Luminex 100 IS Version 2.3 - Manual (Page 118)

Luminex 100 IS User Manual Version 2.3
x
MAP Technology
5 - 76 PN 89-00002-00-072 Rev. C
Export a Lot from
an Existing
Template
Use this procedure to export a lot for use on another instrument.
Depending on the template and its associated products, you may
have standards, controls, or both. Standards and controls can be
grouped into the same lot number.
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To export a lot from an existing template:
1. On the Home tab, click New Lot. The Open Template dialog
box opens.
2. Double-click the template containing the lot to export. The
Update Lot Information dialog box opens. See Figure 5-45.
3. Click Export Lot. A standard or control confirmation dialog box
opens verifying that you want to export the current lot for the
standard or control.
If you want to export the lot information for the standards, click
Yes. If you only want to export the lot controls, click No. A
second dialog box opens to verify if you want to export the
current control lot, or current lot for a control.
After responding to the confirmation dialog boxes, regarding
standards or controls, a Save As dialog box opens.
4. Click the drop-down arrow to select the Save in: location where
you want to save the lot information.
5. Enter the lot file name into the File Name: box.
6. Click Save. The system saves the lot.
Analyzing Batches and
Multi-Batches
You can analyze an acquired batch using the analysis features of
Qualitative and Quantitative algorithms. The algorithm is determined
by the kit manufacturer during template creation.
A Qualitative analysis determines results as either positive or
negative, reactive or non-reactive, and so on. The system is flexible
in defining custom result ranges, such as negative, low positive, high
positive, and so on. Refer to the Luminex Developer Workbench
Guide Version 2.3 for additional information. All determinations are
based on a single standard.
A Quantitative analysis determines the sample concentrations from
standard curves using regression methods, such as 4P or 5P logistic
curve fitting.