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worked_example_prediction [2021/01/07 20:43] krianworked_example_prediction [2021/01/30 16:49] (current) – removed krian
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-====== Worked example Prediction  ====== 
- 
-===== Test ===== 
- 
-**1.** Log in into HiPathia. For further information on this step visit [[logging_in|Logging in]]. 
- 
-**2.** We will test the model with another Breast Cancer dataset 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|}} 
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-**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|Upload your data]]. 
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-**4.** Click //Prediction// button.  
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-{{ :hipathia_bar_pred.png?600 |}} 
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-**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|Worked example Prediction - Train]]. The model information will appear on the right panel. 
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-{{ :hipathia_work5.png?600 |}} 
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-**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//. 
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-{{ :hipathia_work6.png?600 |}} 
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-**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". 
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-{{ :hipathia_work7.png?600 |}} 
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-**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. 
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-===== Test report===== 
-As we said before, this experiment consists in test the trained model [[worked_example_prediction_-_train|(in this example)]], using another split of data (Luminal A or Luminal B). 
-{{ ::testreport.png?nolink |}} 
-==== 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.  
-{{ ::inputpredictreport.png?nolink |}} 
-  * **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 
- 
  
worked_example_prediction.1610052212.txt.gz · Last modified: 2021/01/07 20:43 by krian