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Add assay data

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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.

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Then let’s start with the “Sugar Measurement” assay.

Assay 1: Sugar Measurement

Section titled Assay 1: 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.

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    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
      • …

  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.

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    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

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 reusablity 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.

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    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 on the Add Template button next to Start from an existing template!.

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

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

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

  6. Click Add template to add the columns to your table.

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

  7. 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.

  8. 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

  9. 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_leaf3 seconds95 degree celsius
    Cold2_leaf3 seconds95 degree celsius
    Cold3_leaf3 seconds95 degree celsius
    RT1_leaf3 seconds95 degree celsius
    RT2_leaf3 seconds95 degree celsius
    RT3_leaf3 seconds95 degree celsius

  10. 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_leaf3 seconds95 degree celsiusCold1_sugar-ext
    Cold2_leaf3 seconds95 degree celsiusCold2_sugar-ext
    Cold3_leaf3 seconds95 degree celsiusCold3_sugar-ext
    RT1_leaf3 seconds95 degree celsiusRT1_sugar-ext
    RT2_leaf3 seconds95 degree celsiusRT2_sugar-ext
    RT3_leaf3 seconds95 degree celsiusRT3_sugar-ext

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-ext1…./assays/SugarMeasurement/dataset/sugar_result.csv
    Cold2_sugar-ext2…./assays/SugarMeasurement/dataset/sugar_result.csv
    Cold3_sugar-ext3…./assays/SugarMeasurement/dataset/sugar_result.csv
    RT1_sugar-ext1…./assays/SugarMeasurement/dataset/sugar_result.csv
    RT2_sugar-ext2…./assays/SugarMeasurement/dataset/sugar_result.csv
    RT3_sugar-ext3…./assays/SugarMeasurement/dataset/sugar_result.csv

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 consiley link the samples through the different lab processes in studies and assays to the data produced from those samples.

Seeds —Plant growth⇾ Leaves —Sugar Extraction⇾ Sugar extract —Sugar Measurement⇾ sugar_result.csv

Assay 2: Proteomics Assays

Section titled Assay 2: Proteomics Assays
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Alright, this all makes sense. However, it seems a bit tedious, if I want to achieve this in detail for more complex assays.

And besides, I’m honestly not an expert of proteomics data and I am not sure I can fill out all information about my proteomics assay.

Apply standard procedures (SOPs) to sample records

Section titled Apply standard procedures (SOPs) to sample records

Follow the same steps as before to …

ARCitect

… add two assays and sort the available demo data:

  1. Create two assays called Proteomics_MS and Proteomics_DataAnalysis.
  2. Import the assay files and folders from the demo data into the two assays in your ARC. Use the Import Files and Import Directories functions accordingly:
    demo data ------->ARC
    MS_Raw/Proteomics_MS/dataset/
    AssayTemplate_Proteomics_MS.jsonProteomics_MS/protocols/
    combined_protein.fasta and MSFraggerOutput/combined_protein.csvProteomics_DataAnalysis/dataset/
    AssayTemplate_Proteomics_DataAnalysis.jsonProteomics_DataAnalysis/protocols/

Load the data annotation into the respective annotation tables

  1. Create a new annotation table for the assay Proteomics_MS.
  2. In the bottom-right corner click < to open a panel on the right.
  3. On top of the panel, navigate to the templates tab.
  4. In the “Add template(s) from file” section, select ARCtrl and click Upload protocol.
  5. Navigate to and select the file AssayTemplate_Proteomics_MS.json and click open.
    • Select the “Import Type” ..With Values
    • Check the Import boxes
    • Click Submit

Repeat the same for the Proteomics_DataAnalysis assay, by importing the metadata from AssayTemplate_Proteomics_DataAnalysis.json.