Need help?
See the 'Instructions' tab for details on how to use this tool, for information on plate configuration or to view a list of annotated genes. For additional help, click on the 'Interactive Walkthrough' button on the left-hand side. For any questions, please contact techsupport@stemcell.com .Note: This application will disconnect from the server after 15 minutes of inactivity.
384-Well Plate Layout Options
Chromosomal regions
Input data table
Need help?
See the 'Instructions' tab for details on how to use this tool, for information on plate configuration or to view a list of annotated genes. For additional help, click on the 'Interactive Walkthrough' button below. For any questions, please contact techsupport@stemcell.comSummary of Detected Abnormalities
Summary Table of All Samples
Need help?
See the 'Instructions' tab for details on how to use this tool, for information on plate configuration or to view a list of annotated genes. For additional help, click on the 'Interactive Walkthrough' button below. For any questions, please contact techsupport@stemcell.comGraph Showing Copy Number of All Samples for Each Locus
Graph Showing Copy Number of All Loci for Each Sample
Graph Showing Copy Number of All Samples and Loci
Loading...
Need help?
See the 'Instructions' tab for details on how to use this tool, for information on plate configuration or to view a list of annotated genes. For additional help, click on the 'Interactive Walkthrough' button below. For any questions, please contact techsupport@stemcell.comAnalysis Tables for Samples
Loading...
1. Instructional Video
This video will guide you through the protocol for analyzing genomic DNA samples using the
hPSC Genetic Analysis Kit by providing step-by-step instructions for preparing the
hPSC Genetic Analysis reagents, setting up the qPCR reaction, pipetting mixtures into a qPCR plate,
and analysis of results using the hPSC Genetic Analysis Application.
2. Introduction
The hPSC Genetic Analysis Kit contains primer/probe mixes to
detect the majority of karyotypic
abnormalities reported in human embryonic stem (ES) cells and induced pluripotent stem (iPS) cells.
This qPCR-based kit enables the genetic screening of multiple human ES and iPS cell lines in a rapid
and cost-effective manner, and contains enough material to analyze 20 individual samples in triplicate.
The target regions provided in the kit account for approximately 75 % of all abnormalities observed by cytogenetics, and includes a frequently duplicated region on chr20q that is commonly undetected by classical G-banding methods.
The target regions provided in the kit account for approximately 75 % of all abnormalities observed by cytogenetics, and includes a frequently duplicated region on chr20q that is commonly undetected by classical G-banding methods.
It is important to note that while this kit will detect the most commonly observed abnormalities in hPSC cultures,
it is not intended to be a substitute for karyotyping. The other approximately 25 % of abnormalities observed in hPSCs
are uncommon between cultures and these regions are not covered by this kit.
Furthermore, the detection limit for the proportion
of cells in culture that harbor the abnormality is dependent on the number of replicates used,
and the variability between them.
The detection limit is determined within this application through a power calculation, and the kit will typically
identify an abnormality when it is present in approximately 20-30 % of the culture.
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
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
3. Preparing Your Experiment
For detailed instructions on preparing and running your samples, please refer to the
Product Information Sheet located on the
hPSC Genetic Analysis Kit product page
(link will open a new window).
Caution:
• It is imperative that the protocol is followed carefully to ensure that the data generated are of a high enough quality to make accurate copy number calls. Vigorous vortexing of reagents and accurate pipetting techniques will improve the analysis considerably. It is recommended that only one to two samples are initially tested until the user becomes familiar with the protocol and the variability between replicates is minimal.
4. General Instructions For This Application
By using this program you are agreeing to, and abiding by our terms of service.
This application is designed to be a user-friendly tool for the rapid detection of abnormalities
within hPSC cultures. While there are a number of more advanced data analysis options,
this program will identify copy-number abnormalities
and generate easy-to-interpret graphs in its default setting.
The application consists of four main tabs: Input Data Table, Results Summary, Analysis Plots, and Output Table, together with the Instructions tab you are currently viewing. The left-hand side panel gives you the opportunity to configure the application to your experimental set up. The following sections will help to navigate through each of the tabs. Note: An 'Interactive Walkthrough' button is available at the top of each tab, and clicking this button will launch an interactive, step-by-step guide to using this program.
