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The app screen is divided into a narrow navigation sidebar on the left and a wider workspace area on the right.
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<img src="uploads/4417496b89ef23ca0ef44de8c59b127f/new.png" width="95%">
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## The navigation sidebar
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The navigation sidebar lists available tools. Clicking on a tool in the sidebar switches the app to the corresponding workspace.
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## The workspaces
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Upon starting, the app opens with the data input workspace. Other tools can only be used after uploading a data file.
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### Data input
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This is where the data table is uploaded to the app. Because the app makes few assumptions on the table content, it is up to the user to indicate which columns contain relevant information. The data input workspace is divided into boxes corresponding to the different input required from the user:
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* **Input data file**
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This is where the tabular data file is selected and uploaded to the app server. Before uploading a file, make sure that the file has a header and that the correct column separator and quote type are selected.
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* **Plot variables**
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This allows to select one or two columns whose values will be shown in a scatterplot.
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* **Additional variables to display on hover**
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By default when hovering over a point in the plot, the values of the plot variables are shown in a table below the plot. This box allows the selection of additional variables to be displayed when hovering over a data point.
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* **Columns to hide**
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Hiding columns minimizes the amount of horizontal scrolling needed to reach columns on the right-hand side of the table when all columns can't fit on screen.
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* **Groups**
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This allows to select one column whose values will be used to set colours for the points in the plot. Only 9 distinct colours are available so any selected column with more than 9 distinct values will be ignored.
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* **Images**
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If images are associated with the data file, select the image root directory then one or two columns containing the paths to the images relative to the selected root directory. If a column name contains the pattern 'image.*path', this column will be preselected in the image 1 field.
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* **ROIs**
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If the data table rows correspond to ROIs of associated images, select here the columns containing the coordinates of the ROIs anchor points.
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If the rows correspond to time points only (i.e. with no ROI definition), select only a column for frame coordinates and leave X and Y coordinates empty. If a column name contains the pattern 'coordinate_X|Y|Z|time', it will be preselected in the matching ROI coordinate field (e.g. a column named cell_coordinate_x will be preselected as column for coordinate X).
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* **Save parameters**
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The information entered into the other boxes (except for the input data file) can be saved and downloaded into a configuration file in rds format. When a data file is uploaded, a browse button will appear allowing selection and upload of a previously saved configuration file. Upon upload of this file, input boxes will be populated with the saved values from the file.
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Currently no attempt is made at checking the validity of an uploaded configuration file. Mismatches between the configuration file values and the column names of the uploaded data file can result in unpredictable behaviour.
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### Explore
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The explore workspace is where the interactive data visualization happens. It is divided into 3 areas:
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* **A plot** area on the top left of the screen. By default, this shows a scatterplot of the variables selected in the data input section. Clicking on a data point in the plot selects it in the data table below and opens the corresponding image(s). If the point is associated with x,y coordinates then a red dot is added to the image(s) at the position given by these coordinates.
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* **An image viewer** area next to the plot area. This is where images selected under image 1 in the data input section will appear.
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Clicking on the image selects the corresponding row in the data table and highlights the corresponding point in the plot. If rows correspond to ROIs then the click position is indicated by a red dot and the data point corresponding to the closest ROI in the image is selected in both the data table and the plot.
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* **A data table** area at the bottom of the screen. The data table shows the content of the uploaded data file. A tab allows switching to a second image viewer where images selected under image 2 in the data input section will appear. This second image viewer behaves like the one described above. Clicking on a table row selects it and highlights the corresponding point in the plot. No image is shown when selecting multiple rows. The table is searchable globally using the 'Search' box in the top right corner above the table or by column using the boxes atop each column. Searches filter the rows to be displayed in the table. To select all the rows and highlight them in the plot, click the button labeled 'Show filtered rows in plot' above the table. To deselect all selected rows, click the 'Clear selection' button. To annotate the selected rows, click the 'Annotate selection' button. This is only available if an annotation column has been chosen in the 'Annotate' section.
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### Annotate
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Individual data points, i.e. rows of the data table, can be associated with a label. Annotation starts by visiting the 'Annotate' section (accessible from the sidebar). There, a column to hold the annotations can be selected and labels defined. If an existing column is selected, its distinct values will be available as labels. New labels can also be added. Alternatively, a new column can be created, in which case, new labels must be provided. New labels must be entered as a comma-separated list. Once done, choices must be confirmed by clicking the 'Apply' button. Annotations can then be performed using the 'Annotate selection' button in the 'Explore' workspace.
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### Dimensionality reduction
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To help visualize the overall structure of the data, several numerical variables can be combined into a 2d projection. The numerical columns and method to use can be selected in the 'Dimensionality reduction' section. Application of a dimensionality reduction method results in the creation of two new columns containing new coordinates for all data points. When running the same method multiple times, coordinates columns are re-used (i.e. new columns are not created for each new run). Upon successful completion of the dimensionality reduction, the new columns are automatically selected for plotting and the view switches back to the 'Explore' workspace.
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### Cluster |