Empirical Permutation P

Estimate permutation p-value with plus-one correction.

Description

An empirical permutation p-value counts supplied null statistics at least as extreme as the observed statistic.

An empirical permutation p-value counts supplied null statistics at least as extreme as the observed statistic. Plus-one correction avoids a zero estimate from a finite permutation list.^[1]

Estimate permutation p-value with plus-one correction.

When to use Empirical Permutation P

Use this tool to estimate permutation p-value with plus-one correction.

Prepare the measured profile, formula counts, upstream model outputs or caller-defined reference criteria requested. Keep paired entries aligned and units, sample basis and preprocessing consistent.

How to use Empirical Permutation P and understand its results

Prepare the measured profile, formula counts, upstream model outputs or caller-defined reference criteria requested. Keep paired entries aligned and units, sample basis and preprocessing consistent.
Enter observedStatistic, permutedStatistics, twoSided using the field table and calculation rules, then run the tool.
Read extremeCount, empiricalP. The explanation below defines the units, signs, ordering and any flags or placeholder values.
If the tool reports an input issue, correct the values and run it again. Apply the stated assumptions when interpreting a successfully returned result.

Input field	Meaning	Value type; see rules below	Requirement
observedStatistic	Observed statistic	number	Required
permutedStatistics	Permuted statistics	list of number	Required
twoSided	Two sided	boolean	Required

Enter finite observed statistic, a nonempty finite null list and a two-sided flag. One-sided mode counts raw values≥observed; two-sided mode counts absolute values≥absolute observed. Return count and corrected p.

p=(extremeCount+1)/(permutationCount+1)

Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.

Output field	Meaning	Value type
extremeCount	Extreme count	number
empiricalP	Empirical p	number

json

{
  "input": {
    "observedStatistic": 3,
    "permutedStatistics": [
      1,
      2,
      4
    ],
    "twoSided": true
  },
  "output": {
    "extremeCount": 1,
    "empiricalP": 0.5
  }
}

Limitations and assumptions

Permutations are not generated or checked for exchangeability. No model fitting or multiple-testing adjustment is included.

Numeric inputs must be finite. Follow the calculation-specific rules for overflow, underflow and exceptional cases. Lists are limited to 100,000 entries; the rules above may require smaller limits. Missing required fields, extra fields, wrong value types and violations of the calculation rules are input errors.

Alternative or Complementary methods

Use Pathway Overrepresentation: Calculate hypergeometric pathway over-representation and upper-tail probability. For a complementary task, use Metabolite Transcript Correlation: Build a metabolite-by-transcript Pearson correlation matrix.

References

Empirical Permutation P — tool.io

Similar or alternative tools

Pathway Overrepresentation
Calculate hypergeometric pathway over-representation and upper-tail probability.
Metabolite Transcript Correlation
Build a metabolite-by-transcript Pearson correlation matrix.