Add assay data

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.

Assay: Sugar Measurement

Section titled Assay: Sugar Measurement

Add a new assay

Section titled Add a new assay

ARCitect

1. Click on the plus icon next to assays to add a new assay.

2. Enter a name for the New Assay.

   

   SugarMeasurement

3. Click New Assay.

4. 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
     • …

   Note

   The isa.assay.xlsx is not displayed inside ARCitect.

5. Click on the assay’s name (SugarMeasurement) in the file tree to edit the assay metadata in the right panel.

6. 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.

7. Click to save your metadata.

Separate different assay elements

Section titled Separate different assay elements

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.

Add assay data and protocols

Section titled Add assay data and protocols

ARCitect

1. Right-click on the dataset folder and select Import Files.

2. Select the file sugar_result.csv from the demo data and click Open.

3. Right-click on the protocols folder and select Import Files.

4. Select the file sugar_extraction_protocol.md from the demo data and click Open.

5. The files are added to your ARC.

   • Directoryassays

     • DirectorySugarMeasurement

       • Directorydataset

         • sugar_result.csv
       • Directoryprotocols

         • sugar_extraction_protocol.md
       • isa.assay.xlsx
       • README.md
   • …

Isolate the lab processes in an assay

Section titled Isolate the lab processes in an assay

In order to separate the metadata, we can add one annotation table for each isolated process.

ARCitect

1. Click on the assay’s name (SugarMeasurement) in the file tree.

2. At the bottom of the right panel, click on the + right next to the Assay sheet to add one sheet for each lab process.

   

   I add two tables: one for “SugarExtraction” and one for “SugarMeasurement”

3. After adding the tables, right-click on each sheet’s tab to rename them accordingly.

Use templates to describe the lab processes

Section titled Use templates to describe the lab processes

Sugar extraction

Section titled Sugar extraction

We annotate the Sugar extraction process first.

Similar to the study example, we can parameterize the individual process steps, for instance:

• Vortex Mixer 3 seconds
• Temperature 95 degree celsius

Instead of adding each individual building block to the table, we can use a generic template for a sugar extraction.

ARCitect

1. Click on the assay’s name (SugarMeasurement) in the file tree.

2. Select the “SugarExtraction” table added in the previous step.

3. In the New Table! widget, click to Start from an existing template!.

4. Click on Browse database, now all DataPLANT curated templates are shown.

5. To select a template from a different community click .

6. From the Select community dropdown, select “Training”.

7. Click the name of the template Training - Sugar extraction and select.

8. Click Add templates.

9. Select Import Type with Units and Append to active table.

10. You can expand Select Columns to view all building blocks of the template.

    

    This shows me that the template has an Input, Output as well as two Parameter columns: “Vortex Mixer” and “Temperature”

11. Click Import to use the template.

    Input [Sample Name]	Parameter [Vortex Mixer]	Parameter [Temperature]	Output [Sample Name]

12. At the bottom of the table, type 5 in the text field and click + to add 5 rows to your table for a total of 6 since one was added automatically.

13. Transfer the sample names of your study’s Output [Sample Name] to the Input [Sample Name] column.

    Input [Sample Name]	Parameter [Vortex Mixer]	Parameter [Temperature]	Output [Sample Name]
    Cold1_leaf
    Cold2_leaf
    Cold3_leaf
    RT1_leaf
    RT2_leaf
    RT3_leaf

14. Add information of the sugar_extraction_protocol.md into the table, e.g.

    Input [Sample Name]	Parameter [Vortex Mixer]	Parameter [Temperature]	Output [Sample Name]
    Cold1_leaf	3 seconds	95 degree celsius
    Cold2_leaf	3 seconds	95 degree celsius
    Cold3_leaf	3 seconds	95 degree celsius
    RT1_leaf	3 seconds	95 degree celsius
    RT2_leaf	3 seconds	95 degree celsius
    RT3_leaf	3 seconds	95 degree celsius

15. Fill the Output [Sample Name] column:

    • Select the six cells from Input, and copy the sample names (right-click -> Copy)
    • Select the cell below Output [Sample Name] and paste the sample names (right-click -> Paste all)
    • Click Right-click -> Update on a cell below Output [Sample Name] to change the sample names
    • Type “leaf” in the Regex and “sugar-ext” in the Replacement fields
    • Click Submit

    Input [Sample Name]	Parameter [Vortex Mixer]	Parameter [Temperature]	Output [Sample Name]
    Cold1_leaf	3 seconds	95 degree celsius	Cold1_sugar-ext
    Cold2_leaf	3 seconds	95 degree celsius	Cold2_sugar-ext
    Cold3_leaf	3 seconds	95 degree celsius	Cold3_sugar-ext
    RT1_leaf	3 seconds	95 degree celsius	RT1_sugar-ext
    RT2_leaf	3 seconds	95 degree celsius	RT2_sugar-ext
    RT3_leaf	3 seconds	95 degree celsius	RT3_sugar-ext

16. Click to save your metadata.

Sugar measurement

Section titled Sugar measurement

We follow the same steps to fill the Sugar Measurement table.

ARCitect

1. Select the “SugarMeasurement” table.

2. Load the template Training - Sugar measurement

3. Add the Output [Sample Name] values (*_sugar-ext) of the “SugarExtraction” to the Input [Sample name] column

4. Fill the parameter columns

   • Parameter [technical replicate] of 1,2,3,1,2,3
   • Parameter [sample volume] of 10 microliter
   • Parameter [buffer volume] of 190 microliter
   • Parameter [cycle count] of 5

5. Use the File Picker feature to import the results of sugar measurement (sugar_result.csv) into Output [Data]

   Input [Sample Name]	Parameter [technical replicate]	Parameter […]	Output [Data]
   Cold1_sugar-ext	1	…	./assays/SugarMeasurement/dataset/sugar_result.csv
   Cold2_sugar-ext	2	…	./assays/SugarMeasurement/dataset/sugar_result.csv
   Cold3_sugar-ext	3	…	./assays/SugarMeasurement/dataset/sugar_result.csv
   RT1_sugar-ext	1	…	./assays/SugarMeasurement/dataset/sugar_result.csv
   RT2_sugar-ext	2	…	./assays/SugarMeasurement/dataset/sugar_result.csv
   RT3_sugar-ext	3	…	./assays/SugarMeasurement/dataset/sugar_result.csv

6. Click to save your metadata.

Linking samples to data – across studies and assays

Section titled Linking samples to data – across studies and assays

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.

Loading diagram...

Source

flowchart LR
s1[Seeds] --Plant growth--> s2[Leaves] --Sugar Extraction--> s3[Sugar extract] --Sugar Measurement--> sugar_result.csv