This users' manual describes version 2 of the Quality Control Web Application.


The PhenoDCC Quality Control web application allows a user to visualise phenotype data collected from various research institutes, and to identify and discuss possible quality control issues with the data before they are signed-off for further scientific analysis.

Target users

The quality control web application was designed primarily for 1) data managers at the various participating research centres carrying out the phenotyping experiments and producing the data, and 2) for the data wranglers who are responsible for identifying and raising quality control issues with the data. Using this web application, both the data managers and data wranglers can discuss any quality control issues inside the same platform, allowing quicker turn-around time for resolving issues. Furthermore, other users can also see the progress of the data, as they are submitted by the phenotyping centres.

Accessing the web application

The PhenoDCC web application is accessed using a standard web browser, such as Google Chrome, by visiting the appropriate server. Once the application has been loaded, the web app is ready for usage. Depending on the internet connection speed, loading the web application may take a while. While the application is being loaded, you will see the following screen on your browser.

Web application is loading...

Web application is loading...

Once the application has been loaded, you will see the following screen on your browser.

Web application has loaded successfully

Web application has loaded successfully

The overall process

In order to visualise phenotype data, we must specify the context which selects the required data that we wish to analyse. This is referred to as the data context. In the PhenoDCC web application, a data context is defined by the following variables:

  1. Centre The centre that was responsible for experimenting and collecting the phenotype data. This variable is named cid in the data context.

  2. Pipeline The phenotyping pipeline under which the procedures were carried out. This variable is named lid in the data context.

  3. Genotype The genotype that is associated with the mouse specimens on which the experiments were carried out. This variable is named gid in the data context.

  4. Background strain The specific background strain of the selected genotype. This variable is named sid in the data context.

  5. Procedure The type of experimental procedure that was carried out on the selected specimens. This variable is named peid in the data context.

  6. Parameter While carrying out an experimental procedure, various results and observations are recorded using the standard operating protocols (SOP) defined in IMPReSS. Each of these results are recorded under a well defined parameter. This variable is named qeid in the data context.

Once the data context is defined, the PhenoDCC web application will display the required visualisation of the available data, or alert the user if no visualisation could be rendered. In fact, it is possible to start the PhenoDCC web application using a given data context (see Initialising the web application).

Components of the user interface

The user interface for the PhenoDCC web application is divided into several visual components. Each of these corresponds to a clearly defined function. The icons are explained in Understanding the icons section.

Toolbar, centre, genes and strains

Procedures, parameters and specimens

Quality control issues and actions

Visualisation and controls

Visualise phenotype measurements

To visualise phenotype measurements, specify the data context by selecting the following:

  1. Select a centre. This will update the genes/strains panel, and will lists only those genotypes and background strains pertinent to the centre just selected.

  2. Select a pipeline. This will update the genes/strains panel, and will lists only those genotypes and background strains pertinent to the pipeline just selected.

  3. Search for a specific genotype, or background strain. This will filter the list of genotypes and background strains in the genes/strains panel.

  4. Select a background strain from the list. This will update the data context details panel.

  5. We must now select the procedures and parameters, but before we do that, we must first activate the procedures/parameters panel. To do this, click on the Procedures and parameters tab, as shown above.

  6. Select the procedure that we wish to investigate. This will update the list of parameters in the parameters panel.

  7. Select the parameter that we wish to analyse. This completely defines a data context. If there are data available for this context, these will now be displayed in the visualisation panel.

Visualisation controls

Maximise/minimise visualisation

Clicking on the button maximises the visualisation by hiding the Centre, Genes, Strains, Procedures and Parameters panel; and the Specimens and Quality Control Issues panel. This is shown below. If the visualisation is already maximised, the control has no effect.