How Good Is Your Curve?

• The high resolution standard curve graph on the left depicts the relationship between responses and doses with the most accurate and robust 5PL, 4PL, and linear regression curve fitting algorithms in the industry.

• With the software’s accurate weighting (see Tech Note: Curve Weighting), the squared residual errors (red bars) between the observed responses and predicted responses off the curve should be low for each dilution, as shown in middle graph. A high residual² indicates a bad dilution.

• The graph on the right shows the concentration errors vs. dose of the standard curve in red, with the unknown concentration errors plotted as blue dots. The LLOQ, ULOQ and the reportable range you set for this test method are plotted in green. See the Tech Note: LOQs, LODs on the software’s precision error profile method.

How Good Is Your Assay?

• The current standard response replicates are red dots that are within or are outside the green confidence limits of the standard dilution responses determined from previous assays.

• A line from each control response and dose in the assay is plotted against their respective confidence limits. The response and dose lines are green when inside their confidence limits, or red when outside their confidence limits.

Standard Dilution Response Limits Established For Your Assays

• The graph on the left shows the responses from each of the standard dilutions in your pooled assays.

• The graph in the middle shows the confidence limits for each standard dilution using the data from your pooled assay responses, after filtering out any outliers.

• The graph on the right shows these confidence limits plotted with the standard dilution responses (red dots) of your assay. From this graph, you can see how the assay is behaving compared to the expected behavior determined by your previous assays.

• The development tools in STATLIA MATRIX can help you determine optimal dilution doses and other factors to make your quantitation test more stable and precise.

Limits Established for Control Doses and Responses

• The response and computed dose of each control from your previously run assays is plotted in the graph on the left in the Performance Analysis report. Confidence limits are computed for the response and dose of each control from these data points, after filtering out any outliers.

• In the graph on the right, each control response and dose is plotted as a line against its confidence limits in an assay report. The response and dose lines are green when inside their limits, or red when outside. When the response and the dose are both outside their limits, the control itself is bad.

Set Reportable Range to Match Unknown Population

• The graph on the left shows the standard curve concentration precision errors from a pool of your previous assays. This graph can be used to establish a reliable reportable range (green horizontal bar) for this test. See the Tech Note: LOQs, LODs on the software’s precision error profile method, or the manuscript: The Five Parameter Logistic: A Characterization And Comparison With The Four Parameter Logistic.

• The middle graph shows a distribution of concentration precision errors from the unknowns of a pool of your previously run assays. This graph shows how well the reportable range (green horizontal bar) matches the unknown population.

• The distribution of unknown concentrations from your pooled assays shows the behavior of your test population and can be used to establish a reference range for that population.