The application consists of four main tabs: Input Data Table, Results Summary, Analysis Plots, and Output Table, together with the Instructions tab you are currently viewing. The left-hand side panel gives you the opportunity to configure the application to your experimental set up. The following sections will help to navigate through each of the tabs. Note: An 'Interactive Walkthrough' button is available at the top of each tab, and clicking this button will launch an interactive, step-by-step guide to using this program.
i. Input Data Table Tab
The 'Input Data Table' tab is the location where you will enter your Ct values from your qPCR machine.
From the left-hand side panel you can select the number of replicates you have for both your control and test samples,
and to specify the number of test samples you are running.
Caution:
• Statistics generated by this program will be inaccurate when fewer than 3 replicates are used.
Using a Suggested Plate Layout
If you have used one of the suggested layouts given in the hPSC Genetic Analysis Kit Product Information Sheet, you can click the 'Use Suggested Plate Layout' button to render a representative plate layout. The 'Simple Plate Layout' allows up to 7 test samples and the control sample, while the 'Maximal Sample Layout' allows up to 9 samples.
If you have used one of the suggested layouts given in the hPSC Genetic Analysis Kit Product Information Sheet, you can click the 'Use Suggested Plate Layout' button to render a representative plate layout. The 'Simple Plate Layout' allows up to 7 test samples and the control sample, while the 'Maximal Sample Layout' allows up to 9 samples.
The used wells will be highlighted in orange and
grey, and will change depending on how many samples are selected. Beneath the layout is a table with a list of
chromosomal regions. The chromosomal regions may be rearranged to align with the order in which the locations were
loaded on the plate, or regions may be deleted if they are not run with the kit. This will alter the representative
plate layout. To return the regions to the default order, press the 'reset' button.
The table consists of one column where you can input Ct values directly from your qPCR data.
Caution:
• The order of the 'Sample' and 'Genes' columns of the table will match the representative plate layout. Care should be taken to ensure that the plate layout is identical to the order in which the experimental plate was loaded.
• Data should be pasted using 'Ctrl' (or 'Command', if using a Mac) and 'V' keys; right clicking with a mouse does not currently give the option to paste in data.
• If mistakes were made when loading the plate and you wish to remove any points/replicates in your data, input a zero into the relevant cell of the table and this replicate will be ignored in the subsequent analysis.
Finally, the left hand side panel has an option to give each sample a
unique name and specify the sex of the cells.
The latter is important so as to differentiate between copy number changes from abnormalities and allosome inheritance
for the X chromosome. Once these data have been pasted in, navigating to any of the other tabs will run the analysis
Using Your Own Plate Layout
If you are not using a suggested plate layout, then data must be modified into table format before pasting into the application. The input data table has the samples set as columns, and the chromosomal locations as rows. The number of control and test replicates can be adjusted by changing the values in the left hand side panel, and altering these will resize the table accordingly. The order of the chromosomal regions can be changed by dragging each region up or down, and locations that are not being run can be deleted from the list. To return the order of chromosomal locations to its default, press the 'Reset' button. It is recommended to paste your raw Ct values into your preferred spreadsheet application and rearrange the data to fit the dimensions of the table before pasting them in. The left hand side panel also has an option to give each sample a unique name and specify the sex of the cells. The latter is important so as to differentiate between copy number changes from abnormalities and allosome inheritance for the X chromosome. The tables allow a maximum of 15 samples to be run in a single experiment, and the application will automatically crop out empty samples. Once these data have been pasted in, navigating to any of the other tabs will run the analysis
Using Your Own Plate Layout
If you are not using a suggested plate layout, then data must be modified into table format before pasting into the application. The input data table has the samples set as columns, and the chromosomal locations as rows. The number of control and test replicates can be adjusted by changing the values in the left hand side panel, and altering these will resize the table accordingly. The order of the chromosomal regions can be changed by dragging each region up or down, and locations that are not being run can be deleted from the list. To return the order of chromosomal locations to its default, press the 'Reset' button. It is recommended to paste your raw Ct values into your preferred spreadsheet application and rearrange the data to fit the dimensions of the table before pasting them in. The left hand side panel also has an option to give each sample a unique name and specify the sex of the cells. The latter is important so as to differentiate between copy number changes from abnormalities and allosome inheritance for the X chromosome. The tables allow a maximum of 15 samples to be run in a single experiment, and the application will automatically crop out empty samples. Once these data have been pasted in, navigating to any of the other tabs will run the analysis
Caution:
• Data should be pasted using 'Ctrl' (or 'Command', if using a Mac) and 'V' keys; right clicking with a mouse does not currently give the option to paste in data.
