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Missing Pattern


The Missing Pattern command will summarize missing data in Data object into a new table with a pattern and its frequency. It is most commonly used to figure out if there are any particular patterns of missing data (for instance, whole observations or whole variables with missing data). The results will be generated in the Solution Explorer under the Summarize folder of the Table section.

To run this module, type MicroArray | Summarize | Missing Pattern.

Missing pattern menu.png

Input Data Requirements

This module works on -Omic data types.

General Options


Add file

  • Project & Data: The window includes a dropdown box to select the Project and Data object to be filtered.
  • Variables: Selections can be made on which variables should be included in the filtering (options include All variables, Selected variables, Visible variables, and Customized variables (select any pre-generated Lists)).
  • Observations: Selections can be made on which observations should be included in the filtering (options include All observations, Selected observations, Visible observations, and Customized observations (select any pre-generated Lists).
  • Output name: The user can choose to name the output data object.


  • Group:A "Group" selected from the columns in the Design Table can be used to generate patterns. If there is no group of interest, select the ID column (in this case the ID column is called chip) to perform the analysis on each sample individually.

Output Results

Given the following data in an -Omic object, with two rows containing two columns with missing data, and one row missing data in a different column:


The following summary table will be generated by Summarize Missing Pattern:

Microarray SummarizeMissingPattern Output.png

In this dataset, three rows are missing zero values, so the first report row indicates this. Two rows are missing values in columns 4 and 6 (when sorted alphabetically, i.e. Sample D and Sample F). Finally, one row is missing a value in column 1 (alphabetically, Sample A).

If one or more rows (variables) were missing values for all samples, this row would have missing pattern 111111, with Count indicating the number of rows missing all values.

If one or more columns (samples) were missing all variable data, then every report row pattern would have a 1 in that column's position.



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