Annotating your data is the process of labeling files so that users can:
get a general understanding of what information is contained in the file
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determine what type of experiment was performed
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determine what type of biospecimen was used
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assess whether the data is the type of data that they are looking for
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Annotation is not a replacement for sharing experimental methods via a publication method section, in your Synapse project, or via a protocol repository like http://protocols.io. |
To annotate Annotating your data , first:
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If you are not yet logged in: log in to Synapse.org.
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If you have not yet uploaded your data that you would like to annotate:
Navigate to your Synapse Project that was assigned to you at the time of project on-boarding.
Within the “Raw Data” or “Data” folder, create a new folder to house your current data upload.
Upload the data to this folder.
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Navigate to the NF Data Curator app.
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involves the following actions, to be completed in order:
1. Log in to Synapse
2. Ensure your data is properly uploaded
If you haven’t done so already, follow the instructions at How to Upload Data.
3. Navigate to the NF Data Curator app
In order to access the app, you must be logged into Synapse. If you are not already logged into Synapse when you land on this page, you will be prompted to do so. Click the Synapse link provided on the page to log in to Synapse, and then refresh the app page—you should now be able to access it.
4. Find the data you want to annotate
Once in the app, follow the prompts to select the project, folder
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, and the type of assay you are annotating.
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If the app is idle for too long, it will disconnect to reduce the load on the server. Simply refresh the page to restart the app
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.
5. Generate metadata template
Click
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Get Metadata Template
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, followed by Click to generate google sheets
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template
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, and wait for the app to provide a google sheet link. This may take a few moments, particularly if you have many files or lots of existing annotations on your files.
Note: you may download the manifest as an excel file (File → Download → Microsoft Excel), but we have not extensively tested functionality in Excel. If you encounter any issues filling in the manifest in Excel, please contact us at nf-osi@sagebionetworks.org.
6. Fill in the manifest
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For this step, you may need to reference our full metadata dictionary, including definitions, is available in our Schema spreadsheet. |
For each column, hover over the column title to get a better idea of what type of information is needed in each column. For example, you can hover over the
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individualID column header to see the definition:
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A unique identifier (non-PII) that represents the individual from which the data came. This could be a patient or animal ID.
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Then:
Use the dropdown selector for each cell to pick a value
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For example, if you are annotating a western blot image, under assay, you’d select
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westernBlot
If no terms fit, please type in a term that you feel best fits your file
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For columns without a dropdown, we do not have controlled vocabulary (these are generally project-specific IDs, such as an anonymous patient ID (called
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individualID)
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Continue filling in the columns until all required (green columns) and all relevant optional columns (yellow columns) are filled in
7.
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Submit your manifest
Coming off of step 6, this next step will depend on whether your manifest required custom terms or not.
If your manifest did not require any custom terms
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Submit your manifest using the Submit and Validate Metadata tab in the NF Data Curator app
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Download the completed manifest as a .csv file from Google Sheets (or, if using Excel, save as csv)
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Upload the .csv into the data curator app, following the on-screen instructions to validate your manifest
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Follow the on-screen instructions if validation errors are present
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Once your manifest passes validation, click
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Submit to
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Synapse to annotate your files
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If your manifest did require custom terms
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Email the completed google sheet or excel file to nf-osi@sagebionetworks.org so that we can add your new terms to our dictionary
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We’ll
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work with you to get the annotations applied to your data
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