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SubtitleText | After the Apply filter button is selected, you will be presented with a preview of your pipeline. You need to select the appropriate data node to apply the filtering to. In this case, the Antibody capture node |
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AnchorName | Select antibody capture data node as input for filtering task |
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You will see a message telling you a new task has been enqueued.
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SubtitleText | The two normalization tasks produce Normalized counts data nodes |
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AnchorName | Normalized counts output |
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![](/download/attachments/19333481/Normalized_counts.png?version=1&modificationDate=1593085072404&api=v2)
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Merge Protein and mRNA data
For quality filtering and normalization, we needed to have the two data types separate as the processing steps were distinct. For downstream analysis, we want to be able to analyze protein and mRNA data together. To bring the two data types back together, we will merge the two normalized counts data nodes.
- Click the Normalized counts data node on the Antibody Capture branch of the pipeline
- Click Pre-analysis tools in the toolbox
- Click Merge matrices
- Click Select data node to launch the data node selector
Data nodes that can be merged with the Antibody Capture branch Normalized counts data node are shown in color (Figure ?).
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SubtitleText | Select the normalizated gene expression counts to merge the protein counts with |
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AnchorName | Merge protein and gene expression counts |
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- Click the Normalized counts data node on the Gene Expression branch of the pipeline
- Click Select
- Click Finish to run the task
The output is a Merged counts data node (Figure ?). This data node will include the normalized counts of our protein and mRNA data. The intersection of cells from the two input data nodes is retained so only cells that passed the quality filter for both protein and mRNA data will be included in the Merged counts data node.
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SubtitleText | Merged counts output |
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AnchorName | Merged counts output |
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Collapsing tasks to simplify the pipeline
To simplify the appearance of the pipeline, we can group task nodes into a single collapsed task. Here, we will collapse the filtering and normalization steps.
- Right-click the Split by feature type task node
- Choose Collapse tasks from the pop-up dialog (Figure ?)
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SubtitleText | Choosing the first task node to generate a collapsed task |
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AnchorName | Collapse tasks |
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Tasks that can be selected for the beginning and end of the collapsed section of the pipeline are highlighted in purple (Figure ?). We have chosen the Split matrix task as the start and we can choose Merge matrices as the end of the collapsed section.
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SubtitleText | Tasks that can be the start or end of a collapsed task are shown in purple |
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AnchorName | Available tasks to collapse |
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- Click the Merge matrices task to choose it as the end of the collapsed section
- Name the Collapsed task Data processing
- Click Save (Figure ?)
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SubtitleText | Naming the collapsed task |
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AnchorName | Save collapsed task |
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The new collapsed task, Data processing, appears as a single rectangle on the task graph (Figure ?).
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SubtitleText | Collapsed tasks are represented by a single task node |
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AnchorName | Collapsed task |
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To view the tasks in Data processing, we can expand the collapsed task.
- Double-click Data processing to expand it, or right click and choose Expand collapsed task
When expanded, the collapsed task is shown as a shaded section of the pipeline with a title bar (Figure ?).
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SubtitleText | Expanding a collapsed task to show its components |
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AnchorName | Expanding collapsed task |
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To re-collapse the task, you can double click the title bar or click the
Image Added icon in the title bar. To remove the collapsed task, you can click the
Image Added. Please note that this will not remove tasks, just the grouping.
- Double-click the Data processing title bar to re-collapse
References
[1] Stoeckius, M., Hafemeister, C., Stephenson, W., Houck-Loomis, B., Chattopadhyay, P. K., Swerdlow, H., ... & Smibert, P. (2017). Simultaneous epitope and transcriptome measurement in single cells. Nature methods, 14(9), 865.
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