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:       7    6    4    3
## Number of Columns:    5    6    6    7

bicluster(tds, res)

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

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:  15 
## 
## First  5  Cluster sizes:
##                    BC 1 BC 2 BC 3 BC 4 BC 5
## Number of Rows:     146  119   52   24   15
## Number of Columns:    6    7    6    8   10

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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