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Estimating Missing Values by a Measure of Central Tendency



The process of handling missing values consists of two steps: first, genes that have a minimum number of missing values are removed; and second, the remaining missing values are estimated using a measure of central tendency (mean or median).

On the Estimate Missing Values dialog, when the Remove Genes That Have Missing Values slider is set to 1, the rest of the dialog is grayed out. This is because all genes that have at least one missing value will be removed leaving no missing values to be estimated.



1. Click an incomplete dataset in the Experiments navigator. The item is highlighted.

2. Click the Missing Value Estimation toolbar icon , or select Estimate Missing Values from the Data menu, or right-click the item and select Estimate Missing Values from the shortcut menu. The Estimate Missing Values dialog is displayed.

3. Set the parameters.



Remove Genes That Have Missing Values

Set the threshold for culling genes prior to missing value estimation (1 = remove all genes that have missing values).

Replacement Technique

Select Measure of Central Tendency.


Select which measurement to use: Median or Mean.


4. Click OK. The Experiment Progress dialog is displayed. It is dynamically updated as the Estimate Missing Values operation is performed. To cancel the Estimate Missing Values operation, click the Cancel button.


Related Topics:

Overview of Estimating Missing Values

Nearest Neighbors Missing Value Estimation