Setting Quality Control Flags
A key reason to track samples is to monitor their quality. In Clarity LIMS, samples are flagged with a check mark to indicate good quality (QC Pass) or an X to indicate poor quality (QC Fail).
There are many ways to determine quality, including concentration and DNA 260/280 light absorbance measurements. This example uses a tab-separated value (TSV) results file from a Thermo NanoDrop Spectrophotometer to:
Record concentration and 260/280 measurements, and;
Set quality flags in the LIMS.
In this example, once the script is installed, the user simply runs and records a step and imports the results file. The EPP / automation script does the rest of the work, by reading the file, capturing the measurements in Clarity LIMS, and setting the QC flags.
QC file formats
As spectrophotometers are used for many measurements, within many lab protocols, file formats can vary depending on the instrument software settings. Check your instruments for specific file formats and use the example below to get familiar with the QC example scripts.
User Interaction
The user selects samples and runs the QC Example step.
In the Operations Interface (LIMS v4 & earlier), the user sets the required minimum concentration and/or 260/280 lower and upper bounds.
The QC Example process creates an output artifact (shared ResultsFile) called QC Data File. This file is shown in the Sample Genealogy and Outputs panes. The "!" icon indicates that this entry is a placeholder for a file.
A TSV file is created by the NanoDrop spectrophotometer. The specific file used in this example is shown below.
After the TSV file is imported and attached to the QC Example process in Clarity LIMS, a second script is automatically called with EPP. This second EPP script is part of a second process, called QC Example(file handling). The file attachment event triggers the second EPP script. You can see the process in the Sample Genealogy pane:
The example uses the TSV file Sample ID value to locate the plate and well location to which the QC flag is to be applied. In the example file shown in Step 1: The container is QCExamplePlate.
Automation/EPP can be used to process files when they are attached to the LIMS. Using file attachment triggers is sometimes called data analysis pipelining. Basically, a series of analysis steps across a chain of processes is triggered from one file attachment.
Download the zip file to the server; on a non-production server use the gls user account.
Unzip the file to the following directory: /opt/gls/clarity/Applications. The contents of the zip file will be installed within that directory, to CookBook/NanoDropQC/.
Next, unzip the config-slicer-<version>-deployment-bundle.zip in /opt/gls/clarity/Applications/CookBook/NanoDropQC/. Replace <version> with the version number of the included config-slicer.
Installation validation
To confirm that the example is correctly installed, follow the steps below to simulate the recording of QC information by a user in the lab:
Start the Clarity LIMS Operations Interface client.
Create a project, and submit a 96 well plate named QCExamplePlate full of samples
Select the samples and run the QC Example process.
Example modifications
You can modify the example script to suit your lab's QC experimental methods and calculations. For example, you may want to consider phenotypic information or extra sample data recorded in the LIMS. Two modifications to the example are described below.
Recording QC measurements on sample inputs instead of file outputs
The example script writes the measurements into user-defined fields (UDFs) associated with outputs of the process. This allows multiple measurements to be recorded for one sample, by running the process multiple times. Each time the process is run on an input sample, a new process with new output results is recorded in the LIMS.
You may instead want to write the measurements into UDFs associated with the input samples. For example, you may want to keep the data records simple: the greater the number of outputs recorded in the LIMS, the more confusing it becomes for the user to upload files and navigate results. Setting the fields on the inputs provides a single 'golden' value.
To change the configuration and script to set QC flags and field values on inputs:
Change the code in NanoDrop.groovy so that UDFs are set on inputs instead of outputs. That is, replace this line:
with the following:
Since you are no longer changing the outputs, you can comment or delete the line where the output is saved:
Run the QC Example (preparation) process that was included in the configuration package you imported into your system.
Using additional information stored in sample fields to set the QC flags
Most labs use multiple factors to determine sample QC flags. These factors might be associated with the submitted sample, multiple instrument measurements, or even the type of project or sample.
To demonstrate how easy it is to aggregate multiple factors into the QC flag logic, a boolean field called Human is added to the sample configuration. The script logic is modified to only set flags for human samples.
To change the configuration and script to check for human samples:
Change the code in NanoDrop.groovy (where we loop through the input/output pairs adjusting QC flags/updating UDFs), so that we first ensure we are dealing with a Human sample.
To do this, change the loop at the end of the script from this:
to this:
Configure a checkbox UDF on Sample (this was done for you when you imported the configuration package provided in this application example).
Assumptions & notes
Clarity LIMS v1 or later (API v2 r14)
Groovy 1.7.4 or later (expected location: /opt/gls/groovy/current/)
All prerequisites are preloaded if you install on a non-production server.
file-qc-2.0-bundle.zip:
