Overview

Studies integrate many different types of research data, so they often contain datasets of that have passed through different levels of quality control (QC). Dataset QC states allow you to track the extent of quality control that has been performed on each dataset. This facilitates human approval of study data.

LabKey's dataset QC features allow you to mark incoming datasets with the level of quality control executed before incorporation of the dataset into a study. Once datasets are part of a study, the QC markers for individual rows or entire datasets can be changed to recognize subsequent rounds of quality control.

Feature summary for dataset QC:

• The quality control process allows study administrators to define a series of approval and review states for data. These states can be associated with "public" or "nonpublic" settings that define the default visibility of the data.
• Different data approval states (and thus approval pathways) can be defined for data added to a study through different pathways (e.g., assay data copied to a study, data imported via the Pipeline or TSV data inserted directly into a study dataset).
• Reviewers can the filter a data grid by QC State and thus find all data requiring review from a single screen.
• All quality control actions are audited.

Filter datasets by QC state

You can use filtering to review only data rows that are currently in a particular quality control state. This option is available to all users once an admin has set up dataset-level QC and defined QC states.

For example, the following screenshot shows how you would select all rows of data that remain in the "Not Yet Reviewed" QC state.

Change the QC State

You can change the QC state for dataset rows if you have sufficient permission.

• Go to the dataset and select one or more rows using the checkboxes.
• Click QC States > Update state of selected data.
• Choose the New QC State.
• Enter a comment.
• Click Update Status.

Related Topics

• Manage Dataset QC States. Provides setup instructions to help Admins define QC states. Must be completed before users can change QC states.
• Flag Specimens for Quality Control. Specimen QC is simpler but less customizable than dataset QC.
• Validators and Range Checks for Individual Fields. Provides data-type and data-range checks, defined in the assay design.