With null distributions estimated using the generateNull() function, p-values are estimated using a one-tailed test. A minimum p-value of 1/B can be achieved with B permutations.

getPvals(permuteResult, scoredf, subSamples = NULL)

Arguments

permuteResult

A matrix, null distributions for each sample generated using the generateNull() function

scoredf

A dataframe, the scored results of samples under test generated using the simpleScore() function

subSamples

A vector of sample labels/indices that will be used to subset the score matrix. All samples will be scored if not provided

Value

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.

Examples

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()
#> $MulticoreParam #> class: MulticoreParam #> bpisup: FALSE; bpnworkers: 1; bptasks: 0; bpjobname: BPJOB #> bplog: FALSE; bpthreshold: INFO; bpstopOnError: TRUE #> bpRNGseed: 1; bptimeout: 2592000; bpprogressbar: FALSE #> bpexportglobals: TRUE #> bplogdir: NA #> bpresultdir: NA #> cluster type: FORK #> #> $SnowParam #> class: SnowParam #> bpisup: FALSE; bpnworkers: 30; bptasks: 0; bpjobname: BPJOB #> bplog: FALSE; bpthreshold: INFO; bpstopOnError: TRUE #> bpRNGseed: ; bptimeout: 2592000; bpprogressbar: FALSE #> bpexportglobals: TRUE #> bplogdir: NA #> bpresultdir: NA #> cluster type: SOCK #> #> $SerialParam #> class: SerialParam #> bpisup: FALSE; bpnworkers: 1; bptasks: 0; bpjobname: BPJOB #> bplog: FALSE; bpthreshold: INFO; bpstopOnError: TRUE #> bpRNGseed: ; bptimeout: 2592000; bpprogressbar: FALSE #> bpexportglobals: TRUE #> bplogdir: NA #> bpresultdir: NA #>
# 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)