Why Use Our qPCR Arrays?

CONVENIENT. Save valuable research time with carefully researched, preselected gene panels and validated primers and probes.
ACCURATE. Detect only specific amplification products with fluorogenic-labeled probe technology.
REPRODUCIBLE. Reliable and consistent performance under standard and fast cycling conditions with qPCR Master Mix containing Taq DNA polymerase.

qPCR Array Products
qPCR Master Mix

Want to see how this qPCR analysis tool works but don't yet have your own data? Explore the features of this tool using replicate sample data from the Human Pluripotent Stem Cell Trilineage Differentiation qPCR Array (Catalog #07515) below.

Input Data Table

Zoomable Plot (double-click to reset)


Output Table

Orange highlights denote significantly upregulated genes


Amalgamated Expression Values by Gene Classification


Summary of Expression Level

Orange highlights denote significantly upregulated gene categories


General Instructions

To get started, select your qPCR array product type, as well as the number of replicates for both control and test samples from the "Input Data Table" tab. Note, any statistics generated by this program will be inaccurate when less than 3 replicates are used. Copy and paste Ct data from the qPCR instrument into the columns in the table. If you wish to change program defaults (a maximum Ct value of 38, the type of statistical test used, and whether you have a positive control), select the "Toggle Advanced Options" checkbox. A selection of housekeeping genes are included with which to normalize the data to. If you are running this program in Custom mode, at least one of the genes pasted into the table must match the name of one of these housekeeping genes.

If a mistake is made when loading the plate, and you wish to omit a sample, simply place a 0 in the cell in which the sample was incorrectly loaded. This cell will be ignored in downstream analysis, and a warning message will be printed outlining which gene(s) have less replicates than the rest.

As standard, a T-test (unpaired, two-tailed test with equal variance) is used for all statistical analysis. However, advanced options include a Moderated T-test which has been found to be a more accurate statistical measure (Smyth 2005), or a Wilcox (Mann-Whitney U) test for non-parametric data. In all cases, p-values are corrected for multiple comparisons by the Benjamini-Hochberg procedure.

Our dedicated team of Product and Scientific Support specialists provides support to scientists around the globe, from our locations in North America, Europe, and Asia. To connect with one of our Product and Scientific Support specialists please email us at techsupport@stemcell.com

Plotting Parameters

Once data has been inserted into the "Input Data Table" tab, the "Analysis Plot" tab will populate with a graph. Select either barplot or heatmap from the dropdown menu depending on preferred plot type. By default, plots are colored by the functional class of the genes and are shown on a log-transformed scale. These parameters can be toggled, together with standard deviation bars, asterisks denoting significance using the checkboxes and the ability to order the genes by expression level rather than plate-order. Plots can be zoomed by clicking and dragging with the mouse on these plots. The camera button on the top right of the plot can be used to save an image, or the plot can be downloaded using the download button.

Output Table

The "Output Table" tab shows an interactive table of all important metrics for each gene that can be downloaded either as a .csv or a .xlsx file by clicking the download button. Sample and Control Ct Values are expressed as 2^-deltaCt. This value is the mean of the replicates and is calculated by subtracting the housekeeping gene Ct values from the test or control Ct values, then taking 2 to the negative exponent of this value. The fold change represents the change in expression levels, with downregulation in the test samples expressed as a fraction below 1, which allows these data to be plotted on a log scale for the analysis plots.

The "Transcript Quality" column on the output table gives an estimation of the accuracy of the data based on several criteria. A "Good" is given when the Ct values are in a range that can accurately be called in both Control and Test conditions. A "Moderate" comment is given when the Ct value for this gene is relatively high (> 30) in the control sample, and reasonably low in the test sample (< 30) or vice versa. The interpretation of these data are that since the gene expression in one of the samples is relatively low (and thus less-reliable), the actual fold-change value is at least as large as the calculated and reported fold-change result. This fold-change result may also have greater variance in conjunction with a p-value less than 0.05; therefore, it is important to have a sufficient number of biological replicates to validate the result for this gene. A "Weak" comment is given when the Ct value is relatively high (> 30), meaning that its relative expression level is low, in both control and test samples, and the p-value for the fold-change is either unavailable or relatively high (p > 0.05). This fold-change result may also have greater variations; therefore, it is important to have a sufficient number of biological replicates to validate the result for this gene. An "Unreliable" comment is given if the Ct value of a gene is either not determined or greater than the defined cut-off (default 38) in both samples, meaning that its expression was undetected, making this fold-change result erroneous and uninterpretable.

Global Data

The "Global Data" tab amalgamates all the genes for each particular functional class into a boxplot, showing the overall expression levels of genes present in each group. This allows for quick and easy cell characterization for the test samples. Statistical analysis is performed with respect to controls (if present) to show enrichment of particular gene classes.

qPCR Array Plate Configuration

Annotated List of Genes on qPCR Array