Computing exact permutation ${\boldsymbol~p}$-values for phosphorylation motifs

Computing exact P-values for DNA motifs

MOTIVATION Many heuristic algorithms have been designed to approximate P-values of DNA motifs described by position weight matrices, for evaluating their statistical significance. They often significantly deviate from the true P-value by orders of magnitude. Exact P-value computation is needed for ranking the motifs. Furthermore, surprisingly, the complexity of the problem is unknown. RESULTS...

Computing exact p - values for DNA motifs ( Part I )

Motivation: Many heuristic algorithms have been designed to approximate p-values of DNA motifs described by position weight matrices, for evaluating their statistical significance. They often significantly deviate from the true p-value by orders of magnitude. Exact p-value computation is needed for ranking the motifs. Furthermore, surprisingly, the complexity of the

Permutation P-values should never be zero: calculating exact P-values when permutations are randomly drawn.

Permutation tests are amongst the most commonly used statistical tools in modern genomic research, a process by which p-values are attached to a test statistic by randomly permuting the sample or gene labels. Yet permutation p-values published in the genomic literature are often computed incorrectly, understated by about 1/m, where m is the number of permutations. The same is often true in the ...

JMASM20: Exact Permutation Critical Values For The Kruskal-Wallis One-Way ANOVA

Computing highly accurate or exact P-values using importance sampling