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    5    5    3
## Number of Columns:    5    7    5    5

bicluster(tds, res)

## $Bicluster1
##      [,1] [,2] [,3] [,4] [,5]
## [1,]   17   18   20   20   17
## [2,]   17   20   22   22   19
## [3,]   19   16   20   17   17
## [4,]   19   23   23   20   18
## [5,]   18   21   24   22   18
## [6,]   22   23   22   23   21
## 
## $Bicluster2
##      [,1] [,2] [,3] [,4] [,5] [,6] [,7]
## [1,]   20   23   18   19   16   18   20
## [2,]   22   24   19   19   18   18   24
## [3,]   23   23   21   19   20   19   22
## [4,]   21   18   15   19   17   15   17
## [5,]   25   22   19   19   21   17   20
## 
## $Bicluster3
##      [,1] [,2] [,3] [,4] [,5]
## [1,]   19   15   18   14   21
## [2,]   17   18   19   18   21
## [3,]   21   21   23   17   22
## [4,]   19   20   23   21   24
## [5,]   19   19   21   16   23
## 
## $Bicluster4
##      [,1] [,2] [,3] [,4] [,5]
## [1,]   19   18   21   16   17
## [2,]   19   15   17   15   14
## [3,]   23   19   24   21   22

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:  19 
## 
## First  5  Cluster sizes:
##                    BC 1 BC 2 BC 3 BC 4 BC 5
## Number of Rows:     148  125   27   22   20
## Number of Columns:    6    6    6    9    7

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

• https://en.wikibooks.org/wiki/Data_Mining_Algorithms_In_R/Clustering/Biclust

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