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samr.internal

Internal samr functions


Description

Internal samr functions

Usage

ttest.func(x, y, s0 = 0, sd=NULL)
wilcoxon.func(x, y, s0 = 0)
onesample.ttest.func(x, y, s0 = 0, sd=NULL)
paired.ttest.func(x, y, s0 = 0, sd=NULL)
cox.func(x, y, censoring.status, s0 = 0)
multiclass.func(x, y, s0 = 0)
quantitative.func(x, y, s0 = 0)
patterndiscovery.func(x,s0=0, eigengene.number=1)
timearea.func(x, y, s0 = 0)
sumlengths(aa)
detec.slab(samr.obj, del, min.foldchange)
detec.horiz(samr.obj, cutlow, cutup, min.foldchange)
localfdr(samr.obj, min.foldchange, perc = 0.01, df = 10)
predictlocalfdr(smooth.object, d)
qvalue.func(samr.obj, sig, delta.table)
foldchange.twoclass(x, y, logged2)
foldchange.paired(x, y, logged2)
est.s0(tt, sd, s0.perc = seq(0, 1, by = 0.05))
permute(elem)
sample.perms(elem, nperms)
permute.rows(x)
insert.value(vec, newval, pos)
integer.base.b(x, b = 2)
varr(x, meanx = NULL)
mysvd(x, n.components=NULL)
getperms(y, nperms)
compute.block.perms(y, blocky, nperms)
parse.block.labels.for.2classes(y)
parse.time.labels.and.summarize.data(x, y, resp.type,time.summary.type)

check.format(y, resp.type, censoring.status = NULL)
samr.const.quantitative.response
samr.const.twoclass.unpaired.response
samr.const.survival.response
samr.const.multiclass.response
samr.const.oneclass.response
samr.const.twoclass.paired.response
samr.const.twoclass.unpaired.timecourse.response
samr.const.twoclass.paired.timecourse.response
samr.const.oneclass.timecourse.response
samr.const.patterndiscovery.response
resample(x, d, nresamp=20)
wilcoxon.unpaired.seq.func(xresamp, y)
wilcoxon.paired.seq.func(xresamp, y)
multiclass.seq.func(xresamp, y)
quantitative.seq.func(xresamp, y)
cox.seq.func(xresamp, y, censoring.status)
rankcol(x)
samr.compute.delta.table.seq(samr.obj, min.foldchange=0, dels=NULL)
samr.seq.null.err(samr.obj, min.foldchange, cutup, cutlow)
samr.seq.detec.slabs(samr.obj, dels, min.foldchange)
generate.dels(samr.obj, min.foldchange=0)
foldchange.seq.twoclass.paired(x, y, depth)
foldchange.seq.twoclass.unpaired(x, y, depth)
samr.compute.delta.table.array(samr.obj, min.foldchange=0, dels=NULL, nvals=50)
## S3 method for class 'SAMoutput'
plot(x, ...)
## S3 method for class 'SAMoutput'
print(x, ...)

Details

These are not to be called by the user.

Author(s)

Jun Li and Balasubrimanian Narasimhan and Robert Tibshirani


samr

SAM: Significance Analysis of Microarrays

v3.0
LGPL
Authors
R. Tibshirani, Michael J. Seo, G. Chu, Balasubramanian Narasimhan, Jun Li
Initial release

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