With null distributions estimated using the
function, p-values are estimated using a one-tailed test. A minimum p-value
of 1/B can be achieved with B permutations.
A matrix, null distributions for each sample generated
A dataframe, the scored results of samples under test
generated using the
A vector of sample labels/indices that will be used to subset the score matrix. All samples will be scored if not provided
Estimated p-values for enrichment of the signature in each sample. A p-value of 1/B indicates that the estimated p-value is less than or equal to 1/B.
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ranked <- rankGenes(toy_expr_se) scoredf <- simpleScore(ranked, upSet = toy_gs_up, downSet = toy_gs_dn) # find out what backends can be registered on your machine BiocParallel::registered() # the first one is the default backend, and it can be changed explicitly. # See vignette for more details permuteResult = generateNull(upSet = toy_gs_up, downSet = toy_gs_dn, ranked, B =10, seed = 1, useBPPARAM = NULL) # call the permutation function to generate the empirical scores # for B times. pvals <- getPvals(permuteResult,scoredf)
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