<< bioNMF: a tool for Non-negative Matrix Factorization in biology >>
Analysis parameters:
Analysis method: Biclustering Analysis.
Analysis algorithm: Non-smooth.
Sparsity level ([0..1]): 0.5.
Factorization range: K = [2..5].
Number of runs per K: 40.
Number of iterations per run: 2000.
Stopping threshold: 40 iterations.
Save output matrices: Combine all matrices.
Save heatmaps and profiles for input/output matrices: Yes.
Save analysis's output images: Yes.
Loading and preprocessing data matrix...
Input file selected as ASCII-text. Loading...
Data matrix selected as having numeric column headers: No.
Data matrix selected as having numeric row labels: No.
Row labels detected.
Number of data columns detected (excluding row labels): 20.
Name (ie. description string) detected.
Column headers detected.
Loaded a 100 x 20 data matrix (2000 items).
Done in 0.001174 seconds.
Transpose data matrix: No.
Normalization method: Do not normalize.
Transformation method to make data positive: Exponential scaling.
Done in 4.2e-05 seconds.
Done in 0.001645 seconds.
Biclustering Analysis: Non-smooth, K=[2..5], 40 time(s) per K, sparseness=0.5
Starting NMF...
Done in 5.600032 seconds.
Orderconsensus step...
Done in 0.0035 seconds.
Best K value: 4
Combining output matrices W...
Done in 0.020303 seconds.
Done in 5.661034 seconds.
Postprocessing...
Drawing and saving heatmaps and profiles for input and output data matrices... done in 1.36254 seconds.
Building gene modules... done in 0.153394 seconds.
Printing biclusters... done in 0.773455 seconds.
Total postprocessing time: 2.33202 seconds.