In the Parameters: Linear regression dialog box, check the box labeled Standard Curve X from Y, because we want our unknown concentrations to be provided. A standard curve is a graph relating a measured quantity (radioactivity, fluorescence, or optical density, for example) to concentration of the substance of interest in "known" samples. You may also want to move the origin to the lower left, a choice on the first tab of the Format Axis dialog. The results can be incorrect when the unknown sample are contaminated with other substances that alter the assay. From the drop-down list at the top of the Add Data Sets to Graph dialog box, select ...Linear regression: Interpolated X values.... Click on Add, then Close. Simply multiply both confidence limits by -1. All Rights Reserved. Calculating "Unknown" Concentrations using a Standard Curve in Prism 3. Set the number of significant digits to 3. The confidence inerval for the X intercept gives you the confidence interval for the concentration of the uknown. During each PCR cycle, the amount of fluorescent signal for each standard in the dilution seies is measured. The confidence inerval for the X intercept gives you the confidence interval for the concentration of the uknown. Choose to format the X column as Numbers and to format the Y column for the number of replicates in your data. Analyze, graph and present your scientific work easily with GraphPad Prism. The independent data is plotted on the x-axis, whereas the dependent data is plotted on the y-axis, on a s… Now, Do you see the quality metrics at the bottom of the screen? Let’s review Slope, Y intercept, and R2.? Prism displays the results on pages called views. Select Interpolated X values (in early Prism releases, this was "Standard curve X from Y"). The X axis is the log of the known standard concentrations. It is very important to prepare the standard dilution series carefully to ensure consistent and accurate results! For our example, choose A single column of values. A line that fits the data points perfectly has an R2 of 1. To add the "unknowns" to the graph: Switch to the Graphs section of your project. But there is a problem with interpolating from a standard curve. That’s it for today. protein standard concentrations in a BCA assay), and the other is the dependent variable which refers to the measured values (e.g. The low-concentration, 5 pg/ul standard will take many more cycles to cross the same threshold – and therefore the Ct will be higher. If you want the "unknowns" represented as spikes projected to the X axis (rather than data points), click on the Change button and select Symbols and Lines. Standard curve results -- Unknowns are represented as spikes on the graph; numerical results are reported as an embedded table. To find "unknown" concentrations using a standard curve, follow these steps: In the Welcome to Prism dialog box, select Create a new project and Work independently. The R2 value measures how well the regression line fits the data points. A standard curve is a graph relating a measured quantity (radioactivity, fluorescence, or optical density, for example) to concentration of the substance of interest in "known" samples. If you have other questions, submit them at thermofisher.com/forensicfocus. Such a curve can be used to determine concentrations of the substance in "unknown" samples. The Y axis is the Ct value of each standard. The illustration includes some formatting changes not discussed here. The Ct values for each dilution of the standard curve are plotted on a graph, and the software generates a regression line that fits the data. The dialog box shows all data and results tables that are represented on the graph. Enter data for the standard curve. Take the absolute value, and that is the concentration of the unknown substance. The Standard Addition Method is a way to bypass this problem. Later, Prism will fit the standard curve and then report the unknown substance concentrations using that curve. The high-concentration, 50 ng/ul standard will cross the detection threshold first, generating a “low” Ct. Simply multiply both confidence limits by -1. Instead you add various known concentrations (including zero) of known substance to a constant amount of the unknown.