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

Add a new assay

ARCitect

1. Click on the plus icon add next to storage 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.

ARCitect-GX

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

2. Enter an identifier for the New Assay.

   

   SugarMeasurement

3. Click Create Assay.

4. ARCitect-GX 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-GX by clicking on SugarMeasurement as shown below.

   • Directoryassays

     • DirectorySugarMeasurement

       • Directorydataset

         • …
       • Directoryprotocols

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

5. Click on the assay’s name (SugarMeasurement) in the file tree to open the folder

6. Click on the isa.assay.xlsx workbook to edit the assay metadata in the right panel.

7. 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.

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

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
   • …

ARCitect-GX

1. Right-click on the SugarMeasurement folder and select Open Folder Location.
2. Move the demo data files:

   • sugar_result.csv into dataset

   • sugar_extraction_protocol.md into protocols

     • Directoryassays

       • DirectorySugarMeasurement

         • Directorydataset

           • sugar_result.csv
         • Directoryprotocols

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

Isolate the lab processes in an assay

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

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

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.

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 with template!. This will show you all DataPLANT curated templates.

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

5. From the dropdown, select “Training” and deselect “DataPLANT”.

6. Click on the template Training - Sugar extraction.

7. Click Import Templates.

8. Configure Import Type to ..With Units and SugarExtraction to Append to active table.

9. You can expand Preview Selected 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”

10. Click Submit to use the template.

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

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

12. 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

    Note

    Select multiple cells by clicking once on the first and the last cell while holding the Shift key. You can copy and paste multiple cells by right-clicking on the selected cells.

13. 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

14. Fill the Output [Sample Name] column:

    • Select the six cells from Input, and copy the sample names (right-click -> Copy)
    • Select the cells below Output [Sample Name] and paste the sample names (right-click -> Paste)
    • Right-click a cell in the column Output [Sample Name]. Then select Edit and Update Rows in the opened field to update all rows at once.
    • 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

Sugar measurement

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

1. Select the “SugarMeasurement” table.

2. Click Utilize prior output and Import selected output column to use the (*_sugar-ext) values of the “SugarExtraction” table.

3. Click on the button in the top bar and import the template Training - Sugar measurement, following the same steps as before. this will not replace the existing input 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

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.

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Source

flowchart TD
classDef studyStyle fill:#dae7c1,rx:.4em,ry:.4em,color:#2d3e50,stroke:#2d3e50,font-weight:bold;
classDef assayStyle fill:#ffe080,rx:.4em,ry:.4em,color:#2d3e50,stroke:#2d3e50,font-weight:bold;
classDef processStyle fill:#E08F9C,rx:.4em,ry:.4em,color:#2d3e50,stroke:#2d3e50,font-weight:normal;
classDef sampleStyle fill:#FEFEFE,rx:.4em,ry:.4em,color:#2d3e50,stroke:#2d3e50,font-weight:normal;
classDef dataStyle fill:#FEFEFE,rx:.4em,ry:.4em,color:#2d3e50,stroke:#2d3e50,font-weight:normal;
subgraph study1["Study:AthalianaColdStress"]
    s1[Plants] ---p1[Plant-growth]--> s2[Leaves]
end
subgraph assay1[Assay1:SugarMeasurement]
    s2 ---p2[SugarExtraction]--> s3[Sugar extract]
    s3 ---p3[SugarMeasurement]--> d1@{ shape: doc, label: sugar_result.csv}
end
class study1 studyStyle;
class assay1 assayStyle;
class p1,p2,p3 processStyle;
class s1,s2,s3 sampleStyle;
class d1 dataStyle;