workvafin
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workvafin [2021/01/11 16:25] – [Diabetes study] mestebanm | workvafin [2021/01/19 17:37] (current) – [Results and interpretation] jdopazo | ||
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**2-** We will work with expression data from custom tissue related to Diabetes. In this case we will work with a gene expression dataset of human islets from 63 donors (54 non-diabetic and 9 type 2 diabetic). You can download the raw expression matrix used for this example from GEO repository, accession number [[https:// | **2-** We will work with expression data from custom tissue related to Diabetes. In this case we will work with a gene expression dataset of human islets from 63 donors (54 non-diabetic and 9 type 2 diabetic). You can download the raw expression matrix used for this example from GEO repository, accession number [[https:// | ||
- | For the purpose of this example we will only use the data of the 54 non diabetic donors. The Variant interpreter tool allows to explore the functional consequences of the variation in the expression of a gene or a combination of genes. The aim of this example is to investigate the functions and biological | + | For the purpose of this example we will only use the data of the 54 non diabetic donors. The Variant interpreter tool allows to explore the functional consequences of the variation in the expression of a gene or a combination of genes. The aim of this example is to investigate the functions and biological |
Hipathia only takes as input **normalized data**, so you will have to correctly normalize the raw expression matrix to be uploaded. | Hipathia only takes as input **normalized data**, so you will have to correctly normalize the raw expression matrix to be uploaded. | ||
- | * Custom tissue expression matrix after normalization: | + | * Custom tissue expression matrix after normalization: |
**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]]. | **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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When the analysis is finished at Hipathia web, the report/ | When the analysis is finished at Hipathia web, the report/ | ||
- | As we can see in the figure below, the results after the simulating the KO of gene RAP1GAP over the 54 non diabetic samples only show deregulation on the pathways where the gene RAP1GAP can be found. Since RAP1GAP is an inhibitor of the Rap1 pathway, mostly all the functions associated to the circuits that compose the pathway are UP-regulated. The functional consequences of the KO of RAP1GAP vary from UP-regulation of Inflammatory processes, Cell adhesion and Stress response among others. The results shown seem to indicate that RAP1GAP plays an important role in the control of these processes highly related to diabetes. Therefore, | + | As we can see in the figure below, the results after the simulating the LoF variant |
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+ | Moreover, LoF variants vary considerably in their effects on human phenotype. They can represent severely deleterious disease-causing mutations, however, they will also include mildly deleterious variants with small effects on fitness, and neutral variants disrupting the function of non-essential genes. The Variant interpreter option provide a user-friendly tool for // | ||
workvafin.1610382343.txt.gz · Last modified: 2021/01/11 16:25 by mestebanm