QCanvas Tutorial
1. Launching QCanvas 1.1 Install Java
1.2 Install QCanvas on Windows
2. Main Functions of QCanvas 2.1 Running QCanvas
2.2 Loading Data
2.3 Data Clustering
2.4 Saving Data
3. Visualizing heatmap 3.1 Node
3.2 Tree and Annotation
4. What's New in QCanvas - Data Filtration
5. Notice for QCanvas use
  • 1. Launching QCanvas
  • QCanvas is a Java application verified to run on Windows.

  • 1.1 Install Java
  • If not installed on your computer, download and install Java 1.7 or later.
  • It can be found at main page of QCanvas:

  • 1.2 Install QCanvas on Windows
  • To launch QCanvas:
  •    1)  Go to the the main QCanvas page.
  •    2)  Click the button to download the QCanvas Desktop Application.
  •    3)  Open ‘QCanvas.zip’ file and uncompress the file.
  •    4)  Click the right button on the mouse to install QCanvas1.21.exe and select Run as administrator.
  •    Guide to all process for installation are started from the following window.

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  • 2. Main Functions of QCanvas
  • This program is mainly available to transfer matrix data to clustered heatmap with labels, trees, and nodes.
    The results can be saved as a file of PS, JPG, and Text format.

  • 2.1 Running QCanvas
  • When QCanvas starts, the main windows will appear that looks like this (captured on Window):
  •    1 ) The menu and icons on the top, which is used to open or save data.
       2 ) The navigation bars on the right, which provides functions for clustering and graphic-edition.
       3)  The main panel on the left, which is used to display the heatmap and results of clustering.

  • 2.2 Loading Data
  • To obtain the loading sample data, you can download the file from main page of QCanvas.
  •    1)  Click the [Open] icons or select [Open] tab in the File menu on the top.
  •    2)  Select your input file as Text format.
  •    3)  When the data file is opened successfully, the matrix data are graphically visualized in the main panel.

  • 2.3 Data Clustering
  • Now that you have loaded your data file, you are ready to practice the clustering.
  •    1)  In [Clustering] tab, there are several parameters for similarity function and clustering method.
  •         You can apply the clustering on x- and/or y-axis.
  •    2 ) To run the clustering, set the parameters and click Run Clustering button.
  •    3)  The following new window representing clustered heatmap is opened:

  • 2.4 Saving Data
  •    1)  Click the Save icons or select [Save] tab in the File menu on the top.
  •         You use this window to save your data file as PS, JPG, and Text format.
     PostScript file, which can provide graphic as vector type 
     Image file of high-quality resolution 
     Text-based matrix file same as resulted map 

  •    2)  Give a name to saved file and click Save button.

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  • 3. Visualizing heatmap
  • This program has several applications to edit the visualization.
    You can simply optimize the color, position, and size of clustered heatmap without graphic-editing skill.

  • 3.1 Node

  • [Display Option] tab displays the parameters for editing the node of heatmap.
  • There are four categories of parameters (the fourth category is refereed in the 4th chapter):

  • [1] Color Option
  • You can select the color type along property of each input value - positive, negative, missing, zero.
       1) Click the Color box and open the new window that has the color scope with three tabs - Sample, HSB and RGB.
       2)  And click the Color Contrast button and enter the value. You can define the degree of contrast between colors.
            The bigger value means that the difference between colors is distinct.

  • [2] Range Color Option
  • You can change the color of points contained in the limited range.
       1)  Enter the value that you want to display differently and select the color type.

  • [3] Node size Option
  • Node size of heatmap can be defined simply.
       1)  Click the Set Node Size button and insert the value for height and width.
       2)  Or click the + / - icon to increase or decrease the size vertically and horizontally.

  • The space between tree/annotation and main body of heatmap are set automatically.
       1)  If you want to adjust the gap size, click the + / - icon to increase or decrease the gap size.

  • 3.2 Tree and Annotation

  • In Tree and [Annotation] tab, there are three parameters to set the color, position, and size of tree and annotation.
    You can apply the setting on x- and/or y-axis.

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  • 4. What’s New in QCanvas – Data Filtration
  • QCanvas software, which integrates diverse clustering algorithms and interactive heatmap-displaying interface, provides real-time generation of clustered heatmap.

    Especially, subsets of heatmap data are selectively displayed by using user-defined filters. Data filtrations can be carried out using either given heatmap data or another parameter such as statistical p-values.

  • The fourth category of [Display Option] tab is Data filtering.

       1)  In the File button, open new matrix data used to filtration, which share same annotation with input data.
       2)  And in the Display only with value function, define the appropriate range of limits.
            ' > ' means greater than the number and ' < ' means less than the number.

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  • 5. Notice for QCanvas use
  • There are several notice points to use the QCanvas.

  • 1)  Input File
  •      QCanvas only recognize the input file with extension type of ‘txt’.
  •      And input file have to contain ‘Index’ in the first row and column of file.

  • 2)  Save with Extension 'ps'
  •      When you save the results as the PS format, it can be transferred to PDF format in the illustrator program.

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  • Last update: Feb. 06, 2018 by Hyojung Kang