fishersPvalueSumTest | R Documentation |
Fisher's method for combining P-values together consists of studying a test statistic of T = ∑_i -log(P_i) and finding the corresponding point in the cumulative distribution of an appropriately parameterised chi-squared distribution.
fishersPvalueSumTest(testPvalues, ...) ## S4 method for signature 'numeric' fishersPvalueSumTest(testPvalues, ...) ## S4 method for signature 'Pvalues' fishersPvalueSumTest(testPvalues, na.rm = TRUE, rate = 1, ...)
testPvalues |
A numerical vector of P-values to be tested. |
... |
extra-arguments |
na.rm |
remove NA. Default set to TRUE |
rate |
Provide the rate for the exponential in the sum (distributed as a gamma) |
The basic assumption is that P-values are uniformly distributed under the null-hypothesis, meaning that -log(P) \sim exp(1). Recall that if X \sim exp(1) then ∑_{k} X_{k} \sim Γ (k,1) \sim χ^2 (2k) (note that the gamma and erlang distributions are identical for integer k). We therefore simply calculate the point in the cumulative of the gamma distribution
Note that the use of this method for analysis of omics datasets was pioneered by Luo et al.
combinedPval A single P-value combining the results of multiple independent hypothesis tests into one
numeric
: Convert to P-values on the fly
Pvalues
: Fisher's combined probability test
https://en.wikipedia.org/wiki/Fisher%27s_method
https://en.wikipedia.org/wiki/Erlang_distribution
Luo, W., Friedman, M. S., Shedden, K., Hankenson, K. D., & Woolf, P. J. (2009). GAGE: generally applicable gene set enrichment for pathway analysis. BMC Bioinformatics
betaUniformPvalueSumTest
Other P-value sum tests:
betaUniformPvalueSumTest()
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