Step 1. Begin by locating the Immunogenicity icon on your dashboard or application interface. This icon is typically represented by a distinctive symbol that signifies immunogenicity analysis. Once you have identified the icon, click on it to initiate the process. This action will lead you to the job execution interface, where you can manage and run your immunogenicity jobs effectively.
Step 2. Select a pre-uploaded dataset from the 'input_dataset_id' field. When you click on the input field, a dropdown menu will appear, showcasing all available datasets that have been previously uploaded to the system. Take a moment to review the list and identify the dataset that best suits your analysis needs. It's important to note that you should select the entire dataset rather than individual files contained within it, as the process is designed to work with datasets as a whole. To aid in your selection, you may see additional details such as dataset names, descriptions, or timestamps indicating when they were uploaded. Once you have made your selection, confirm your choice to proceed to the next steps in the immunogenicity analysis workflow.
Step 3. Provide an experiment name. This name serves as a unique identifier for your immunogenicity analysis, making it easier to reference and track your work later. When creating your experiment name, it is crucial to avoid using white spaces, as the current system does not support names with spaces. Instead, consider using underscores (_) to separate words for clarity. For example, instead of naming your experiment "Immunogenicity Study 2023," you could use "Immunogenicity_Study_2023". This practice will help ensure that your experiment name is compliant with the system’s requirements and facilitate smoother data processing. Once you have crafted an appropriate name, enter it in the designated field to proceed to the next steps in the immunogenicity analysis workflow.
Step 4. Extra options are provided in case you want to apply a filter on specific Loci or ethnicities. This step allows you to refine your analysis by focusing on particular genetic regions (Loci) or demographic groups (ethnicities) that are of interest to your study. To utilize these filtering options, you can select the specific Loci or ethnicities you wish to include in your analysis by including them in the input fields.
When filtering by Loci, consider the biological relevance of the regions you choose, as this can significantly impact the interpretation of your immunogenicity results. For ethnicities, selecting the appropriate group can help ensure that the analysis is tailored to the population you are studying, which may yield more meaningful insights into the immune response.
Make sure to review the information provided for each available option, as it may include descriptions or data about the significance of certain Loci or ethnic groups in immunogenicity studies. Once you have made your selections, apply them by typing in the provided box to ensure that your analysis will be based on the specific parameters you've identified. This targeted approach enhances the accuracy and relevance of your immunogenicity analysis.
Step 5. Launch the calculation by clicking the run job button at the bottom left. After confirming your selections and entering all required information, you are ready to initiate the analysis. Clicking the run job button will start the process, and you will receive a notification or progress indicator informing you of the job's status. Depending on the complexity of your analysis and the size of your dataset, this process may take some time. You can monitor the progress through the interface and will be notified once the analysis is complete, enabling you to review and interpret your results efficiently.