• If mistakes were made when loading the plate and you wish to remove any points/replicates in your data, input a zero into the relevant cell of the table and this replicate will be ignored in the subsequent analysis.
ii. Results Summary Tab
Once data has been inserted into the 'Input Data Table'
tab, the 'Results Summary'
tab will show a high-level summary table of your data alerting you to any duplications or deletions
that are detected. The abnormalities are given a score, based on a statistical model that
incorporates a variety of parameters to give confident calls.
In addition to identifying normal
and abnormal copy numbers, any regions that have some evidence for abnormalities, but do not meet
the calling threshold are highlighted as regions to investigate further. Any regions that lack
the statistical power to make any call are also described.
Caution:
• The degree of variability between replicates is an important factor in the statistical determination of copy number differences. As such, a high inter-replicate variability from insufficiently mixing reagents and pipetting accurately has the potential to make accurate calling impossible across the entire experiment.
For a visual representation of these data you can download
a report using the 'Download Summary Report'
button below the table. This report includes the table, together with a heatmap of abnormality calls,
descriptive results and a graphical representation of the data. The type of graphical representation
included in the report is dependent on the graphical parameters set in the 'Analysis Plots' tab (see below).
The default setting will generate a bar chart with standard deviation bars.
iii. Analysis Plots Tab
Navigating to this tab will render a graph of your data. By default, the 'Plot By Location' option
is selected, and there will be one graph for each locus that is run. If you run the full panel of
regions, nine plots will render with the samples on the x-axis, and the plot for the control locus, chr4,
is shaded for quick identification. Changing the 'Plot By' value to 'Sample' (in the left-hand panel)
will render plots for
each sample you have run, with the x-axis representing the different loci and the control sample shaded for
quick identification. By selecting 'Neither', a single plot is generated with the x-axis representing both
sample and loci.
The plots are interactive, with the option to zoom in (double clicking will reset the scales), and get further information by hovering the cursor over any of the data. There are four plot types that can be selected, and each has their own options to configure the samples.
The plots are interactive, with the option to zoom in (double clicking will reset the scales), and get further information by hovering the cursor over any of the data. There are four plot types that can be selected, and each has their own options to configure the samples.
In all cases, plots can be saved either by clicking on the camera icon in the top
right corner of the plot, or by pressing the 'Download plot' button at the top left. The plotting types and
options associated with them are outlined below.
1. Bar plot
The bar plot represents replicate data as bars with error values. The copy number is represented by the y-axis, and one, two and three copies are denoted by thick lines. There are two main graphical parameters that can be changed with these plots. The first is a toggle button that will remove outliers from the analysis. Outliers are defined as any replicates whose difference from mean exceed three standard deviations. For more details about the calculations used in this application, see the Statistics section. The second graphical parameter is whether to draw the error bars. These can be hidden with the toggle button, or be displayed as either the standard deviation (default), standard error of mean, or the range of replicates.
2. Scatter Plot
The scatter plot displays each replicate as a single point, with the mean values denoted as red lines. All points are plotted as circles except for outliers, which are plotted as triangles. The only option available for these plots is to remove the outliers. This option provides a good overview for inspecting individual replicates and is recommended if you have a high number of variability and/or outliers in your samples.
3. Boxplot
The boxplot option creates a 'box and whisker' diagram. The box represents the interquartile range of the replicates, with 75th and 25th percentiles at the top and bottom respectively. The horizontal line within the box represents the median value. The vertical 'whiskers' represent the maximum and minimum values. These plots are recommended when multiple replicates (>5) are used, as it represents a good standardized method for displaying the distribution.
