Figure 24

Interpreting q-values and calibrating q-value cut-offs. Four plots to facilitate q-value interpretation and calibrate the q-value cut-off [45, 46] using the function qplot(). (a) The estimated portion of the true null hypotheses (π₀) versus the tuning parameter λ ('bootstrap' method is used for automatically choosing λ by the software and π₀ estimate is 0.978). (b) The expected proportion of false positives (q-value) for different p-value cut-offs. (c) The number of significant candidates for differential expression for each q-value. (d) The expected portion of false positives as a function of the number of candidates for differential expression called significant. The dotted black line in (a) is π₀ approximation using bootstrap method; the dotted color lines in (b) (green for expected false positives (FP) on average < 1 and red for < 0.1) are used to match q- and p-value levels (0.011 and 0.0016 for expected FT < 1, 0.0015 and 0.000015 for expected FT < 0.1, correspondingly) for the expected FP cut-offs; the dotted color lines in (c) are used to match q-value cut-offs (0.011 and 0.0015) and the number of significant tests on average (83 and 59); the dotted color lines in (d) are used to match expected FP cut-offs (< 1 and < 0.1) and the number of significant tests on average (83 and 59, correspondingly).