bioNMF Results


bioNMF 1.0 - Main Menu
Job's parameters:
Job's ID:Biclustering_example
Analysis type:Biclustering analysis
Data matrix has numeric column headers:No
Data matrix has numeric row labels:No
Transpose data matrix:No
Normalization method:Do not normalize
Method to make data positive:Exponential scalling
Minimum number of factors:3
Maximum number of factors:5
Number of runs per factorization:40
Number of iterations:2000
Stopping threshold:40
Save options:Just save the best factorization
Sparseness ([0..1]):0.5
NMF results:
Best rank of factorization:4
Best Run (0-based indexing):21
Explained Variance:82.5149

Input matrix V heatmap Input matrix V profile
 
Matrix W Matrix H
Matrix W (data with labels) Matrix H (data with labels)
Matrix W heatmap Matrix H heatmap
Matrix W profile Matrix H profile
Biclustering analysis results:
Number of biclusters found:4
 
Bicluster 1:

Bicluster 1 data
Bicluster 1 data (with labels)
Bicluster 1 row-indexes (1-based indexing)
Bicluster 1 column-indexes (1-based indexing)
 
Bicluster 2:

Bicluster 2 data
Bicluster 2 data (with labels)
Bicluster 2 row-indexes (1-based indexing)
Bicluster 2 column-indexes (1-based indexing)
 
Bicluster 3:

Bicluster 3 data
Bicluster 3 data (with labels)
Bicluster 3 row-indexes (1-based indexing)
Bicluster 3 column-indexes (1-based indexing)
 
Bicluster 4:

Bicluster 4 data
Bicluster 4 data (with labels)
Bicluster 4 row-indexes (1-based indexing)
Bicluster 4 column-indexes (1-based indexing)
Job's output-file (detailed information and timings)
bioNMF 1.0 - Main Menu