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Worked example Prediction

Test inputs

1. Log in into HiPathia. For further information on this step visit Logging in.

2. We will test the model with another Breast Cancer dataset (Luminal A Vs Luminal B) from the repository The Cancer Genome Atlas. You can download the expression matrix of the test data from the link:

Test expression matrix: brca_genes_vals_bn_test.txt

3. Upload the data to HiPathia in the data panel by clicking on My data. For further information on this step visit Upload your data.

4. Click Prediction button.

5. In the Type panel, select Test existing predictor. A window with all the existing models will appear. Select the model you want to use. We will use the model we have created in Worked example Prediction - Train. The model information will appear on the right panel.

6. In the Input data panel select Expression matrix. Press the File browser of the Expression matrix file, and select the desired file, brca_genes_vals_bn_test.txt.

7. In the Job information panel, press the File browser button and select the desired output folder. In this case, we will use analysis_BRCA. Give a name to the study, for example, “BRCA test model”.

8. Press the Run analysis button. A study will be created and listed in the studies panel. You can access this panel by clicking on the My studies button.

Test report

As we said before, this experiment consists in test the trained model (in this example), using another split of data (Luminal A or Luminal B).

Study Information

Here you can find the information about the selected study.

Name: the study name.
Description: the description of the current study.
Tool: the name of the used tool (in this case, is Hipathia).
Date: study's launching date (MM/DD/AAAA, HH:MM:SS AM/PM format)

Input Parameters

Here you can find the parameters with which the current study was launched.

Expression file: The name of the expression file that has been used in the current study.
Species: The species of this experiment; Human (Homo sapiens),Mouse (Mus musculus) or Rat (Rattus norvegicus).

Circuit values

You can download the matrix of circuit activity values by clicking on circuit values. This matrix file indicates for each “effector circuit” the level of activation calculated using Hipathia method for each sample.

Prediction model

This is the most important result of our predictor, which is a matrix with three columns :

Sample name: all the 125 samples in the used expression matrix file.
Prediction: the predicted group LumB (Luminal B) or LumA (Luminal A)
Probability LumB: this is the probability of being lumB, if it is 1 that means the predictor is 100% sure that the given result will be LumB.

You can download the matrix of predicted experimental design by clicking on Prediction results.

Prediction evaluation

Confusion Matrix and Statistics

    	     Reference

Prediction LumA LumB

	LumA   95	5
	LumB	9   16
                                   	 
         	Accuracy : 0.888      	 
           	95% CI : (0.8192, 0.9374)
No Information Rate : 0.832      	 
P-Value [Acc > NIR] : 0.0547     	 
                                   	 
            	Kappa : 0.6277

Mcnemar's Test P-Value : 0.4227

                                   	 
      	Sensitivity : 0.9135     	 
      	Specificity : 0.7619     	 
   	Pos Pred Value : 0.9500     	 
   	Neg Pred Value : 0.6400     	 
       	Prevalence : 0.8320     	 
   	Detection Rate : 0.7600     	 
 Detection Prevalence : 0.8000     	 
	Balanced Accuracy : 0.8377

hiPathia

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