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Since this procedure generates a multiple hypothesis scenario where each group will have an individual p-value for each recombination test, users can choose to control the Type 1 errors through the false discovery rate (FDR), configuring POTION to further analyze only genes with corrected q-values smaller than user-defined cutoffs for all tests executed.
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Similarly to the recombination analysis, this step is also a multiple hypothesis testing scenario, and therefore POTION also reports corrected q-values from the list of p-values obtained for all groups evaluated using a given nested model pair (q-values are calculated as explained for recombination detection).
Finally, the simultaneous search for recombination and/or positive selection in several groups of homologs creates a multiple hypothesis-testing scenario that requires correct statistical treatment to control the frequency of Type 1 errors [ 8, 22].
Finally, with the exception of PSP, none of the analyzed software take into account the multiple hypothesis-testing scenarios present during GSPSD.
To evaluate the ability of our method to describe and calibrate a model in a realistic scenario where multiple hypothesis are postulated, we used the model derived by Rodriguez-Fernandez and colleagues to generate pseudo-experimental data.
Multiple hypothesis tracking-based data association is included to be able to deal with ambiguous scenarios.
The multiple hypothesis tracker (MHT) can establish the hypotheses of all possible measurements and keep these hypotheses [4].
In [14], the authors tracked multiple flying targets using a Multiple Hypothesis Tracker (MHT).
All p-values reported are unadjusted for multiple hypothesis testing.
In Multiple Hypothesis Testing, prognostic group labels are randomly permuted.
Step 3: Adjusting for multiple hypothesis testing.
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CEO of Professional Science Editing for Scientists @ prosciediting.com