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P-Value Plot Types

16.2 P-Value Plot Types

16.2.1 P-Values Sorted by Var # from the Manual Split Window

In this type of plot, you may select which level of multiplicity adjustment for the p-values you would like to plot: P (raw P), aP (adjusted P), or bP (bonferroni-adjusted P).

In addition, you can consolidate either the (raw) p-values or the adjusted p-values using Simes’ method over a moving window of tests (potential splits). A slider allows you to select the size of this moving window. The moving window may, for instance, consist of genetic markers that are within proximity of each other according to the genetic marker map. The result for each position of the window is shown for the test at the window’s center. (NOTE: Zero is shown for tests near the edge of the plot which are not at the center of any window.)

With Simes’ method, a process resembling finding the False Discovery Rate is used. If there is a significant effect within the window influencing more than one p-value, Simes’ method will show this. On the other hand, Simes’ method will “correct” single p-values that are much more significant than their neighbors. See 26.20.

NOTE: It is often useful to plot genetic split or haplotype trend regression p-values using this option in order to locate the region of a chromosome where there are more associations. An example of such a plot is depicted next for data_312.ghd.

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The same plot with Simes’ method applied with a window size of 17 is shown next. Note that the main effects are from marker12 to marker53, centered somewhere around marker24.

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16.2.2 FDR and P-Values from the Manual Split Window

This type of plot shows the values of the False Discovery Rate (FDR) corresponding to the adjusted p-values (aP) of the respective tests (potential splits). The plot is sorted by the adjusted p-values (aP).

The interpretation of the False Discovery Rate is, “What would the rate of false discoveries (false positives) be if I accepted ALL of the tests at or below the adjusted P-value of this test?” See 26.20.

You may also plot p-values with a multiplicity adjustment – P (raw P), aP (adjusted P), or bP (bonferroni-adjusted P) – in addition to plotting the False Discovery Rate.

16.2.3 P-Values Resulting from Regression Analysis Using a Moving Window

This type of plot, which is sorted by variable number, allow you to select from P (raw P) or bP (bonferroni-adjusted P) for the level of multiplicity adjustment for the p-values.

In addition, if you have clicked an x-axis location to view the p-values resulting from the left edge of the moving window being at that location, you can press a button to view the complete regression results for that location. (See 16.3.4.)

16.2.4 Spreadsheet Column Plots

Plots can be created displaying any real or integer column or columns. The column values will be plotted against the rows. These plots allow you to view any spreadsheet-format analysis results as a plot.

These plots are sorted by spreadsheet row, according to how the spreadsheet was most recently sorted before creating the plot. Optionally, instead of the values v of any spreadsheet column, you may plot the negative logarithms of the column’s values -log ₁₀v.

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