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    4    3
## Number of Columns:    7    5    6    5
bicluster(tds, res)
## $Bicluster1
##      [,1] [,2] [,3] [,4] [,5] [,6] [,7]
## [1,]   21   21   22   18   19   20   23
## [2,]   21   18   21   20   20   21   21
## [3,]   22   21   24   20   19   20   22
## [4,]   20   18   19   22   22   20   21
## [5,]   24   19   22   21   21   21   22
## [6,]   20   17   22   17   20   21   24
## 
## $Bicluster2
##      [,1] [,2] [,3] [,4] [,5]
## [1,]   18   21   21   25   18
## [2,]   18   18   17   19   16
## [3,]   18   21   21   21   21
## [4,]   20   19   20   21   18
## [5,]   20   20   23   23   21
## [6,]   22   23   22   21   19
## 
## $Bicluster3
##      [,1] [,2] [,3] [,4] [,5] [,6]
## [1,]   21   23   16   16   21   20
## [2,]   20   23   17   18   19   22
## [3,]   22   23   22   21   21   22
## [4,]   19   20   17   17   21   23
## 
## $Bicluster4
##      [,1] [,2] [,3] [,4] [,5]
## [1,]   17   17   15   17   18
## [2,]   23   18   20   19   23
## [3,]   23   22   21   24   23
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:     119  100   63   34   14
## Number of Columns:    7    6    7    6   11
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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