Understanding the P-Value of Overlap Statistic in IPA

October 17, 2017
Learn how to interpret your p-value of overlaps results in IPA. You can gain a deeper understanding of the right-tailed Fisher’s Exact Test, why it’s used in IPA, how the results are calculated, and caveats to keep in mind when interpreting your results.
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0:00-1:09  Introduction to the video. The two types of p-values that are relevant for IPA and how they differ.
1:09-2:25  History of the Fisher’s Exact Test: the “Lady Tasting Tea” experiment.
2:25-5:50  Hypothesis testing for enrichment in IPA. The reference set, the null hypothesis used, and the overlap of molecules defined.
5:51-7:58  Why the right-tailed Fisher’s Exact Test is used in IPA.
7:58- 8:41  Explanation of sampling and expected proportions from the hypergeometric distribution.
8:41-9:34  Defining significance levels in the distribution. Why only the right-tailed, rather than two-tailed test, is considered in IPA.
9:35-11:04  The p-value defined and default significance level used in IPA.
11:04-11:12  How the p-value is calculated.  How data is entered into the 2 x 2 contingency table and the formula used.
11:13-13:34  Example calculation and interpretation using the “Lady Tasting Tea” experimental data. Why the p-value of overlap calculations are Exact.
13:35-15:09  Transcriptomics example: Number of molecules tested and how they are categorized.
15:10-16:10  Transcriptomics example: data in 2 x2 contingency table, p-value calculation performed and interpreted.
16:11-18:07  Caveats for using and interpreting the p-value of overlap statistic in IPA.
18:08-18:36  Where to find more information about IPA and Customer Support information.

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