 0 0 0 0
## [5,] 0 0 0 0 0 0 0 0 0 0 0 0
## [6,] 0 0 0 0 0 0 0 0 0 0 0 0
## [,99] [,100] [,101] [,102] [,103] [,104] [,105] [,106] [,107] [,108]
## [1,] 0 1 1 0 0 0 0 0 0 0
## [2,] 0 0 0 1 1 1 1 1 1 0
## [3,] 0 0 0 0 0 0 0 0 0 1
## [4,] 0 0 0 0 0 0 0 0 0 0
## [5,] 0 0 0 0 0 0 0 0 0 0
## [6,] 0 0 0 0 0 0 0 0 0 0
## [,109] [,110] [,111] [,112] [,113] [,114] [,115] [,116] [,117] [,118]
## [1,] 0 0 0 0 0 0 0 0 0 0
## [2,] 0 0 0 0 0 0 0 0 0 0
## [3,] 0 0 0 0 0 0 0 0 0 0
## [4,] 1 0 0 0 0 0 0 0 0 0
## [5,] 0 1 0 0 0 0 0 0 0 0
## [6,] 0 0 0 0 0 0 0 0 0 0
## [,119] [,120] [,121] [,122] [,123] [,124] [,125] [,126] [,127] [,128]
## [1,] 0 0 0 0 0 0 0 0 0 0
## [2,] 0 0 0 0 0 0 0 0 0 0
## [3,] 0 0 0 0 0 0 0 0 0 0
## [4,] 0 0 0 0 0 0 0 0 0 0
## [5,] 0 0 0 0 0 0 0 0 0 0
## [6,] 0 0 0 0 0 0 0 0 0 0
## [,129] [,130] [,131] [,132] [,133] [,134] [,135] [,136] [,137]
## [1,] 0 0 0 0 0 0 0 0 0
## [2,] 0 0 0 0 0 0 0 0 0
## [3,] 0 0 0 0 0 0 0 0 0
## [4,] 0 0 0 0 0 0 0 0 0
## [5,] 0 0 0 0 0 0 0 0 0
## [6,] 0 0 0 0 0 0 0 0 0