Multicrystal

• Create a New Multicrystal Project
• List Multicrystal Projects
• The Scaling Tool
  • Control Bar
  • Filter Panel
  • Unit Cell Distribution
  • Data Coverage
  • Override Section (Advanced)
  • Dataset Dispay Table

The Multicrystal tab provides tools for combining diffraction data from multiple crystals into a single merged dataset. The scaling tool displays numerous parameters and filters for excluding outlier datasets.

Create a New Project

The Create New tab (Fig. 1) allows you to create a multicrystal project from two different sources:

• Datasets from Directory — browse to a main directory that contains all the processed dataset subdirectories. The system scans sub and sub-sub directories for autoProc output and reports how many datasets were found.
• Datasets from Spreadsheet(s) — select datasets from your uploaded spreadsheets. You can add complete spreadsheets or select particular samples from each spreadsheet.

Once the datasets have been selected, enter a project name and click Create.

Note: projects are automatically created for the BluIce multicrystal data collection mode and will appear in the Projects list.

List Projects

This tab (Fig. 2) provides a list of all your multicrystal projects and associated information:

• Last Modified — last time modified
• Project Name — click to open the project in the Scaling Tool
• Project ID
• Total Datasets — number of datasets in the project
• Scaling Jobs — number of scaling jobs created
• Created — creation date
• Options — available project actions

Use the Options dropdown to open projects in the Scaling Tool or to delete them.

The Scaling Tool

The Scaling Tool is the main interactive interface for configuring and running aP_scale jobs (Fig. 3). It has several sections: a main control bar, a panel for filtering out datasets, unit cell distribution, data coverage, an advanced options section and a table listing each dataset and associated processing parameters.

Control Bar

The main control bar (Fig. 4) is used to select multicrystal projects, create new scaling runs, and submit scaling jobs to the compute cluster.

Projects are selected from the dropdown menu and Scaling Jobs are listed in the menu. The status field provides the Status of the scaling job (New / Queued / Scaling / Scaled / Failed) and the number of datasets associated with the scaling job is displayed and updates if selected datasets are removed or added. Click Scale to submit scaling jobs to queue them for the compute servers. Click on the See Results button to view the scaling results and merging statistics in the Processing Results tab once the job has completed.

Filter Panel

The filter panel (Fig. 5) is used to apply quality-based filters to exclude poor quality datasets.

Each parameter shows the minimum, average and maximum values for the selected datasets. Red indicates the value is outside the "nominal" limits. The Min and Max arrows can be used to manually narrow or expand a range or a value can be entered manually.

Note - depending on your window size you may have to hover over the panel to see the horizontal slide bar to access all available output parameters.

Scaling output parameters will also be available for filtering after the first scaling job has completed. The Use Nominal Filters button applies a generous set of limits and the Remove All Filters button will remove all filtering.

Integration Results that can be used for filtering datasets:

• Space Group
• Unit Cell Parameters
• Phi Range
• I/σ(I) estimate
• Mosaicity
• Resolution
• Reflections

Individual Scaling Results that can be used for filtering datasets:

• R-rank — R value in comparison to the merged dataset
• CC-rank — correlation coefficient in comparison to the merged dataset
• Scale Factor — scaling factor compared to the reference dataset (Scale Factor is set to 1 for reference)
• B Factor — B-factor compared to the reference dataset (reference value set to 0)

Unit Cell Distribution

The Unit Cell Distribution panel (Fig. 6) provides an interactive histogram for each unit cell parameter (a, b, c, α, β, γ) that can be used for excluding datasets. Drag the min/max sliders to exclude outliers and narrow the range. Click "+" icon to expand the view. Nominal definitions indicate the selected range is isomorphous, moderate or nonisomorphous.

Data Coverage

The Data Coverage panel (Fig. 7) provides a 3D visualization of the estimated reciprocal space coverage for the selected datasets. The minimum multiplicity level can be set (1+, 2+, 5+, etc.) and the sphere can be viewed along or rotated about the reciprocal axes (a*, b*, c*) to inspect coverage.

In addition, the range of different crystal orientations is displayed (Random, Moderate and Clustered). The percentage of unique reflections is also displayed.

Override Panel (Advanced)

The Override panel (Fig. 8) allows one to override specific parameters including adding any valid keyword to the aP_scale run.

Parameters that can be overriden:

Dataset Display Table

The dataset display table (Fig. 9) shows the results of the individual dataset integration runs as well as the results of the scaling runs.

The Dataset display table lists every dataset with Integration Results:

After the first scaling run, Individual Scaling Results are also displayed:

Values that are highlighted in red are outside the "nominal" limits. Manually select or deselect datasets for scaling using the checkboxes on the left side. Use the green box in the Status column header to remove datasets from the display that had produced an error during integration.