The Assays application has a powerful and flexible data model specifically designed to store experimental data. Each assay (a.k.a., experimental run) that is recorded in the application can be loaded with experimental data tables associated with a particular experiment.

The users can either manually annotate the different datasets for column types or use our auto mapper feature which relies on machine learning capabilities to automatically annotate the data with their relevant column types.

Here, we are going to learn how to execute the latter, i.e., automatically annotating your datasets with column types.

Click on Assays from the Data Analysis Toolkit in the left menu of the TeselaGen application.

It will take you to the "Import Experiment Data into Assay" tool, where you can access your pre-registered experiments data grids or import new (assay) files. In this example, we are going to import a new file.

It will take you to the Data Selection interface, where you can select the data from Data Grids.

This will take you to the Data Mapping interface.

On the Data Mapping Interface, you will see undefined classes and sub-classes. Instead of going through each individual column and naming it with a descriptor as per the data type, you can use the pre-saved Maps or the Smart Mapper.

You can now see the Smart Mapper dialog box. This will identify available data types in your experimental data and then will automatically map your columns with relevant class and sub-class types using machine learning algorithms.

You can either check the Accept all box or individually check the box for each row to confirm whether the mapping suggestions fit your needs, and once did click the confirm button to "auto" map your Assay datasets.

This will also enable the validate button on the bottom right of your screen meaning that your mapping is correct. Once validated, a Save option will replace Validate.

Click on Validate and then Submit.

You can then see your Assay on the Assay Import Jobs in the Data Analysis Toolkit and access it from there.

Supplementary Readings