Introduction

The software can now automatically analyse High Resolution Melt (HRM) data to generate difference plots and represents results in clusters to easily identify genotypes.

Performing Automatic HRM

To demonstrate Automatic HRM open up the “MyGo Pro HRM Class 4 SNP.ppf” from the demo date folder and select the Profile tab. To perform Automatic HRM analysis you will need to perform a melt. A melt can follow an amplification or can be performed on its own if pre-amplified tubes are available. In this case we have a High Resolution Melting phase which has proceeded an amplification. The range of temperatures covered by the High Resolution Melting phase determines what data will be available for analysis - this range should cover the entire range where interesting melt features may occur, with some margin above and below.

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Click on the Samples tab to view the samples and targets for this experiment:

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The samples layout for an Automatic HRM experiment is generally simple - samples should be assigned as normal, and all targets will generally use the same dye. The Automatic HRM analysis can analyse multiple targets but will analyse a single target in this example. The target can be present as an unknown, standard or negative, as appropriate for the experiment - all target types will be analysed. In the example experiment, all wells contain the same target as an unknown.

Select Analysis Type

Click the Analysis tab, Automatic tab and add a High Resolution Melt (Auto) analysis from the Select Analysis Type window. If not already present learn how to do this in the Selecting Analysis Type section.

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Automatic clustering

The example data file already contains a High Resolution Melt (Auto) analysis. In this case the software has automatically clustered 3 genotypes. In the event where the Auto High Resolution Melt analysis is not already present, the software will automatically detect clusters when the Auto High Resolution Melt analysis is added to the experiment.

Samples as Plate

The Samples as Plate view shows the features described in Working with Plate Displays

Results as Table

Click the Results tab, if it is not already selected. This shows the common features present in the Results as Table layout, as shown in General Table Layout. Additional columns include an Assigned and Inferred Genotypes column that will be covered in more detail further on in this section.

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HRM Plots

In the top left hand side of the screen there are three tabs labelled Difference, Normalized and Raw.

Difference Plot

The Difference plot as shown below is automatically generated - there is no need for you to set normalization boundaries.

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Normalized Plot

The Normalized tab shows the automatically generated normalized view. The software has selected the optimum ranges to set for normalizing the fluorescence intensity.

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Raw Plot

The Raw tab is the raw data before automatic normalization and difference analysis.

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The top right hand side of the screen shows two tabs including Clustering and Notes. Clustering is a clustered representation of the difference plot to easily visualize potential genotypes. An ellipse is drawn around each cluster to show the size and shape of the cluster. Vector parameters 1 and 2 help to cluster genotypes in a scatter graph format.

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Inferred Genotypes

In the Results tab there are two genotype-related columns. The initially empty Assigned genotype column contains user-assigned genotypes. The Inferred genotype column assigns wells based on the information available : the results of the automatic clustering, and any additional user-specified information in the Assigned genotype column. The inferred genotype Cluster colors are consistent with the colors of curves in the Difference, Normalized, Raw and Clustering graphs.

Assigned Genotypes

Generally, the work here is done and further user input is not needed : the data has been grouped into clusters corresponding to the different genotypes that are present in the wells. All further actions we will describe here allow the user to name and/or color the genotypes as desired, use controls, and/or, in rare cases, influence the clustering result.

Selecting Wells and Assigning Genotypes

To assign genotypes, firstly add genotypes to the Genotypes pane on the bottom right hand side of the screen by selecting the “+” icon. Genotypes can be renamed by double clicking the default name and typing in a desired name. Select the genotype you wish to assign.

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Secondly, select the wells you wish to assign a genotype to. This can be done by selecting wells in the Results table or selecting either clusters in the Clustering graph or difference curves in the Difference plot. Once selected, press the Assign button. This will assign the selected genotype to each selected sample.

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When genotypes have been assigned the Assigned genotype column in the Results Table will now include your assigned genotypes. The inferred genotype column changes to accommodate the new information. Graphical representations of these genotypes will also be colored to the user’s chosen genotype colors.

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Un-assigning Genotypes

Genotypes can be unassigned by selecting the desired wells, and then clicking the Clear button. In the example below, all gen. 3 wells have been unassigned. When no well within a cluster has an associated genotype, the default Inferred genotype reappears. With this in mind cluster colors will depend on whether they have been assigned a genotype or are using the default inferred genotype colors.

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Genotype Clusters

Genotypes do not have to be assigned to all wells : assigning just one well will assign the whole associated cluster (1). If you assign the same genotype to wells in different clusters, the cluster will be forced to join (2). If you assign a different genotype to two wells within the same cluster, the cluster will be forced to split (3).

Assigning a Cluster (1)

A1 has been assigned with gen.1 and the entire cluster is now gen.1

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Joining Clusters (2)

D5 and A1 have been assigned gen.1 and has forced the original clusters to join.

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Splitting Clusters (3)

B6 and B8 have been assigned different genotypes and has forced the original cluster to split as indicated by the small cluster around the pink triangle. The clustering graph has been zoomed in.

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Genotype Control

Genotypes can be defined when setting up samples by using Custom Controls. These controls will assign all samples with the same inferred genotype to the same genotype control. This genotype can not be removed or overwritten in the analysis module and if you wish to remove it you must do so in the sample setup. For more information of Genotype Controls please refer to Samples Setup in the Experiment section.

Cluster colors

Clustering colors can be modified to show Inferred genotype, Sample or Assigned genotype. In the Clustering tab on the top right hand of the screen there is a Color by: drop down menu. Selecting Sample will color the clusters based on how samples are assigned in the Samples tab*.*

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Selecting Assigned genotypes will color clusters depending on how the user has assigned genotypes to the samples. In the example below all clusters are colored grey which indicates genotypes have not yet been assigned.

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Genotypes as Plate View

Genotypes can also be viewed using the plate view under the Genotypes tab. In the example below genotypes are represented by the Inferred genotypes. These colors will change to Assigned genotype colors if genotypes are assigned to wells.

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