jaccard: Jaccardind

In biclust: BiCluster Algorithms

Description

An adaption of the Jaccard Index for clustering is calculated.

Usage

jaccardind(bicres1,bicres2)
jaccard2(Rows, Cols)

Arguments

bicres1	A object of class Biclust
bicres2	A object of class Biclust
Rows	Matrix containing rows of biclusters
Cols	Matrix containing cols of biclusters

Details

The function calculates the percentage of datapoints in the same bicluster structure from all datapoints at least included in one bicluster.

Value

jaccardind calculates the Jaccard index jaccard2 returns a similarity matrix containing the Jaccard index between all biclusters (upper triangle matrix)

Author(s)

Sebastian Kaiser [e-mail]

Examples

## Not run: 
data(BicatYeast)
res1<-biclust(BicatYeast, method=BCPlaid(), back.fit = 2, shuffle = 3,
  fit.model = ~m + a + b,iter.startup = 5, iter.layer = 30,  verbose = TRUE)
res2<-biclust(BicatYeast, method=BCCC())
jaccardind(res1,res2)


## End(Not run)

Example output

Loading required package: MASS
Loading required package: grid
Loading required package: colorspace
Loading required package: lattice
layer: 0 
 1224.87
layer: 1 
[1]   0 153   4
[1]   1 161   4
[1]   2 156   4
[1]   3 155   4
[1]  30 155   4
[1] 31 74  4
[1] 32 74  4
[1] 33 71  4
[1] 34 71  4
[1] 35 65  4
[1] 36 65  4
[1] 37 64  4
[1] 38 64  4
[1] 39 64  4
[1] 60 64  4
[1] 4
[1] 938.4732   0.0000   0.0000   0.0000
back fitting 2 times
layer: 2 
[1]   0 200  15
[1]   1 198  13
[1]   2 198  12
[1]   3 200  12
[1]   4 202  12
[1]   5 201  12
[1]   6 200  12
[1]   7 201  12
[1]  30 201  12
[1] 31 21 12
[1] 32 21 10
[1] 33 20 10
[1] 34 20 10
[1] 35 19 10
[1] 36 19 10
[1] 37 19 10
[1] 60 19 10
[1] 8
[1] 505.0514   0.0000   0.0000   0.0000
back fitting 2 times
layer: 3 
[1]   0 151   6
[1]   1 129   6
[1]   2 122   6
[1]   3 119   6
[1]   4 118   6
[1]  30 118   6
[1] 31 59  6
[1] 32 59  5
[1] 33 56  5
[1] 34 56  5
[1] 35 54  5
[1] 36 54  5
[1] 37 53  5
[1] 38 53  5
[1] 39 53  5
[1] 60 53  5
[1] 5
[1] 1208.511    0.000    0.000    0.000
back fitting 2 times
layer: 4 
[1]   0 197  12
[1]   1 172  12
[1]   2 156  12
[1]   3 153  12
[1]   4 149  12
[1]   5 147  12
[1]   6 146  12
[1]  30 146  12
[1] 31 14 12
[1] 32 14  6
[1] 33 14  6
[1] 34 14  5
[1] 35 14  5
[1] 60 14  5
[1] 7
[1] 157.4592   0.0000   0.0000   0.0000
back fitting 2 times
layer: 5 
[1]   0 198  12
[1]   1 171  12
[1]   2 160  12
[1]   3 152  12
[1]   4 146  12
[1]   5 142  12
[1]   6 140  12
[1]  30 140  12
[1] "Zero residual degrees of freedom"
[1] 31  1 12
[1] "Zero residual degrees of freedom"
[1] 32  1 12
[1] 33  0 12
[1] 34
[1] 0 0 0 0
     
Layer Rows Cols  Df      SS    MS Convergence Rows Released Cols Released
    0  419   70 488 2065.51  4.23          NA            NA            NA
    1   64    4  67 1269.18 18.94           1            91             0
    2   19   10  28  573.53 20.48           1           182             2
    3   53    5  57 1777.90 31.19           1            65             1
    4   14    5  18  191.14 10.62           1           132             7
[1] 0.006627616

biclust documentation built on May 2, 2019, 5:56 p.m.