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:    6    5    4    8

bicluster(tds, res)

## $Bicluster1
##      [,1] [,2] [,3] [,4] [,5] [,6]
## [1,]   23   18   21   23   21   21
## [2,]   24   20   21   22   20   20
## [3,]   19   15   20   21   21   20
## [4,]   20   19   20   23   18   18
## [5,]   22   18   18   20   21   18
## [6,]   19   18   19   21   22   21
## 
## $Bicluster2
##      [,1] [,2] [,3] [,4] [,5]
## [1,]   22   24   23   22   22
## [2,]   20   19   16   18   21
## [3,]   15   17   15   16   19
## [4,]   23   22   20   22   25
## [5,]   21   18   21   18   19
## [6,]   14   16   13   16   16
## 
## $Bicluster3
##      [,1] [,2] [,3] [,4]
## [1,]   22   20   15   19
## [2,]   21   21   17   26
## [3,]   24   25   18   25
## [4,]   23   22   19   23
## [5,]   22   20   17   21
## 
## $Bicluster4
##      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8]
## [1,]   27   22   26   29   28   22   24   24
## [2,]   20   19   18   22   18   14   22   16
## [3,]   22   17   21   20   20   16   21   18

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:  22 
## 
## First  5  Cluster sizes:
##                    BC 1 BC 2 BC 3 BC 4 BC 5
## Number of Rows:     168   60   48   33   29
## Number of Columns:    6    8    9    8    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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