Ok, I think I understand. The study is used to describe the overall experiment and the sample generation. Then the assays are used to describe the individual lab processes and the data generation!
Right! In assays you can store data and metadata from measurements.
You can have multiple assays in one ARC. Each assay can have its own metadata, data, and protocols. How you structure your assays is up to you.
In general it is a good approach to describe each logical process in a separate assay.
Then let’s start with the “Sugar Measurement” assay.
Click on the plus icon next to assays to add a new assay.
Enter a name for the New Assay.
SugarMeasurement
Click New Assay.
ARCitect adds the assay SugarMeasurement including the folders dataset and protocols as well as a README.md and the isa.assay.xlsx workbook. You can display the file structure created by ARCitect by clicking on SugarMeasurement as shown below.
Directoryassays
DirectorySugarMeasurement
Directorydataset
…
Directoryprotocols
…
isa.assay.xlsx
README.md
…
Click on the assay’s name (SugarMeasurement) in the file tree to edit the assay metadata in the right panel.
Here you can add metadata about your assay.
Ok, so my measurement type is “sugar measurement”.
And to specify the device I used for my measurement, I add “photometry” and “Infinite M200 plate reader (Tecan)” as the technology type and technology platform, respectively.
Just as with studies, the individual assay elements (protocols, data, metadata) find a specific place in the assay subfolders.
This enhances the reusability and identification of each element.
Following the simple approach of reusing sample and data identifiers in different parts of the ARC, we were able to concisely link the samples through the different lab processes in studies and assays to the data produced from those samples.