We have identified an issue affecting Lab Auto Runs created more than two years ago before 2022. These older runs were originally configured to function correctly, even though the configurations may not now appear accurate in the run UI editor. Run schemas created in or before 2022 can show a generic “Schema Field” for their column mappings in the UI, which can look unusual but continues to work in the backend.

However, if these older runs are modified now—such as when updating column mappings or adding new columns—the configurations displayed in the frontend will overwrite the correct backend configurations. This results in the run breaking because the actual behavior will now match the broken display shown in the frontend.

We have identified all runs that have been affected and any new runs created or edited will not have this issue. If you would like a list of the affected runs in your tenant(s), please reach out to Benchling support. 

Resolution Options

To resolve the issue with outdated Lab Auto run configurations, follow either of these two proposed options. These options will allow you to maintain the correct column mappings while avoiding the problems associated with modifying older configurations. We highly recommend the first option as it allows you to only change the affected columns and is the easier option. 

If you would like to get a list of your affected runs, please reach out to Benchling Support with the email subject: “Legacy Lab Auto Runs Mapping Configuration Issue”. We are here to support you through this process and ensure everything works smoothly.

Option 1: Remap By Column Order (Recommended Option)

1. Identify Column Mappings: 

• When the mapping type is set ‘By column order’, review the Columns with the generic ‘Schema Field’ mapping. 
• In the image below we see Column C and Column D need to be re-mapped with the correct Column type.

2. Review the Input File for the run: 

• In this example, in our Input file we found that Column C is for ‘Plasmid’ and Column D is for ‘Cell Line’. 

3. Remap Schema Fields: 

• Change the Column type to their correct labels. 
• In this example, the correct mapping is ‘Schema Field: Plasmid’ for Column C and ‘Schema Field: Cell Line’ for Column D. 
• This will align the schema with the actual data without causing any issues with backend functionality.

Option 2: Remap By Column Name

To resolve the issue by referencing the JSON of the run schema, follow these steps:

1. Open Column Mapping Modal: 

• Begin by opening the column mapping modal for the output file configuration. You’ll likely see that the columns are mapped By column order rather than By column name. 
• Some columns will display as “Schema Field” without specifying which exact schema field they correspond to.

2. Check the JSON Editor:

• Open the run in the JSON editor and navigate to the entitySchemaInfo, resultSchemaInfo, or destinationInfo sections.
• Under these sections, you’ll find a fields section containing items with columnName and "type": "DIRECT". These entries correspond to the unspecified Schema Field columns seen in the UI.

3. Review a Previously Processed File:

• Download a previously processed file for this output processor to examine the column structure. For instance, if Columns C and D are unspecified, look at this file to determine what was in those columns (e.g., “Plasmid” for Column C and “Cell_Line” for Column D).

4. Remap Schema Fields:

• Return to the column mapping modal and make sure to switch the mapping type to By column name.
• Manually input the correct column names and remap the “Schema Field” columns to their proper schema fields, based on your findings in your previously processed file in the JSON editor.
• For example, if the JSON shows that the third and fourth columns should correspond to “Expression Plasmid” and “Parent Cell Line”, the column names you enter should be “Plasmid” and “Cell_Line.”
• Make sure to enter the names for all other columns as well.

Either of these approaches should allow you to maintain the correct column mappings while avoiding the problems associated with modifying older configurations. By following these steps, you’ll ensure that the column mappings are correctly aligned with the actual schema fields, preventing future issues when the run is updated.