Raw Results

 

In this section, you can view the output results generated by our program.

The output contains a list of all the genes, with their TNoM score and p-value, sorted by their p-value.

 

Step 1 – Running data without noise.

For the output of the non-weighted version on the raw data (before adding the noise), click here.

 

Step 2 – Running data with noise produced using table 2

After adding the noise using the table 2 in the quality analysis section and running the un-weighted algorithm we’ve received these results (click here).

The attached algorithm output can be found here.

The unattached algorithm output can be found here.

A summery comparing the un-weighted algorithm to the attached algorithm can be found here.

A summery comparing the un-weighted algorithm to the unattached algorithm can be found here.

 

Step 3 – Running data with noise produced using the statistical method.

Since we observed that the attached version is the one improving the results while the unattached version does not, we decided to continue our testing using only the attached version. From this point on, we used the second (statistical) method for producing noise. For each gene quality, we’ve run 10 tests, each time re-creating the weights and noise matrices. Since there are a total of 220 output files, we shall only list the summery files containing the M-measures and their averages.

For the summery, click here.

 

 

Results of running the algorithms on Real Data

 

Normal artery vs. diseased artery:

The non-weighted algorithm output can be found here.

The weighted algorithm output can be found here.

 

Diseased arteries from patients who suffer from diabetes vs. diseased arteries from patients who don't suffer from diabetes:

The non-weighted algorithm output can be found here.

The weighted algorithm output can be found here.

 

Normal arteries from patients who suffer from diabetes vs. normal arteries from patients who don't suffer from diabetes:

The non-weighted algorithm output can be found here.

The weighted algorithm output can be found here.