A histogram is a plot that summarizes the underlying frequency of a set of data with the variable of interest on one axis and the frequency distribution of that variable in the other axis. In Partek Flow, histogram can be invoked on continuous or categorical variable.
Invoking a histogram
From a data viewer session, drag the histogram icon onto the data viewer canvas click on New plot > Bar chart (Figure 1).
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SubtitleText | Drag histogram plot (red rectangle) onto data viewer canvassSelect the Bar chart option from the New plot menu. |
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AnchorName | Invoke Histogram 1 |
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Upon dropping the histogram clinking on the canvas Bar chart menu, a dialogue opens up with the different data nodes sources that can be displayed on the histogram. Select your data node of interest and the content data (Figure 2).
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SubtitleText | Select Normalized count the appropriate data node (red) and content data to display on the histogram plot |
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AnchorName | Plot datanode on histogram |
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The first row in the data will be displayed by default in the histogram and in this case, it is the histogram of the expression values for the gene A1BG (Figure 3).
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SubtitleText | Histogram showing the distribution of AIBG expression (red) |
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AnchorName | Default display on histogram |
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Histogram of Continuous variables
Change the data displayed on the histogram by using the Configuration settings > Content > Data and Configure > Axes menu and selecting the desired variable to display. Here the data displayed was switched to “Expressed genes” which is a continuous variable (Figure 4).
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SubtitleText | Histogram showing the distribution of expressed genes variable (red rectangle) |
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AnchorName | Histogram of expressed genes |
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Use the "Sort by" function to sort the plot. The default sorting is by Value on the x-axis and this default setting is sorted in ascending order. Users have the option to change that by changing the Default to value or frequency in the sort option (Figure 5)
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SubtitleText | Sort by function can be by Value or Frequency (red) |
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AnchorName | Sorting options for continuous variable |
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Users can color the histograms by a categorical attribute using the Color by function (in red below). The bars were colored by the graph-based classifications in the example below (Figure 6).
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SubtitleText | Histogram of expressed genes sorted by Value in descending order (red) |
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AnchorName | Image of expressed genes sorted by Value and in descending order |
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annotated by automatic classifications | AnchorName | Annotate histogram |
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The bars in the histogram above were stacked. They can be unstacked using the Style menu as seen below in red (Figure 7).
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SubtitleText | Unstacked bars in the histogram plot |
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AnchorName | Unstacking histogram |
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Users also have the option to bin by either Count or Size. When binned by Count, the user specifies the number of bins for the data and the distribution is fit into the specified number of bins. Data below is binned by Count (Figure 78).
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SubtitleText | Histogram of expressed genes with number of bins specified as 510 |
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AnchorName | Image of expressed genes with bin Count of 5 |
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When binned by Size, the user specifies the number of items in the bin (size of a bin). This is used to calculate the number of bins required for the data. Data below is binned by Size (Figure 810).
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SubtitleText | Histogram of expressed genes with size of bin specified as 1075 |
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AnchorName | Value binned by Size image |
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Histogram of Categorical variable
In the figure below, a categorical variable (Classifications) was selected to be displayed in the plot and sorted by frequency in ascending order (Figure 9).
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SubtitleText | Histogram of Classifications variable sorted by ascending order of Frequency |
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AnchorName | Image with Categorical data displayed on plot |
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For categorical data, the user can select number of groups in the categorical variable to be binned together. In the figure below, the Classifications variable is binned into groups of 5 (Figure 10).
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SubtitleText | Histogram of Classifications variable with bin groups set as 5 |
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AnchorName | Binning of Categorical variable |
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SubtitleText | Different modes of Pie Chart. |
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AnchorName | Different modes of Pie Chart |
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Once you are pleased with the appearance of the Pie plot, push Save image button to save it to the local machine or click Save button to save the Data Viewer. The resulting dialog (Figure 8) controls the Format,Size and Resolution of the image file. The image will be saved in your favorite format (.svg, .png and .pdf).
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SubtitleText | Save image dialog (default settings) |
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AnchorName | Save image |
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Click the Save image button Image Added to save a PNG or SVG image to your computer.
Click the Send to notebook button Image Added to send the image to a page in the Notebook.
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