differential_signaling_exercises
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| * Experimental design: {{:GSE51835-Exercise_ED.txt|}} | * Experimental design: {{:GSE51835-Exercise_ED.txt|}} | ||
| - | **1.1.-** Run the Differential signaling tool with these files, selecting the option //Color nodes by differential expression//. Take a llok to the results. Which pathways are differentially activated? | + | **1.1.-** Run the Differential signaling tool with these files. Take a look to the results. Which pathways are differentially activated? |
| **1.2.-** What is the role of the differentially expressed genes in the pathways? | **1.2.-** What is the role of the differentially expressed genes in the pathways? | ||
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| - | **1.3.-** Run the Differential signaling tool with these files again, selecting the option //Decompose paths//. Which diferences can you find between the two methods? | ||
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| Run the Differential signaling tool with these files, selecting the options of both functional analysis //Gene ontology// and //Uniprot keywords//. | Run the Differential signaling tool with these files, selecting the options of both functional analysis //Gene ontology// and //Uniprot keywords//. | ||
| - | Try to identify representative functions of this experiment (related to the disease). Are there significative functions? Are they related with the disease? | + | **2.1.-** Try to identify representative functions of this experiment (related to the disease). Are there significative functions? Are they related with the disease? |
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| + | **2.2.-** Look at the Heatmaps provided by the tool for the different analyses. Do you think that a predictor could be trained from these data? With which matrix do you think that it would work better? | ||
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| * Experimental design: {{:kirc_demo_ED_class.txt|}} | * Experimental design: {{:kirc_demo_ED_class.txt|}} | ||
| - | **3.1.-** Run the Differential signaling tool with these files, selecting also the functional analyses. You can select the option //Color nodes by differentail expression// if desired. Look at the results. If you have done Exercises 1 or 2, can you find any difference in the results of this dataset? | + | **3.1.-** Run the Differential signaling tool with these files, selecting also the functional analyses. Find representative paths and functions of this disease. |
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| - | **3.2.-** Look at the Heatmaps provided by the tool for the different analyses. Do you think that a predictor could be trained from these data? With which matrix do you think that it would work better? | + | |
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| - | Stages describe the natural evolution of any cancer. You can find further information on the matter in | + | |
| - | [[http://www.cancer.gov/about-cancer/diagnosis-staging/staging/staging-fact-sheet]]. | + | |
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| - | Now we will try to understand how the Kidney cancer evolves by comparing the initial (I) with the final (IV) stages. We will use a subset of the former matrix, with a new experimental design, that you can download from the following links: | + | |
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| - | * Expression matrix: {{:kirc_demo_genes_vals_tumor.txt|}} | + | |
| - | * Experimental design: {{:kirc_demo_ED_stages.txt|}} | + | |
| - | **3.3.-** Run the Differential signaling tool with the former files comparing stage I versus stage IV. Compare the results with those given in Exercise 3.1. Are there any differences? What do they mean? | + | **3.2.-** Look at the results. If you have done Exercises 1 or 2, can you find any difference in the results of this dataset? |
| - | **3.4.-** Look for some paths which are related with disease but not with its progression. | ||
| ==== Exercise 4 ==== | ==== Exercise 4 ==== | ||
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| Then we will analyze the luminal subtype. This subtype is divided in two classes, A and B, but we will not take into account this division. You can download the normalized expression matrix and the experimental design from these links: | Then we will analyze the luminal subtype. This subtype is divided in two classes, A and B, but we will not take into account this division. You can download the normalized expression matrix and the experimental design from these links: | ||
| - | * Expression matrix: {{:brca_genes_vals_b.txt|}} | + | * Expression matrix: {{:brca_genes_vals_ln.txt|}} |
| - | * Experimental design: {{:brca_normal-luminal_ed.txt|}} | + | * Experimental design: {{:brca_luminal-normal_ed.txt|}} |
| Identify paths and functions which are significant for each type of breast cancer. | Identify paths and functions which are significant for each type of breast cancer. | ||
| Try to find differences between these two subtypes of breast cancer. | Try to find differences between these two subtypes of breast cancer. | ||
| - | If you are familiar with R, you can compare both cancer subtypes by merging the two datasets and run the resulting dataset in HiPathia. | + | If you are familiar with R, you can compare both cancer subtypes by combining both datasets and run the resulting dataset in HiPathia. |
differential_signaling_exercises.1456334362.txt.gz · Last modified: 2020/04/03 20:18 (external edit)
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