collectBest {GGtools} | R Documentation

## given a collection of All.cis outputs (cisRun instances) compute FDRs for various filterings

### Description

given a collection of All.cis outputs (cisRun instances) compute FDRs for various filterings

### Usage

    collectBest(fns,
     targetname = "harvest",
     mafs = c(0.01, 0.02, 0.025, 0.03333, 0.05, 0.075, 0.1),
     hidists = c(10000, 25000, 50000, 75000, 1e+05, 250000), interimSaves=FALSE)

    collectFiltered( fns, targetname="harvest",
       mafs = c(.01, .02, .025, .03333, .05, .075, .1),
       hidists = c(10000, 25000, 50000, 75000, 100000, 250000),
       filterFun = cis.FDR.filter.best, filtApplier=lapply,
       interimSaves=FALSE)

### Arguments

`fns` | names of .rda with the cisRun outputs
`targetname` | basename of rda file to be emitted
`mafs` | lower bounds on MAF for filtering
`hidists` | upper bounds on cis radius for filtering
`filterFun` | function like GGtools:::cis.FDR.filter.best
`filtApplier` | function like lapply
`interimSaves` | logical, if TRUE save list at each maf/dist transition

### Details

`pifdr` is repeatedly used to generate conditional plugin FDR for different filtering criteria

### Value

a list of lists is written to disk incrementally, as the job can be long running

### Note

This is the workhorse of sensitivity analysis. Permits counting of genes with eQTL at selected FDR for various criteria on cis radius and MAF.

### Examples

    ## Not run:
    #
    # contents of fns are two chromsomes of cis runs for CEU
    #
      fns = dir(system.file("rdas", package="GGtools"), full=TRUE)
      cc = collectBest(fns, mafs=c(.01, .05), hidists=c(10000, 50000))
      sapply(cc, sapply, function(x) sum(x$fdr <= 0.01))
    #
    # this tells us which to keep
    #
      kp = cc[["0.05"]][["50000"]]
      kp = kp[kp$fdr <= 0.01,]
    #
    # the hits are in the table above; the following function
    # retrieves the initial scores giving rise to the filtered
    # hits
    #
      pullHits = function(fns, atts) {
        tmp = lapply(fns, function(x) get(load(x)))
        kl = lapply(tmp, function(x) paste(names(x), x$snp, sep=":"))
        attk = paste(atts$genes, atts$bestsnp, sep=":")
        tmp = lapply(1:length(tmp), function(x) tmp[[x]][ match( attk, kl[[x]], nomatch=0 ) ])
        curans = do.call(c, lapply(tmp, as, "GRanges"))
        neword = match( attk, paste(names(curans), curans$snp, sep=":"))
        newfdr = atts$fdr[neword]
        curans$fdr = newfdr
        curans
        }
      pullHits( fns, kp )
    #
    #
    #
    #   after executing code in example for All.cis (protected by dontrun)
    #   and running save(f1, file="f1.rda"), the following will work
    # genewise max score
        cf1 = collectFiltered("f1.rda", mafs=.02, hidists=25000, targetname="gwise")
    # SNPwise scores, all
        cf2 = collectFiltered("f1.rda", mafs=.02, hidists=25000, targetname="swise",
             filterFun = cis.FDR.filter.SNPcentric.complete )
    # SNPwise scores, best per SNP when SNP is cis to multiple genes
        cf3 = collectFiltered("f1.rda", mafs=.02, hidists=25000, targetname="swise2",
             filterFun = cis.FDR.filter.SNPcentric )

    ## End(Not run)  # end dontrun

[Package GGtools version 5.18.0 Index]