19.2 Biclustering

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20200902

library(biclust)
tds <- matrix(rbinom(400, 50, 0.4), 20, 20)
res <- biclust(tds, method=BCCC(), delta=1.5, alpha=1, number=10)
res
## 
## An object of class Biclust 
## 
## call:
##  biclust(x=tds, method=BCCC(), delta=1.5, alpha=1, number=10)
## 
## Number of Clusters found:  4 
## 
## First  4  Cluster sizes:
##                    BC 1 BC 2 BC 3 BC 4
## Number of Rows:       6    6    5    3
## Number of Columns:    7    5    7    4
bicluster(tds, res)
## $Bicluster1
##      [,1] [,2] [,3] [,4] [,5] [,6] [,7]
## [1,]   17   16   19   21   22   17   19
## [2,]   18   20   17   22   24   17   18
## [3,]   19   20   24   25   26   20   21
## [4,]   17   16   15   19   23   17   20
## [5,]   20   19   18   22   23   20   19
## [6,]   16   20   20   23   23   19   20
## 
## $Bicluster2
##      [,1] [,2] [,3] [,4] [,5]
## [1,]   19   17   23   17   20
## [2,]   20   19   22   19   17
## [3,]   20   19   24   24   21
## [4,]   22   16   22   20   20
## [5,]   21   17   23   20   17
## [6,]   22   19   25   24   22
## 
## $Bicluster3
##      [,1] [,2] [,3] [,4] [,5] [,6] [,7]
## [1,]   18   18   18   19   19   19   20
## [2,]   15   20   19   23   18   21   17
## [3,]   18   18   19   18   19   21   18
## [4,]   22   22   21   22   21   24   20
## [5,]   18   21   20   24   21   22   19
## 
## $Bicluster4
##      [,1] [,2] [,3] [,4]
## [1,]   18   18   21   20
## [2,]   19   20   25   19
## [3,]   15   15   21   16
parallelCoordinates(tds, res, number=4)

data(BicatYeast)
tds <- discretize(BicatYeast)
res <- biclust(tds, method=BCXmotifs(), alpha=0.05, number=50)
res
## 
## An object of class Biclust 
## 
## call:
##  biclust(x=tds, method=BCXmotifs(), alpha=0.05, number=50)
## 
## Number of Clusters found:  20 
## 
## First  5  Cluster sizes:
##                    BC 1 BC 2 BC 3 BC 4 BC 5
## Number of Rows:     160   76   59   37   21
## Number of Columns:    6    8    6    6    9
parallelCoordinates(BicatYeast, res, number=4)

plotclust(res, tds)

tds <- tribble(~x, ~y,
               1, 1,
               2, 1,
               1, 0,
               4, 7,
               3, 5,
               3, 6)

res <- biclust(as.matrix(tds), method=BCCC(), delta=50, alpha=0, number=5)
res
## 
## An object of class Biclust 
## 
## call:
##  biclust(x=as.matrix(tds), method=BCCC(), delta=50, alpha=0, 
##      number=5)
## 
## There was one cluster found with
##   6 Rows and  2 columns

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