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Corrected p-values

Clicking **Next**will display a dialog as shown in figure 26.98.

**Figure 26.98:** *Additional settings for the statistical analysis.*

At the top, you can select which values to analyze (see Selecting transformed and normalized values for analysis).

Below you can select to add two kinds of corrected p-values to the analysis (in addition to the standard p-value produced for the test statistic):

**Bonferroni corrected**.**FDR corrected**.

The Bonferroni corrected p-values handle the multiple testing problem by controlling the 'family-wise error rate': the probability of making at least one false positive call. They are calculated by multiplying the original p-values by the number of tests performed. The probability of having at least one false positive among the set of features with Bonferroni corrected p-values below 0.05, is less than 5%. The Bonferroni correction is conservative: there may be many genes that are differentially expressed among the genes with Bonferroni corrected p-values above 0.05, that will be missed if this correction is applied.

Instead of controlling the family-wise error rate we can control the false discovery rate: FDR. The false discovery rate is the proportion of false positives among all those declared positive. We expect 5 % of the features with FDR corrected p-values below 0.05 to be false positive.
There are many methods for controlling the FDR - the method used in ** CLC Genomics Workbench** is that of [Benjamini and Hochberg, 1995].

Click **Next** if you wish to adjust how to
handle the results. If not, click **Finish**.

Note that if you have already performed statistical analysis on the same values, the existing one will be overwritten.