4. Heatmap
The heatmap option will plot the samples across the x-axis and the regions across the y-axis, with the color in each cell representing the copy number. Here, a diploid region will be colored in yellow, while duplications and deletions will be shown in varying shades of green and red respectively. Hovering the cursor over any box will display additional information and the exact copy number. There are three adjustable parameters specific for these plots: 'Cluster by Sample', 'Plot as replicates', and 'Display values on heatmap'. 'Cluster by Sample' will perform a hierarchical clustering of the samples, rearranging them such that the samples with the most-similar abnormalities will cluster together. A dendrogram is displayed above the plot, with the branch height reflective of the degree of similarity. The 'Plot as Replicates' toggle allows all the individual replicate wells to be plotted, rather than their mean. This can be useful in conjunction with the 'Cluster by Sample' option to ensure that your replicates are closer to each other than they are to other samples. Finally, the 'Display values on heatmap' option will overlay the copy number values on top of the heatmap for quick reference.
1. Bar plot
The bar plot represents replicate data as bars with error values. The copy number is represented by the y-axis, and one, two and three copies are denoted by thick lines. There are two main graphical parameters that can be changed with these plots. The first is a toggle button that will remove outliers from the analysis. Outliers are defined as any replicates whose difference from mean exceed three standard deviations. For more details about the calculations used in this application, see the Statistics section. The second graphical parameter is whether to draw the error bars. These can be hidden with the toggle button, or be displayed as either the standard deviation (default), standard error of mean, or the range of replicates.
2. Scatter Plot
The scatter plot displays each replicate as a single point, with the mean values denoted as red lines. All points are plotted as circles except for outliers, which are plotted as triangles. The only option available for these plots is to remove the outliers. This option provides a good overview for inspecting individual replicates and is recommended if you have a high number of variability and/or outliers in your samples.
3. Boxplot
The boxplot option creates a 'box and whisker' diagram. The box represents the interquartile range of the replicates, with 75th and 25th percentiles at the top and bottom respectively. The horizontal line within the box represents the median value. The vertical 'whiskers' represent the maximum and minimum values. These plots are recommended when multiple replicates (>5) are used, as it represents a good standardized method for displaying the distribution.
4. Heatmap
The heatmap option will plot the samples across the x-axis and the regions across the y-axis, with the color in each cell representing the copy number. Here, a diploid region will be colored in yellow, while duplications and deletions will be shown in varying shades of green and red respectively. Hovering the cursor over any box will display additional information and the exact copy number. There are three adjustable parameters specific for these plots: 'Cluster by Sample', 'Plot as replicates', and 'Display values on heatmap'. 'Cluster by Sample' will perform a hierarchical clustering of the samples, rearranging them such that the samples with the most-similar abnormalities will cluster together. A dendrogram is displayed above the plot, with the branch height reflective of the degree of similarity. The 'Plot as Replicates' toggle allows all the individual replicate wells to be plotted, rather than their mean. This can be useful in conjunction with the 'Cluster by Sample' option to ensure that your replicates are closer to each other than they are to other samples. Finally, the 'Display values on heatmap' option will overlay the copy number values on top of the heatmap for quick reference.
iv. Output Table
The "Output Table" Tab will show a series of interactive tables of important
metrics for each chromosome. A separate tab is created for each sample. To download these
tables, press the 'Download Table' button at the bottom of the page.
Tables can be re-named and downloaded in Excel format (.xlsx), with each sample occupying its own tab, or in
comma-separated format (.csv).
ΔCt values are generated by normalising each locus from the sample (Ctx) against its
chr4p control region (Ctchr4x), and each locus from the control sample (Ctc) against
its chr4p control region (Ctchr4c).
These results are used to calculate ΔΔCt value by subtracting the sample ΔCt
from the control ΔCt.
The copy number (Cn) is calculated by taking two to the negative exponent of the ΔΔCt
value and multiplying by 2 to represent the diploid state.
A one-way Analysis Of Variance (ANOVA) test is performed across all loci,
and individual adjusted p-values
are calculated using a post-hoc Tukey honestly significant difference test, which assumes homogeneity of
variances between loci. The p-values are listed to 3 decimal places, with darker shades of red representing
increasing significance levels.
While significance against the chr4p control locus is important,
the p-values of a particular locus against other diploid loci improves the accuracy of identification,
so a locus that is significantly different to all other loci is treated as a more accurate copy number call than
a locus that is only significant to the control region. The median p-value across all loci and the
percentages of loci that are significant against each chromosomal region capture this confidence, and are also given.
Finally, the 'Status' column shows whether the locus is called as normal or abnormal by our gradient-boosted
machine learning algorithm.